LIFE AND DEATH IN THE VALLEY OF HEART’S DELIGHT: UNDERSTANDING 
HEALTH AND NUTRITION AT THE SANTA CLARA VALLEY MEDICAL CENTER 

HISTORICAL CEMETERY 

 
By 
 

Lisa Nicole Bright 

 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

 

 
 

2019 

A DISSERTATION 

Submitted to 

Michigan State University 

in partial fulfillment of the requirements  

for the degree of 

Anthropology—Doctor of Philosophy 

 

LIFE AND DEATH IN THE VALLEY OF HEART’S DELIGHT: UNDERSTANDING 
HEALTH AND NUTRITION AT THE SANTA CLARA VALLEY MEDICAL CENTER 

HISTORICAL CEMETERY 

ABSTRACT 

 
By 
 

 

Lisa Nicole Bright 

There are many interconnected variables that directly impact an individual’s health, 

including but not limited to economic status, gender, ethnicity, environment, and access to care.  

Between 2012-2014, a portion of the Santa Clara Valley Medical Center Historical Cemetery, 

located in San Jose, California, was excavated.  The cemetery was in use from approximately 

1875-1935 and served as one of the county’s indigent burial grounds.  This dissertation explores 

the impact of immigration, public health, and structural violence on the biological health of 

individuals interred at the Santa Clara Valley Medical Center Historical Cemetery (VMC).   

 The primary goal of this study is to examine specific and non-specific indicators of 

health, while contextualizing the archaeological and osteological data with the socio-political 

context in which the pathological conditions occurred.  Multiple theoretical paradigms including 

structural violence and epidemiological transitions are used to provide possible explanations for 

the observed health patterns.  The VMC skeletal sample is also compared to archival data sets 

and other historic skeletal samples to examine similarities and differences in expected and 

observed health indicators.   

 

The individuals interred at VMC had higher rates of infectious communicable disease and 

higher infant and neonate mortality rates than comparative samples.  The results of this research 

suggest that the social and health inequalities seen in the VMC skeletal sample can be 

understood by examining the county’s efforts towards public health initiatives, public policy 

 

towards the destitute, and the components of structural violence and institutionalization that 

intertwine these factors.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LIST OF TABLES 

 

LIST OF FIGURES  

 

 

 

 

TABLE OF CONTENTS 

 

 

 

 

 

 

 

 

 

 

 

viii 

xi 

Chapter 1: Introduction 

 

 

1 
Bioarchaeological Approaches to “Health” and Paleopathology                   1 
3 
Research Goals 
Significance of Research 
4 
5 
Outline of the Dissertation 

         

 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 

 

 

 

 

 

 

 

 

 

 

 
 
 

 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
Cemeteries and the Historical Era 
 
Identity 
Interpreting Identity in Historic Cemeteries   
 
Ritual and Identity 
 
 
Placement and Spatial Analysis 
 
 
 
 
Stress/Non-Specific Infections 
 
Measuring Indicators of Health: Infections and Degenerative           23    
Changes 
Paleodemography 

Chapter 2: Theoretical Background 
Introduction 
 
Mortuary Archaeology Theory 
 
 
 
 
 
Bioarchaeology Theory 
Paleopathology Theory 
 
 
 
 
Public Health Theory   
 
Structural Violence 
Epidemiology Transition 
Summary  
 

 
 
Race and Class Issues in Public Health 
 
 
 

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Chapter 3: Historical Background  
 
 
 

 
 
 
 
Mexican Period: 1810-1848 
 
American Period: Post 1848   
Early 20th Century: 1900-1940 
 

Introduction 
 
Historic Era Context   
Spanish Period: 1777-1810 
 
 
 
Immigration Trends 
 
 

 

 

 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 

 
 
 
   
 
 
 
 

 
 
 
 
 
 
 
 

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County Hospital 
  
 The Infirmary Cemetery 
             Other Local Cemeteries 
Conclusion  

 

 

 

 

 
 
 
 

 
 
 
 

 

 

 

Chapter 4: Research Questions & Expectations    
 
 
 
 
 
 
 
 

Introduction 
 
Research Questions and Expectations 
Question 1 
 
 
 
 
Question 2 
 
            Question 3 
 
Question 4 
 
 
            Question 5 
Summary  
 

 
 
 
 
 
 

 
 
 
 
 
 

 

Chapter 5: Materials & Methods 

 

 

 
 

 
 
 

 
 
 
 
 
 

 
 
 
 
Introduction 
 
 
Introduction to Excavation 
 
 
On-Site Data Collection Protocols 
 
 
            Biological Profile   
 
 
 
            Age 
 
 
            Sex  
 
 
 
            Ancestry           
 
 
            Archaeology    
 
Validation Study 
 
 
 
Paleopathology & Indicators of Health 
 
Demographic Analysis 
 
 
 
 
Historical Archives 
 
 
 
            Historic Age 
 
 
            Historic Sex 
 
 
            Historic Ancestry 
 
 
            Historic Pathology 
 
 
            Mission City Memorial Park   
 
Comparative Skeletal Samples 
 
           Milwaukee County Institution Grounds 
 
           Alameda-Stone  
 
 
           Voegtly  
Statistical Analysis 
 
 
 
 
Spatial Analysis 
Summary 
 
 
 
 
 

 
 
 
 
 
 

 
 
 
 
 

 
 
 
 
 

 
 
 
 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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v 

            Chapter 6: Results from VMC 

 

 

 

 

 

 

 
 
 

 

 
 

 
 
 

 
 
 

 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 

Demography of Skeletal Sample 

 
 Specific Infections 

 
 
Introduction 
 
 
Skeletal Results 
 
 
 
 
 
            Age 
 
 
            Sex 
 
 
            Ancestry 
 
 
            Demographic Analysis 
 
Pathology 
 
 
            Nonspecific Infection  
Periostitis and Osteomyelitis   
 
 
 
                          Coccidioidomycosis (Valley Fever)  
 
 
            Treponemal Infections  
 
 
 
            Tuberculosis    
 
Age and Sex Differences 
 
 
 
 
Mortuary Archaeological Analysis 
 
 
             Coffins 
 
 
             Length 
 
             Depth                                  
 
 
 
 
             Width  
 
 
             Shape  
 
 
             Grave Goods   
 
 
 
             Clothing Related Artifacts 
 
 
                           Buttons 
 
 
                           Other Clothing Fasteners 
 
             Jewelry 
 
 
 
             Religious Artifacts 
 
 
Burial Categories 
 
Spatial Analysis 
 
 
Comparing Coffin Shape with other Variables 
 
 
 
              Sex 
 
 
 
              Age 
 
Coffin Dimensions 
 
 
 
 
 
 Artifacts 
 
 
 
              Buttons 
 
 
 
              Single Button Type Burials   
              Multiple Button Burials 
 
 
 
 
 
              All Button Categories              
 
 
 
              Button Co-Occurrence 
              Religious Artifacts 
 
 
 
 
 
 
 
 
 Summary 

 
 
 
 
 
 
 
 
 
 
 
 

 
 

 
 
 

 

 
 
 
 
 

 
 
 
 

 
 
 
 
 

 
 

 

 
 

 
 

 

 
 
 
 

 

 

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Chapter 7: Comparative Studies Results 

 

 

 

 
 

 
 
 
 
 

 
 
Introduction 
Comparing with Historical Records 
 
Santa Clara Infirmary Death Record   
              Nativity 
 
 
              Health 
 
              Infectious Disease 
Comparative Samples  
 
              Demography  
 
              Mission City Memorial Park  
              Alameda Stone 
 
              Alameda Stone Sections 1-2  
              Alameda Stone Sections 3-5  
              Milwaukee County Institution Ground  
              Voegtly 
Health  
Summary 

 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Chapter 8: Discussion 
 

 
 

 
 

 
 

 
 

 

 
 
 
 

Introduction 
Question 1: Does institutionalization and or structural  
violence lead to identifiable biological impacts? 
Question 2: At this time, we know that major issues such as the second  
epidemiological transition, public health reform, immigration, and  
socioeconomic status impact the health and nutrition of people. Given  
the nature and historical context of VMC how did these events effect  
people at VMC?  
               Infant Mortality 
               Disease                         
               Mortality 
 
               Public Health  
               Immigration   
Question 3: Putting the cemetery in context with the historical record  
suggests a set of expectations of particular kinds of pathologies. How  
do these expectations compare with the pathologies documented in the  
skeletal remains? 
Question 4: How does VMC compare to similar cemeteries in terms of  
the consequences of structural and institutional behavior? 
 
Question 5: Are there changes in the cemetery in terms of the spatial  
organization, and might these be attributed to change over time or  
differential treatment of health? 
Conclusion 

 
 
 
 
 

 
 
 
 
 

 
 
 
 
 

 
 
 
 
 

 
 
 
 
 

 
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
 

 

 

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REFERENCES 
 
 
 

 

 
 

 
 

 
 

 

 

 

 

 

 

vii 

LIST OF TABLES 
 
 
 
 

Table 1. Non-metric traits used to ancestry assessment.  Table source Rehor 
               and Beck 2015:5-5.  
Table 2. Historical Cemetery Comparative Sample.   
 
Table 3. VMC Broad Age Category Distribution. 
Table 4. VMC Broad Sex Category Distribution. 
 
 
Table 5. Age Categories Fine Typology. 

 
 
 
 

 
 
 
 

 
 
 
 

 

Table 6. Course Age Categories. 

Table 7. Course Sex Counts.   

 

 

 

 

 

 

 

 

 

 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 

Table 8. a and b values males v. females. 
 
Table 9. Log likelihood difference males v. females.  
Table 10. Non-specific infections by Age and Sex. 
 
 
Table 11. Non-specific infections by sex. 
 
Table 12. Tuberculosis by sex. 
 
 
Table 13.  Coccidioidomycosis by sex. 
Table 14.  Tertiary Syphilis by sex. 
 
 
 
Table 15. Non-specific infections by age. 
Table 16. Coffin Length. 
 
Table 17. Coffin Depth. 
 
 
 
 
Table 18. Coffin Width. 
 
Table 19. Coffin Shape Count & Frequency.  
 
Table 20. Button Pattern Types by Burial Count. 
 
Table 21. VMC Burial Categories by Sex. 
 
Table 22. VMC Burial Categories by Age. 
Table 23. VMC Non-Specific Infections by Burial Category. 

 
 
 
 
 

 
 

 
 

 

 
 

 

 

 

 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 

 

 

 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 

 

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Table 24. VMC Syphilis by Burial Category.  
Table 25. VMC Tuberculosis by Burial Category. 
Table 26. Average Nearest Neighbor Results, significant bolded. 
Table 27. Coffin Shape by Sex. 
Table 28. Coffin Shape by Age. 
Table 29. Coffin Length Descriptive Statistics (length in inches). 
Table 30. Coffin width descriptive statistics (width in inches). 
Table 31. Coffin depth descriptive statistics (depth in inches). 
Table 32. Button categories by sex count. 
 
Table 33. Button co-occurrence correspondence analysis transformed variables. 
Table 34. VMC All Hospital Deaths Age at death distribution. 
 
Table 35. County Hospital Deaths county burials age at death distribution.   
 
Table 36. County Hospital Death private burial age at death distribution. 
Table 37. Sex distribution of VMC, and Hospital Deaths. 
 
 
 
Table 38. α1, β1, α3, and β3 parameters for VMC and county burials.   
Table 39. Hospital Ledger County Burial Nativity. 
 
 
 
Table 40. Foreign born county burial nativity by country. 
 
Table 41. Foreign born county burials by larger geographic region.  
 
Table 42. Top 10 causes of death nationwide. “”” indicates that cause of death             

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ranking matches the previous year.  Data source:            
https://www.cdc.gov/nchs/data/dvs/lead1900_98.pdf. 

 

Table 43. Hospital Death Register causes of death by CDC categories for county        
                 burials. 
Table 44. Comparative Samples. 
 
Table 45. Comparative sites age estimation midpoint counts. 
Table 46. Sample α1, β1, α3, and β3 parameters. 
 
Table 47. Statistical results for demographic comparisons between cemetery               
                 samples.  
Table 48. Individuals by Sex at VMC and MCMP. 

 
 
 

 
 
 

 
 
 

 

 

 

 

 

 

 

 

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ix 

 
Table 49. Individuals by Sex at VMC and Alameda Stone Sections 1-2. 
 
Table 50. Individuals by Sex at VMC and Alameda Stone sections 3-5. 
 
 
Table 51. Individuals by Sex at VMC and MCIG. 
Table 52. Individuals by Sex at VMC and Voegtly.   
 
Table 53. Presence and absence of periosteal reactions in adults at each cemetery.  
 
Table 54. Presence and absence of tuberculosis in adults at each cemetery.  
Table 55. Presence and absence of syphilis in adults at each cemetery. 
 
 
 
Table 56. Chi-squared results for pathological comparisons between samples. 

 
 
 
 

 
 

 
 

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x 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

LIST OF FIGURES 

 
 
 
 
Figure 1. 1876 Map of Santa Clara County Showing County Infirmary and  

John S. Connor Property - Source: Thompson & West 1876, David Rumsey  
Map Collection. 

 

46 

Figure 2. Infirmary, Santa Clara Co. 1876.  Lithograph.  Source: Thompson & West          47 

1876, David Rumsey Map Collection. 

 
Figure 3. 1929 County Surveyor Map Close-up - Showing Encroachment of Milk   

house, Horse barn and Cow Barn. Image Source Roher and Beck 2015. 

50 

Figure 4. 1929 Campus Map - Cemetery Boundary Highlighted in Red. Image Source       51 

 Roher and Beck 2015. 

Figure 5. The County Hospital - Front Entrance Source: Mars 1901:77. 
Figure 6.  County Hospital Approximately 1907-08.  Source California 1908. 
 
Figure 7. 1915 Sanborn Insurance Map - reformatted along match lines to show partial   54 

51 
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cemetery.  Image Source Roher and Beck 2015. 

Figure 8. Infirmary Fund record book – Image from February 1902 account. Image 

taken by author.  Archival source Santa Clara County Archives Clerk-Recorder 
Records Collection number 2009-009 through 2009-164 Series XII  
Miscellaneous 1840-1985 Sub-series 5: Classified Allowances Infirmary fund  
1896-1904.  

Figure 9. For County Needs Supplies and Labor Required During January Name of  
 Claimants San Jose Mercury News February 16 1902 Volume LXI Page 7.   

 
 
 
 

 
 
 
 

 
Figure 10. SCVMC Excavated Burials.   
 
Figure 11. Age categories by count.   
 
Figure 12. Coarse Age Categories. 
 
Figure 13. VMC Age at Death. 
 
 
Figure 14. Map of burials colored coded by age categories.   
Figure 15. Course Sex Counts. 
 
 
Figure 16. Map of burials color-coded by course sex. 
 
Figure 17. VMC Male v. Female Probability Density Function. 
Figure 18. VMC Male v. Female Mortality Hazard.   

 

 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 

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Figure 19. VMC Male v. Female Survivorship. 
Figure 20. Burial 685 overview, hematogenous osteomyelitis. 
 
Figure 21. Close up of Burial 685 right femur hematogenous osteomyelitis. 
 
Figure 22. Burial 218 mastoidectomy, left mastoid.   
Figure 23. Burial 732 tertiary syphilis with saber shins. 
 
Figure 24. Burial 736 enamel defects and calculus, congenital syphilis.  Photo   

 
 

 
 

 
 

courtesy of Karen Gardner. 

 
 
 
 
 
   

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Figure 25. Burial 736 mulberry molar, congenital syphilis.  Photo courtesy of Karen         98 

Gardner.  

 
 
 

 
 
 
 
 

 
 
 
 
 

 
 
 
 
 
 

 
 
 
 
 
 

 
Figure 26. Coffin Length Counts, length in inches. 
 
 
Figure 27. Coffin Depth Counts. 
 
 
Figure 28. Coffin Width Count. 
 
Figure 29. Coffin Shape Counts. 
 
 
Figure 30. Burial Map color coded by shape.  
Figure 31. Total Number of Buttons by Button Material Type. 
 
Figure 32. Count of Button Material Types in burials with a single type of button   
                  present. 
Figure 33. Count of button material type in burials with multiple types of buttons.  
Figure 34. Clothing Fastener Count.   
 
Figure 35. Jewelry Count by Type. 
 
 
Figure 36. Burial 199 two gold rings with makers marks and engraving.  Ring 1 hall  

 
 

 
 

 
 

 
 

 
 

marks HA (Hyde Aston Jewelers)/18 (18k gold standard)/Anchor  
(Birmingham England Assay Office)/Face (Queen Victoria)/Y (1873).  
Ring 2 engraved initials I (or A)/D/B.   

Figure 37.  Advertisement for W.L. & Co Rings (Chicago Dry Goods Reported 1900). 

 Rings from Burial 932 highlighted by red rectangle. 

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Figure 38. Religious Artifact Count.   
Figure 39. Burial 832 Hospital Internment button pattern. Image courtesy of URS.  
 
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Figure 40. Burials by age, Subadult burials (<25 years of age) are red. 
Figure 41. Map showing hospital button category individuals, individuals with hospital   120 

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button pattern in red. 

 

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Figure 42. Coffin Shape by Sex. 
 
Figure 43. Correspondence Analysis of Sex v. Coffin Shape. 
 
Figure 44. Coffin Shape by Age. 
 
Figure 45. Correspondence Analysis of Coffin Shape by Course Age Group. 
Figure 46. Coffin Length by Shape. 
 
 
Figure 47. Coffin Width by Shape. 
Figure 48. Coffin depth by shape. 
 
Figure 49. Button patterns by coffin shape. 
 
Figure 50. Burials with single button type Correspondence Analysis by Coffin Shape  

 
 
 
 
 
 
 
 

 
 
 
 

 
 
 
 

 
 
 
 

 
 
 
 

 
 
 

and pattern presence absence. 

Figure 51. Burials with single button type correspondence by sex and coffin shape  
 
Figure 52. Burials with single button type correspondence analysis by age and coffin  

shape. 

Figure 53. Burials with multiple button types correspondence analysis by sex and   

coffin shape. 

 

 
Figure 54. Button categories by sex.   
 
Figure 55. Button type correspondence analysis. 
Figure 56. Burials with Religious Artifacts by Sex and Coffin Shape. 
Figure 57. Hospital Death Records Volume 5 Page 44. Santa Clara County Archives  
Collection 2008-013 Medical Examiners-Coroner’s Office Records Box 8  
Volume 5. 

 
 
 

 
 
 

 
 

 
 

 

 
Figure 58. Age-at-death distribution of VMC and county burial hospital deaths. 
Figure 59. Hospital private burials and VMC age at death distribution. 
 
Figure 60. Probability density function of VMC and Hospital Deaths with county   
                 burials. 
Figure 61. Mortality hazard for VMC and Hospital deaths with county burials. 
Figure 62. Survivorship of VMC and Hospital Deaths with county burials.  
Figure 63. Number of individuals with an infectious cause of death from the hospital 
                 death register. 
Figure 64. Age at Death results for VMC and MCMP. 

 
 

 

 

 

 

 

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Figure 65. Probability density function for VMC and MCMP. 
 
 
 
Figure 66. Mortality Hazard of VMC and MCMP. 
 
 
Figure 67. Survivorship VMC and MCMP.   
 
 
Figure 68. Age at death structure of VMC and Alameda Stone sections 1-2.   
 
Figure 69. Probability Density Function VMC and Alameda Stone sections 1-2.  
 
 
Figure 70. Mortality Hazard VMC and Alameda Stone sections 1-2. 
 
 
Figure 71. Survivorship VMC and Alameda Stone sections 1-2.  
 
Figure 72. Age at death structure of VMC and Alameda Stone sections 3-5.   
 
Figure 73. Probability density function of VMC and Alameda Stone sections 3-5.   
 
Figure 74. Mortality hazard of VMC and Alameda Stone sections 3-5.  
 
Figure 75. Survivorship VMC and Alameda Stone sections 3-5.  
Figure 76. Age at death structure of VMC and MCIG.  
 
 
 
Figure 77. Probability density function VMC and MCIG.  
 
Figure 78. Mortality Hazard of VMC and MCIG.  
 
 
 
Figure 79. Survivorship VMC and MCIG. 
 
Figure 80. Age at death structure of VMC and Voegtly. 
 
 
 
Figure 81. Probability density function VMC and Voegtly.   
Figure 82. Mortality Hazard of VMC and Voegtly.   
 
 
Figure 83. Survivorship of VMC and Voegtly. 
 
 
 
Figure 84. Record of Baby Warren, stillborn.  Cause of death Eclampsia.  Date of   
death December 23rd, 1931. Originally recorded as a county burial, but  
ultimately given to Stanford University.  Image source: County hospital  
death register Volume 5: 72-73.  

 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 

 
 

 

Figure 85. San Jose Mercury News October 20th, 1901. 
 
Figure 86. Probable Length of Stay based on hospital patients statewide in 1914.    

 

 

 

State Board of Charities and Corrections 1916:60.  

 

State Board of Charities and Corrections 1916:60.  

Figure 87. Child buried without Health Board Permit.  Evening News April 7,  
                 1916 page 9. 

 

 

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Figure 88 Excerpt from article blaming San Jose’s high infant mortality rate on  
mothers not knowing how to give proper care to their babies.  Image  
source: The Evening News, March 31st 1917 68(78):6.  

 

Figure 89. Consumption Death Rate is Decreasing. Santa Clara County Favorably  
Reported by Health Officer Simpson Evening News (Published as The 
 Evening News) - April 16, 1902 Volume XLI Issue 99 Page 3. 

Figure 90. Breakdown of “racial and national groups” among county hospital patients  
                 statewide in 1914.  Source: State Board of Charities and Corrections 1916:56.  
Figure 91. California foreign born population by world-region of origin.  Data source:  
                 The Population of California, 1946. 
Figure 92. Native born v. foreign born. Data Source Population of California 1946. 
Figure 93. Burials by coffin shape. Rectangular coffins are red, all other shapes are  
                  yellow.  
Figure 94. Burials with non-specific infections in red.   
Figure 95. Burials with syphilis shown in red.  
 
Figure 96. Burials with tuberculosis shown in red.     

 
 
 

 
 
 

 
 
 

 
 
 

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xv 

Chapter 1: Introduction 

This research seeks to examine the complex processes that led to potential social and 

 
 

health inequalities by examining a large-scale historical cemetery from California; the Santa 

Clara Valley Medical Center (VMC) Historical Cemetery. Most large-scale historical cemeteries 

that have been analyzed (Collins 2009; Dougherty 2011; Grauer et al. 1998; Grauer and 

McNamara 1995; Higgins and Sirianni 1995; Lanphear 1988; Leavitt-Reynolds 2001; McGloin 

2012;Milligan 2010;Phillips 2001A, 2001B; Richards 1997; Wesolowsky and Eila 1991) are 

located in the East and Midwest, and are thus based on the demographics of the area.  The 

examination of a historical cemetery from the Western United States would address a regional 

research gap. This research will have implications for both bioarchaeology and mortuary 

archaeology, as it will address a portion of the mortuary and bioarchaeological record that has 

been addressed thus far only in a limited fashion.  

Bioarchaeological Approaches to “Health” and Paleopathology 

 

 

Bioarchaeologists are limited in the ways health and stress can be documented from 

skeletal remains.  This interpretation requires evaluating an individual’s resistance to stressors by 

examining the presence and severity of skeletal lesions such as linear enamel hypoplasias, 

porotic hyperostosis, cribra orbitalia, periosteal reactions, and other systemic infections such as 

osteomyelitis, syphilis, or tuberculosis (Goodman et al. 1984;Lawler 2016; Martin et al. 2013; 

Ortner 2003,2008; Pinhasi and Mays 2008).  These skeletal indicators of health can be used to 

evaluate stress incurred during an individual’s lifetime.  However, many stress events do not 

leave evidence skeletally, as only long-term or chronic health events impact bone growth and 

response. Pathognomonic diseases are unfortunately the exception as skeletal tissue most often 

responds in nonspecific and generalized ways, making the diagnosis of specific causes/pathogens 

 

1 

difficult (Bush 1991; Lawler 2016; Ortner 2009; Wright and Yoder 2003). However, these 

biological responses can still be used to examine the interactions between biology and culture in 

disease processes.    

 

Most current bioarchaeological studies examine health within the framework of Selyean 

stress, where stress is a bio-behavioral response to external environmental conditions (Klaus 

2014; Goodman et al. 1988; Schell 1997). In general, the biological responses to stress should be 

the same for everyone (with of course minor differences due to genetic background and host 

resistance factors), so it is the cultural interference that will result in the variation seen in skeletal 

populations. “This approach also views evidence of stress and disease as products of 

environmental inadequacies, whether socially, economically, politically, or ecologically 

generated” (Zuckerman et al. 2012:35).   

 

There are many factors that will impact host-pathogen-environment interactions 

(Zuckerman et al. 2012), and an integrated biocultural approach using historical documents can 

answer some of these factors.   It is also important to consider the impact of age, sex, and the 

overall health of the individual being stressed and their specific host resistance factors (Martin et 

al. 2013:11, Reitsema and McIlvaine 2014).  Although Selyean stress models acknowledge that it 

is difficult to determine the sole mechanism by which “sociocultural events translate to disease” 

(Goodman et al. 1988:176), as a framework for understanding health it is heuristically useful. 

 

In historical cemetery populations, it is possible to reconstruct some of the cultural 

buffering systems and culturally induced stressors the individuals would have encountered 

during life.  This part of the stress model, however, is too often overlooked by bioarchaeologists.  

Even if the all other components of the stress model are employed, without a nuanced 

incorporation of the historic scenarios that impacted the biological responses of the people being  

 

2 

studied, we are destined to create interpretations that are “wanting in relevance and significance” 

(Martin 1998:177).   Historical cemeteries provide an opportunity to interweave the cultural and 

biological variables that result in skeletal indicators of stress.  

The VMC historical cemetery (~1875-1935) was used by Santa Clara County to bury 

Research Goals 

 

indigent patients from the county hospital, unknown individuals from the coroner’s office, and 

members of the community that could not afford private burial elsewhere (Rehor and 2015). 

Between 2012 and 2014, a portion of the VMC cemetery was excavated resulting in the 

exhumation of 998 burials, consisting of 1,004 individuals (Rehor and Beck 2015).  This skeletal 

collection provides a unique opportunity to examine rural, western, frontier health amongst 

recent immigrants, migrants, and lower socioeconomic individuals at a crucial time in U.S. 

history.   

 

This study seeks to examine the health of the most at-risk and least documented segment 

of the historical Santa Clara Valley population; indigents.   The primary objective of this 

research is to understand the health patterns present within the VMC burials while incorporating 

both the mortuary archaeological and historical context of the burial ground. Furthermore, this 

research will study the health of the excavated individuals while specifically examining the 

biological impact of the county’s efforts towards public health initiatives, public policy toward 

the poor, and prevailing medical practices of the time.  Paleopathological observations of 

specific and nonspecific indicators of stress will be used to establish prevalence rates within the 

sample and will be compared to available historical records. This research also seeks to focus on 

the comparison of the VMC sample with similar samples from indigent and non-indigent 

 

3 

historical cemeteries.  These comparisons will serve to establish the relative health of the VMC 

sample. 

 

This research will have implications for both bioarchaeology and mortuary archaeology, 

Significance of Research   

 

as it will address a portion of the mortuary and bioarchaeological record that has been addressed 

only in a limited fashion. Investigating VMC also presents a unique opportunity to examine 

historical immigrant groups that are not Western European in nature.  Because VMC is located in 

San Jose, California, the ethnic makeup of the area in the late 19th and early 20th century is 

drastically different from both the East Coast and Midwest. California underwent many 

significant demographic, economic, and social changes during the mid 19th and early 20th 

centuries.  The discovery of gold at Sutter’s Mill in 1848, and California’s admittance to 

statehood in 1850, created a precedent for a dramatic influx of domestic and international 

immigrants (Hall 1871; Foote 1888). Asian and Pacific Islander immigrants accounted for 6-9% 

of the total population of California between 1860 and 1900, but this group accounted for only 

0.11-0.21% of the total U.S. population (Campbell and Jung 2002). By 1870 the percentage of 

foreign-born residents had risen from an initial 24% in 1850, to 37% (Wright 1940:332), and 

Chinese migrants were the second largest ethnic population in Santa Clara County (Tsu 2013). 

By 1870 the top five countries of origin for foreign-born residents in California were Great 

Britain (37%), China (23%), Germany (14%), Mexico (4.5%), and France (4%) (Wright 

1940:340). In striking contrast to the eastern U.S., California displayed a heavily Hispanic 

population (Wright 1940, Pitti 2003), and in 1860 Santa Clara County likely boasted the largest 

Hispanic immigrant population in the United States (Pitti 2003:41).  By the time VMC opened in 

 

4 

1871 (Foote 1888) the demography in California, and specifically Santa Clara County, was 

unique both in terms of the number of foreign-born residents, and their countries of origin.    

 

By assessing the health of the individuals at VMC, while incorporating and interpreting 

both their mortuary and social contexts, this research will give a broader and more holistic 

understanding of rural, western, migrant, immigrant, and indigent health during the late 19th and 

early 20th century. Additionally, this research will demonstrate the implications of structural 

violence, social inequality, and institutional caregiving on both individual and population levels 

of health, thus also examining the potential timing of the second epidemiologic transition within 

this population. Historical records pertaining to the cemetery use are sparse. Therefore, the 

biological analysis of the skeletal remains offer an opportunity to fill in gaps in our knowledge 

regarding this period of Santa Clara County history.  

 

This dissertation addresses a number of important research questions: specifically, what 

Outline of the Dissertation 

 

is the impact of structural violence, public health, and institutionalization on the low 

socioeconomic individuals of Santa Clara County in the late 19th and early 20th century.  Chapter 

two outlines the theoretical foundation of this dissertation. 

 

Chapter Three discusses the historic era context of the California, with a specific focus on 

the Santa Clara Valley and immigration trends.  Following the discussion of the larger historic 

context, a history of the development of the Santa Clara county hospital and the counties use and 

formation of potter’s fields is outlined.   

 

Chapter Four outlines the research questions and goals for this project.  Chapter Five 

presents the materials including VMC, details regarding the excavations, and the comparative 

and historical records used.  Chapter Six presents the results of the VMC skeletal analysis.  

 

5 

Chapter Seven presents the comparative sample results.  Chapter Eight synthesizes the results of 

this study and presents interpretations of the skeletal pathology and mortuary analysis within 

larger theoretical frameworks       

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6 

Chapter 2: Theoretical Background 

 

Introduction 

Historical mortuary sites are uniquely positioned to explore complex biological and 

 

social situations because of the cross-cultural, empirical, and diachronic perspectives that the 

skeletons and historic context can provide. The integration of empirical studies using skeletal 

remains with social theory to interpret the skeletal data provides an interpretive framework to 

better understand how social and political relations create specific health patterns (Klaus 2014a, 

2014b; Nguyen and Peschard 2003).  However, to date, few systematic studies of health have 

been conducted on large-scale historical cemeteries in the United States. Some bioarchaeological 

researchers have worked to broadly contextualize historic health patterns (Collins 2009; 

Dougherty 2011; Grauer and McNamara 1995; Grauer et al. 1998; Heilen 2012; Higgins and 

Sirianni 1995; Higgins et al. 2002; Lanphear 1988, 1990; Leavitt-Reynolds 2011; McGloin 2012; 

Milligan 2010; Phillips 2001A, 2001B; Richards 1997; Wesolowsky and Eila 1991), but the 

salvage nature of many of the archaeological projects, along with time and budgetary constraints, 

have limited the scope of past bioarchaeological research.   

 

The studies of health, disease, and stress have been key components of bioarchaeological 

research since the beginning of the field (Cohen and Armelagos 1984; Buikstra 1977; Temple 

and Goodman 2014).  Although bioarchaeology has attempted to move beyond the descriptive 

approach and embrace larger theoretical frameworks, the reality of integrating and examining the 

intricate biosocial processes that shape health and illness has remained an issue. Just as 

archaeological data is viewed as messy and thus often avoided by the bioarchaeologist 

(Goldstein 2006), so too is social data and theory.   

 

7 

 

Health and disease cannot be disassociated from the larger socio-political context and 

must be considered within the global (and regional) political-economic structure that shapes the 

local context of people’s lives and becomes embodied biologically (Temple and Goodman 

2014). It is not debated that skeletal morbidity correlates with lower social and economic status 

(Klaus et al. 2017; Danforth 1999; Larsen 1997), but it is often difficult to consider the 

interconnections of the full array of variables.  The ability to consider the interconnections 

among these parts, including the ways they promote and reinforce each other, creates a “complex 

and burdensome web of intertwined health and social problems” (Singer 2009:xiv).   

 

Health disparities examined in modern times are increasingly understood to be caused by 

social and economic inequality; “i.e., social bias and institutional racism, limited education, 

poverty, and related environmental conditions that either directly produce ill health or promote 

unhealthy behaviors that lead to poor health” (Mikkelsen et al. 2002:3).  Historical cemeteries 

are uniquely positioned to allow bioarchaeologists to examine the biological impact of health 

disparities. Archival sources have the potential to provide abundant contextual information 

regarding both the individuals buried in the cemetery, and the social systems and policies 

operating during their lives.  The physical remains of the people themselves can provide direct 

evidence of the biological impact of long-term and episodic health stressors. 

 

To contextualize the methodological and theoretical frameworks employed in this 

dissertation, an overview of mortuary archaeology, bioarchaeology, paleopathology, and public 

health theory is discussed.  Additional focus on class and race-based issues in public health, 

structural violence, and the epidemiological transition are also discussed as it relates to this 

research. 

 

 

8 

 

Mortuary Archaeology Theory 

The study of mortuary rites and their archaeological correlates has been an integral part 

of archaeology since the beginning of the discipline. In the early twentieth century 

anthropological approaches to mortuary behavior focused on the assumption that funerary rituals 

hold social meaning (Rakita and Buikstra 2005). The concept of the “rite of passage” was 

developed by Van Gennep (1908) and is frequently used by anthropologists as a means to 

interpret mortuary behavior.  Van Gennep (1908) proposed a three-part transitional period that 

involved rituals divided into stages of separation, transition, and reincorporation. It is through 

these specific processes that death is transformed from a threat into a normal part of life. By the 

mid twentieth century mortuary archaeological work began to critique Kroeber’s idea that 

funeral rituals were unrelated to other social customs (Rakita and Buikstra 2005).  

Hertz’s (1960) publication marked a shift in mortuary studies. This work focused on 

expanding the meaning and context of mortuary rituals with a particular focus on secondary 

burials.  Binford (1971) argued that mortuary studies should be used as a method to interpret 

social organization and complexity.  He also suggests that as the number of social roles an 

individual held during life increases, so too does the symbolic representations of those roles in 

mortuary treatment.  O’Shea (1981) expands on past work by comparing ethnographic status 

against the archaeological record to highlight both vertical and horizontal status differentiation. 

Morris (1992) addresses the need for mortuary archaeology to be integrated and well 

contextualized, specifically when it comes to incorporating other lines of evidence such as text, 

art, ethnography, and other types of archaeology/anthropology. He argues that in rituals people 

use symbols to make explicit the cultures’ social structure. Parker-Pearson (1999) emphasizes 

that in mortuary archaeology we analyze the life of the individual, not their death.  He cautions 

 

9 

that we must be wary of how we separate the material culture on the body from the material 

culture of the body, from the material culture off the body.    

Cemeteries and the Historical Era 
 

Historic mortuary sites are uniquely positioned to answer questions surrounding the 

effects of large-scale political, social, ecological, and economic processes and their effects on the 

biology of members of those communities.  The textual evidence available at historic period sites 

allows for anthropologists to provided more nuanced interpretations of historical narratives.  

Perry (2007) points out that both textual evidence and archaeological evidence must be examined 

for inherent biases.  Perry (2007) demonstrates this with a case study from the Classical Near 

East where the bioarchaeological data contrasts with some forms of historic textual data.   

Mortuary behavior in the United States and Great Britain underwent significant changes 

during the nineteenth and twentieth centuries.  The rise of urbanism, industrial capitalism, and 

increased consumerism profoundly changes attitudes towards death, culminating in a trend of 

mortuary behavior commonly referred to as the Beautification of Death movement (Lee Decker 

2009).  Funerals and graveyards are important parts of rituals and are employed as 

communicative symbolic actions for the construction of ethnic and cultural identity (Reimers 

1999).  Cannon (1989) demonstrated that during the 19th and 20th centuries western mortuary 

displays went through cycles of elaboration and simplification due to funerals and mortuary 

monuments being used as opportunities for social advancement and social display.  However, as 

noted by Aries (1974) there has been an increasing disconnection in the West of death, and the 

feelings and processes associated with it, from everyday thought. 

As mortuary traditions shifted towards large ostentatious displays associated with the 

Beautification of Death movement, the funeral rituals of the poor were also impacted.  This shift 

 

10 

caused a major change in the final determination of one’s social status from the time of death to 

the time of burial.  Thus, being relegated to a simple, anonymous paupers burial became a source 

of great shame, highlighting a perceived failure on the part of the deceased (Laqueur 1983).  

Additionally, the anonymity of a pauper’s burial impacted the use of these burial spaces as 

mourning and commemoration locations.  Denied the ability to privatize burial space, the 

working class adopted a mutable language of loss, allowing for the veneration of the dead 

without definitive burial spaces (Strange 2003).  

Identity 
 

Mortuary practices represent the complex interplay of ritual, material culture, and social 

memory as seen through the material remains created by ceremonies.  Archaeologists attempt to 

reconstruct social structure through the interpretation of grave goods, skeletal remains, and 

funerary structures.  The translation of material culture and the material remains of mortuary 

rites into social identity is one of the most fundamental aspects of mortuary archaeology.  

However, in order to make these inferences, archaeologists must first consider the social, 

religious, political, and environmental dimensions of mortuary behavior in order to examine and 

reconstruct the social relationships between them (Carr 1995).  We infer that material cultural 

patterning relates to social patterning (Shanks and Tilley 1987).  

Many of these frameworks hinge on the belief that the embodied value of commodities is 

the connection between cultural material and existing social frameworks (Appadurai 1986). 

According to Budja (2010) the living use death rituals to negotiate the agency of both the living 

and the dead’s relatedness; thus, these social structures should be reflected in mortuary contexts. 

It follows that mortuary ceremonies including grave goods deposited with the remains, the 

physical location of the burial, and relationship of the burial to the larger landscape all signal 

 

11 

both social (vertical) and kin based (horizontal) levels of social configuration (O’Shea 1981). 

Tainter (1978) argues that social personae are determined by the larger group’s social 

organization, which in turn is reflected in the mortuary ritual. He argues that in order to correlate 

mortuary data with identity the use of spatially distinctive groups of evidence to correlate burial 

type with social persona is necessary.   

Peebles and Kus (1977) developed a model to describe some archaeological correlates of 

social hierarchy, with burial distinctions being one category of potential. They concluded that 

mortuary practices are the most effective way to demonstrate ascribed ranking of persons based 

on the symbols, energy expenditure, age, and sex of the individual. Cannon (2005) was able to 

demonstrate the role of age and gender in historic burial trends and patterns of mortuary 

treatment.  However, Conkey and Spector (1984) argue that archaeology tends to reinforce 

modern culture-specific beliefs of gender when interpreting past societies.  They suggest the 

reevaluation of many prior gender-based identity assumptions. 

Interpreting Identity in Historic Cemeteries  
 

Given the diverse demographic makeup of the historic United States, one of the central 

questions of any examination of a historic U.S. cemetery revolves around the concept of the 

identity of the individuals interred there.  Bioarchaeologists and mortuary archaeologists are 

being asked to move beyond the basic biological profile, and to assess cultural affinity, identity, 

and relatedness.  Unfortunately, when it comes to burial practices there is no simple 

correspondence between one’s biological ancestry and one’s culture.  The assessment of 

individual identity requires a close examination of archaeological, osteological, and historical 

evidence.  Belonging to a specific religious group could supersede the burial traditions of 

belonging to a specific ethnicity, just as being socioeconomically disadvantaged can impact a 

 

12 

range of burial traditions. The intersection of religion, biology, culture, and ethnicity necessitates 

a nuanced approach where context means everything (Goldstein et al. 2012).  Never the less, 

some cultural affinity trends have been established by examining the historic mortuary practices 

of different groups. 

The transnational identity of Chinese migrants in the United States created a unique 

mortuary tradition.  In Mainland China the prevailing death ritual was a combination of multiple 

religious denominations including Confucianism, Taoism, and Buddhism.  Chinese belief holds 

that the dead can directly influence the lives of the living, thus many customs have remained 

relatively unchanged for centuries for fear of retribution.  Graveside services include ritual 

wailing, fasting, burning of symbolic sacrifices, and offerings of food.  Burial location and 

orientation is determined through geomancy in accordance with feng shui principles. Shrines to 

specific ancestors are maintained both in private homes, and ancestral worship halls.  After a 

predetermined amount of time, individuals are disinterred, the bones are washed and the remains 

are re-deposited in an urn for a secondary burial (Rouse 2005).  For the Chinese sojourners that 

died in America, an additional layer was added to the ritual; the transportation of their bones 

back to China for final burial in their home provenance.  Chinese individuals that permanently 

resettled in the United States typically did not undergo the secondary burial, but maintained the 

other graveside and mourning components of the traditional mortuary ritual (Rouse 2005; Smits 

20008).  

African American burial characteristics were influenced first by slavery, and later by 

racial segregation.  Within mortuary contexts enslaved Africans were given more cultural leeway 

than in other facets of their lives.  Cultural transmission of traditional burial practices was also 

hindered by the age and gender distribution of individuals taken by the slave trade.  There is also 

 

13 

a lack of comparative ethnohistorical and archaeological data from Africa, which further limits 

the creation of burial typologies. However grave goods placed with the body, such as copper 

jewelry and cowrie shells, may offer the most obvious and abundant evidence (outside of the 

physical remains themselves) for identifying antebellum African burials. By the late 19th century 

African American burials, like many others, were homogenized by religious and cultural trends 

towards mass-produced coffins and coffin hardware (Jamieson 1995).  In the late 19th and early 

20th centuries American cemeteries reflected larger race, class, age, gender and religious 

distinctions.  Thus, African Americans were often segregated into separate cemeteries, or in 

biracial burial grounds they were relegated to the outer periphery along with paupers and 

criminals (Kruger-Kahloula 1994).   

Hispanic and Mexican American burial characteristics are heavily influenced by the wide 

scale adoption of Catholicism. The Catholic funerary model emphasized the need to put the soul 

to rest is consecrated ground.  Funeral arrangements are made quickly, cremation is taboo, and 

the extended family is often included in burial decisions (Kalish and Reynolds 1981; Younoszai 

1990).  The corpse typically undergoes minimal treatment, and children are often dressed in 

white (Marino 1997).  

The Beautification of Death movement significantly impacted Euro American burial 

characteristics in the historic United States.  By the end of the eighteenth-century dramatic 

changes in both death rites and burial grounds had occurred.  Rural areas continued more 

traditional mortuary rites with the body being washed and prepared by family or close friends, 

covered in a burial shroud, and then transported to the cemetery (Laderman 1996).   By the 

second half of the 19th century, death was further segregated from the living.  Industrialization 

and urbanization lead to the rise of undertakers, and the increased popularity of embalming 

 

14 

removed the dying process from private homes and transferred the body preparation and disposal 

processes to professionals (Steiner 2003). The emergence of a low socioeconomic working class 

facilitated changes to a subsection of American mortuary rites.  In opposition with the 

Beautification of Death movement, the poor were left with anonymous burials in potter’s fields.  

This necessitated a more flexible mourning tradition within these groups, as the traditionally 

marked grave location was denied to them.  These potter’s field graves were also regulated by 

the government entity overseeing the process, limiting potential individual expression in burial 

characteristics (Rosenow 2015).    

Ritual and Identity 
 

To understand mortuary rituals and their accompanying behaviors, it is necessary to 

examine the symbolic roles these rites encompass.  Death is a transition, both of the biological 

and social components of an individual’s place in a community.  However, it is important to keep 

in mind that death is inherently related to life (Metcalf and Huntington 1991).  Bloch and Perry 

(1982) discuss death as a form of regeneration, and thus specifically focus on symbols of fertility 

and rebirth in funerary rituals. The key to the archaeological inference of ritual and performance 

from mortuary remains is the connection between social behaviors and the mortuary remains. 

The physical traces of rituals are used to interpret issues of power relations, identity, social 

transformation, and cultural constructions of ecology, community, and personhood (Swensen 

2015).  Swensen (2015) cautions that in understanding ritual, archaeologists need to recognize 

that rituals are not immediate proxies of other sociopolitical realities but are often vehicles of 

social change.  Rituals related to death are of particular interest to archaeologists, as the 

treatment of human remains, and the accompanying processes often leave visible archaeological 

traces. 

 

15 

The connection between material culture and ritual hinges on the meaning conveyed by 

funerary objects and the placement of the dead.  These are believed to reflect the social structure 

of the living population in that the social persona of the deceased is expressed in the mortuary 

ritual.  According to Kuijt (1996) ritual behavior can also be employed as a framework for 

modifying social relationships, either by reinforcing social cohesion and community identity, or 

as a means to symbolize social change. Kopytoff (1986) argues that commodities are a universal 

cultural phenomenon, and that the exchange of commodities is a universal feature of human 

social life.  Because commodities have value, and can be exchanged, they are of particular 

interest to archaeologists.  Weiner (1983) explores the concept of inalienable wealth in which 

value is created in objects not because of their material value, but because of their cultural value.  

Thus commodities, or material culture, can be imbued with levels of both ritual and social 

significance.  Weiner (1983) examines the implications of such types of wealth in the Maori, and 

arguing that in ranked societies social capital is often defined not only by relationship networks 

among the living, but the demonstrated connection to ancestors, thus specific types of objects 

display levels of cultural wealth.  Goldstein (2000) demonstrates the connection between 

material cultural and inalienable wealth by examining secondary burial practices at Cahokia’s 

Mound 72.  She argues that the secondary burials could represent a form of inalienable wealth, as 

the individuals within the mound became a demonstration of group, rather than individual 

identity.  

Placement and Spatial Analysis 
 

Spatial analysis of burial locations is used to examine many dimensions of funerary ritual 

and social complexity.  Saxe (1970) was one of the first to acknowledge and apply a spatial 

analysis to mortuary studies.  Saxe sought to create a model of sociocultural systems based on 

 

16 

mortuary practices through the formulation of eight specific hypotheses.  With regards to spatial 

analysis, Saxe’s hypothesis 8 argued that formal disposal areas of the dead are maintained by 

corporate groups with ancestral claims to that specific area (Saxe 1970). Goldstein (1981) 

challenges this hypothesis and noted that although bounded space is typically associated with 

corporate groups, not all corporate groups create and utilize bounded mortuary spaces. Brown 

(1995) supports the hypothesis but argues that there are some problems stemming from a 

misconception that hypothesis 8 defined a relationship between boundary rights and settlements.  

Brown argues that the patterns visible archaeologically are not the only part of the funerary ritual 

occurring.  Brown suggests that the focus of funerary ritual related research should shift towards 

attempting to understanding the funerary process and how it benefits the living population.  

Goldstein (1995) also proposes a multidimensional approach that considers both inter and 

intra site spatial dimensions, including their placement on the larger landscape.  The benefits of 

this multiscalar approach is well-illustrated by Ashmore and Geller (2005), who examine the 

mortuary landscape of the formative Maya.  They argue that placement within the larger 

landscape is just as important as individual burial placement within a defined mortuary burial 

boundary.  Charles and Buikstra (2002) examine how the dead and the living interact by 

examining how the dead are placed, seen, and referenced by the living.  They demonstrate this 

by examining changes in cemetery locations throughout the woodland period in the Illinois 

Valley.  They argue that as group identity became more important for the living population, 

centrally constructed, easily sighted burial mounds were used to promote active engagement with 

the ancestors as a means to negotiate social and political spheres.   

 

17 

Bioarchaeology Theory 

 

The field of bioarchaeology has its origins in the combination of human osteology and 

archaeological techniques to investigate the human condition and the role of the environment on 

human biology (Larsen 2006).  Although the term bioarchaeology had been used previously, 

Jane Buikstra popularized its current usage in 1977 (Buikstra 1977).  The development of 

bioarchaeology is often framed alongside the rise of the “New Archaeology” of the 1960s and 

the processual archaeology of the 1970s (Armelagos 2003; Buikstra 1977).  Prior to this time, 

archaeological and osteological studies were strongly descriptive, rather than interpretive 

(Buikstra 2006).  Buikstra advocated the need for an interdisciplinary research strategy that 

incorporated mortuary archaeology and osteology in order to investigate broad research 

problems including: burial program and social organization, daily activities and division of labor, 

estimates of population size and density, population movement and genetic relationship, and 

diet/disease (Buikstra 1977:71).  The interdisciplinary nature of bioarchaeology allows for cross-

cultural perspectives and larger evolutionary frameworks to be applied to studies examining the 

biological impact of cultural practices (Armelagos 2003).  

The study of human remains and their integration into broader investigations of culture 

began, in the United States, prior to 1900 with Thomas Jefferson’s burial mound excavations 

(Buikstra 2006).  Jefferson combined osteological observations with archaeological contexts to 

answer larger questions about pre-contact North America.  His studies influenced additional 

nineteenth century works of scholars including Samuel George Morton, Joseph Jones, 

Washington Matthews, Frank Hamilton Cushing, and George A. Otis (Buikstra 2006).  Aleš 

Hrdlička and Earnest A. Hooton dominated early 20th-century physical anthropology, and their 

drastically different orientations to archaeological contexts and anthropological problem solving 

 

18 

greatly influenced a generation of physical anthropologists (Buikstra 2006). Bioarchaeology’s 

problem-oriented approach and hard science based analysis has proven especially suited for 

examining past human behavior and lifestyle including: quality of life, behavior and lifestyle, 

population history and biological relatedness (Larsen 2006). The procedures outlined in 

Standards sought to standardize recording methodology in human skeletal analysis (Buikstra and 

Ubelaker 1994). However, there are several theoretical and methodological issues that 

complicate the use of human skeletal remains for the reconstruction of past populations. 

The seminal Osteological Paradox publication by Wood et al. (1992) presented three 

large issues that bioarchaeology and paleopathology needed to overcome; demographic non-

stationary, selective mortality, and hidden heterogeneity. Demographic non-stationary refers to 

the issue of age-at-death distribution sensitivity to changes in fertility, but not mortality.  This 

means that the often-used life expectancy or mean age at death are actually measures of fertility 

and not mortality.  The second issue of selective mortality grapples with the fact that 

bioarchaeologists never have a sample of all the individuals at risk of death or at a specific age.  

The skeletal samples we use are only individuals that died and happen to end up in any given 

burial context.  Hidden heterogeneity is the unknown variation present in underlying frailty or 

susceptibility to disease and death.  Frailty can be impacted by biological factors such as genetic 

predisposition, or cultural factors like socioeconomic differentials. These major issues make it 

impossible for bioarchaeologists to obtain direct estimates of demographic and epidemiological 

rates from archeological samples (Wood et al. 1992).  Wood et al. (1992) suggest four specific 

areas of research that may help solve the Osteological Paradox: (1) research on the underlying 

causes of heterogeneity in individual frailty; (2) research on the relationship between frailty and 

the risk of death; (3) research on pathological lesion formation processes and the interaction 

 

19 

between frailty and the risk of death at different stages in the disease process; and (4) the role of 

culture in heterogeneity and culture’s interaction with selective mortality. 

Dewitte and Stojanowski (2015) summarize and analyze research on Wood et al.’s 

Osteological Paradox in the approximately 20 years since publication.  They argue that although 

Wood et al. is a seminal document in the history of the field there are many misperceptions, and 

few authors have actually attempted to directly tackle answering the issues of the osteological 

paradox. Dewitte and Stojanowski note that particularly in the last five years (preceding the 2015 

publication) paleopathology and bioarchaeology have developed new techniques (such a 

genomic, phonemics, epigenetics, parasitology, and stable isotope analysis) and perspectives that 

have allowed more researchers to tackle the osteological paradox in direct and meaningful ways.  

They call for a multidisciplinary bioarchaeology with an emphasis on cultural context with 

research that examines heterogeneity of frailty as an important component of the research design 

itself.   

Paleopathology Theory 

 

The definition of paleopathology has changed over time, today paleopathology is the 

study of the evolution of human diseases, human adaptation to the environment, and the 

interactions between human culture and infectious/noninfectious diseases (Grauer 2012; 

Zuckerman et al. 2012).  Before the 20th century the discipline was focused on descriptive and 

typological approaches examining the origins and antiquity of specific diseases with little 

incorporation of theory.  During the early 20th century (1900-1960), following trends in wider 

anthropology, paleopathology began to consider diseases in broader biological and social 

contexts.  This was pushed forward greatly by Hooton’s 1930 Pecos Pueblo study, and the 

development of Washburn’s “new physical anthropology” in the 1950s (Zuckerman et al. 2012).   

 

20 

In the 1960s the focus shifted to ecological, epidemiological, and evolutionary 

considerations.  The development of processual archaeology, and the emergence of ecological 

and biocultural approaches in conjunction with the recognition of skeletal indicators of stress 

allowed for the investigation of adaptation in past populations (Grauer 2010; Zuckerman et al. 

2012).   The 1970s and 1980s were greatly impacted by improved dating techniques, larger 

sample sizes, and the recognition of the issues with specific diagnoses.  This allowed for research 

projects to examine large scale epidemiological and culturally/ecologically relevant 

interpretations of diachronic trends in health (Zuckerman et al. 2012).  Since the 1980s 

methodological advances in biomolecular and biochemical techniques such as; stable isotopes, 

parasitology, and ancient DNA have largely affected paleopathology.   

Population level analysis has allowed the theoretical investigation of paleopathology with 

larger issues such as social roles, social status, living environments, activity patterns, disease and 

diet, disease lesion relationships, and injuries/treatment (Boldsen and Milner 2012; Buzon 2012). 

Though it is stressed that solid archaeological techniques and context are necessary to integrate 

paleopathology with larger evolutionarily based lines of inquiry. Researchers caution that it is 

necessary to consider the specific place, time, sex, age, socioeconomic position, and residential 

location when putting disease into a population context.  Although there has been progress in the 

methodological approach to paleopathology, there are still many diagnostic and theoretical issues 

that must be overcome.  These include the adequacy of archaeological samples, sample size, 

accuracy of diagnosis, research design issues, and contextualizing the meaning and importance 

of research questions (Ortner 2003a; Ortner 2009). Paleopathological research should strive to 

contribute to understanding the significance of disease in human societies or the evolutionary 

processes that shape present day and the future (Ortner 2009).    

 

21 

Stress/Non-specific Infections 
 

Bioarchaeologists are limited in the ways health and stress can be documented from 

skeletal remains.  This interpretation requires evaluating an individual’s response to stressors by 

examining the presence and severity of skeletal lesions such as enamel hypoplasia’s, porotic 

hyperostosis, cribra orbitalia, periosteal reactions, and other systemic infections (Lewis and 

Roberts 1997).  However, skeletal tissue most often responds in nonspecific and generalized 

ways to stress and disease, making the diagnosis of specific causes/pathogens difficult.  Most 

current bioarchaeological studies examine health within the framework of Selyean stress, where 

stress is a biobehavorial response to external environmental conditions (Goodman et al. 1988, 

Klaus 2014).  Although Selyean stress models acknowledge that it is difficult to determine the 

sole mechanism by which “sociocultural events translate to disease” (Goodman et al. 1988:176), 

as a framework for understanding health it is heuristically useful. Schell (1997) made the 

important point that although many researchers treat culture as a buffer to stress, it can also be 

the causal agent.  

There have been some critiques of the application of “stress” and “health” in 

bioarchaeological research.  Temple and Goodman (2014) argue that bioarchaeologists are not 

actually measuring health outcomes when they talk about stress response.  Klaus (2014) is a bit 

more optimistic, but stresses that bioarchaeology needs to be more interdisciplinary in order to 

better understand biological stress and disease outcomes.  These issues are highlighted in works 

by Weston (2012) and Walker et al. (2009).  Weston (2012) argues that bioarchaeologists don’t 

really understand the physiological response bone takes to stress events, and that the 

interpretation of periosteal reactions as generalized nonspecific reactions ignores biology.  In a 

similar vein Walker et al. (2009) suggests that long standing assumptions regarding the 

 

22 

relationship between cribra orbitalia and porotic hyperostosis with iron-based anemia are wrong 

based on the physiological way hematopoietic marrow expansion occurs.  

Measuring Indicators of Health: Infections and Degenerative Changes 
 

Although the skeleton generally responds to stress and infection in nonspecific ways, 

there are several instances in which a specific disease can be pinpointed.  This includes leprosy, 

treponemal infection, tuberculosis, and most metabolic disorders.  Due to their pathognomonic 

natures these diseases have received ample attention in paleopathological research.   

Leprosy, also known as Hansen’s disease, is caused by the bacteria Mycobacteria leprae 

(Lynnerup and Boldsen 2012). Although this disease has been documented since 2,500 BC and 

studied intensively, the exact path of contagion is still unknown.  Disease manifestation is 

extremely variable and can range from mild to very severe, therefore only a small portion of the 

total infected population will progress to skeletal involvement. The paleopathological diagnosis 

is further aided by a strong historical documentation of the disease.  Because leprosy is severely 

debilitating and causes overt physical symptoms, sufferers were often segregated into leper 

colonies and buried in segregated cemeteries (Lynnerup and Boldsen 2012).  Skeletally leprosy 

is characterized by resorption of the anterior nasal spine, alveolar resorption (with loss of the 

maxillary incisors), periostitis of the maxillary palate, and contraction of the hands and feet.  The 

accumulation of bacteria in nerve sheaths of the peripheral ulnar and fibular nerves leads to a 

loss of motor function and causes high rates of secondary infections in the damaged tissue that 

results from the loss of sensation (Lynnerup and Boldsen 2012).  

Tuberculosis (TB) is an infectious disease caused most commonly by the bacteria 

Mycobacterium tuberculosis (in humans) and rarely by Mycobacterium bovis (in humans and 

cows). Prior to the genomic sequencing of TB in 2002, it was believed that M. tuberculosis 

 

23 

developed from M. bovis as a byproduct of animal domestication.  However, the DNA analysis 

concluded that M. tuberculosis predates the domestication of animals by thousands of years.  TB 

causes skeletal changes in the post-primary stage of infection, 3-5 years following initial 

infection.  Skeletally TB is recognized primarily through destructive lesions of the lumbar and 

thoracic vertebral bodies (Pott’s disease), periosteal pitting and new bone formation on the 

visceral rib surface, calcified pleura, hypertrophic pulmonary osteoarthropathy, and septic 

arthritis (although some of these responses are nonspecific and can be caused by other 

pathological conditions).  TB has been documented as far back as the 3rd millennium B.C. in 

specific parts of the world but is absent from parts of North and most of South America, Africa, 

and most of eastern Europe and Asia.  However, this absence may be due to preservation, 

culture, and lack of bioarchaeological work in many of those locations, rather than a historical 

lack of the disease itself. TB is still a major concern globally today, with millions of cases and 

the emergence of antibiotic resistant strains (Roberts 2012).   

There are four distinct types of treponemal diseases: pinta, yaws, bejel (endemic syphilis) 

and syphilis (venereal syphilis). Yaws, bejel, and venereal syphilis all have the potential to 

manifest skeletally, while pinta only impacts the skin. There is considerable overlap in lesion 

type, distribution, and frequency between treponemal variants.  Treponemal disease manifests in 

three stages: primary, secondary, and tertiary. Primary infection rarely involves the skeleton, 

producing only mild, non-diagnostic lesions.  Secondary stage infection also produces periosteal 

reactions, though they are very mild and often completely remodel. Tissue is damaged by 

localized and systemic inflammation however distinctive skeletal lesions appear only in the 

tertiary stage. Tertiary infection involves periosteal reactions, osteitis, osteomyelitis, and 

gummata necrotizing lesions. Tertiary lesions are characteristically bilateral and systemic.  

 

24 

Excessive periosteal deposition results in pseudo-bowing of the tibia, commonly referred to as 

saber shins.  Cranially, tertiary infection can cause palatal perforation, rhinomaxillary 

destruction, periosteal reactions on the maxilla, and caries sicca on the vault (Harper et al 2011).  

There are three competing theories regarding the evolution and spread of treponemal 

diseases: Columbian, Pre-Columbian, and Unitarian.  The Columbian hypothesis suggests that 

venereal syphilis originated in the New World and was introduced into the Old-World following 

Columbus’s return from the Americas in the 15th century. The Pre-Columbian hypothesis argues 

that treponemal disease existed in the Old World prior to 1492.  The Unitarian hypothesis argues 

that treponematoses are environmentally determined variants of a single flexible disease and are 

thus a reflection of cultural changes.  The Unitarian hypothesis has been discredited by recent 

genetic evidence that shows three distinct treponemal subspecies with different evolutionary 

trajectories (Harper et al. 2011). Both the Columbian and Pre-Columbian theories hinge on 

proper diagnosis of treponemal disease skeletally.  Proponents of the Columbian hypothesis, 

such as Rothschild (2005), point to data suggesting that syphilis is absent from pre-Columbian 

Europe, Africa, and Asia, while it has been identified in North America as far back as 8,0000 

years ago.  However, Harper et al. (2011) assessed 54 published reports of supposed pre-

Columbian, Old World treponemal disease.  They found no solid evidence for a single case of 

Old World treponemal disease with a certain diagnosis and secure pre-Columbian date.  They 

conclude that the diagnosis of syphilis is complicated by the continued use of specific and non-

specific indicators by paleopathologists.  

The final category of specific diseases is metabolic disorders.  Metabolic disorders are all 

based in nutritional issues, be it the result of too much or too little of some food component.  

Vitamin C deficiency, known as scurvy, is characterized in subadults by subperiosteal 

 

25 

hemorrhages, hypertrophic lesions, abnormal flaring of ribs, and cortical thinning of long bones.  

Healed scurvy presents as coarsely structured transverse bands.  There is sparse evidence of adult 

scurvy.  Rickets and osteomalacia are associated with a lack of vitamin D.  Too little vitamin D 

prevents mineralization of bone protein.  Rickets is a systemic disease of early childhood that 

extensively impacts the growth and shape of the skeleton, causing bending deformities of the 

long bones and brittle stress fractures.  Osteomalacia is connected with intestinal mal-absorption 

of calcium and vitamin D in adults.  Because the skeleton is no longer growing, osteomalacia 

impacts the remodeling of trabecular and compact bone, causing diffuse diminished density 

(Ortner 2003c).   

Paleodemography 
 

Paleodemography is the study of past population dynamics including age and sex.  The 

interpretation of skeletal age distribution has been the focus of paleodemography since the 

1920s.  Critiques of paleodemography, responded to in turn by equally strong defense of the 

subject, have focused on measurement and analytical concerns (Bocquet-Appel and Masset 

1982).  Bocquet-Appel and Masset (1982) argue that osteological methods for estimating age and 

sex from skeletal remains are flawed.  They contend that age structures of skeletal samples 

reflect the age structure of the reference population that was used to create the aging standard, 

and thus not a true reflection of that population.  Second, they feel that age estimates on adult 

individuals lack sufficient accuracy (they argue that only an accuracy rate of .9 or better would 

work) to produce legitimate demographic profiles.  Van Gerven and Armelagos (1983) present 

research to contradict Bocquet-Appel and Masset’s assertions. Their data fails to support 

Bocquet-Appel and Masset’s conclusions, and the authors argue that paleodemography does 

have an important future and application.  Supporters of the field (Konigsberg and Frankenberg 

 

26 

1994; Frankenberg and Konigsberg 2006; Milner et al. 2008; Meindel and Russell 1998) argue 

that the critiques have spurred much needed constructive debate and timely reexaminations of 

models and assumptions.   

Beginning in the 1960s and 1970s demographic data began to be presented using life 

tables derived from the age profiles of skeletal samples. Life tables are used to measure 

mortality, survivorship, and the life expectancy of a population at varying ages. However, this 

approach treats skeletal samples as stable populations, with all skeletons deriving from a single 

population. Beginning in the 1980s demographic analysis transitioned to the use of hazard 

models (Frankenberg and Konigsberg 2006; Meindel and Russell 1998).  Hazard models are 

nonlinear mathematical functions that represent age related changes in the risk of dying, i.e. the 

hazard function (Gage 1991).  Hazard models, including Siler and Gompertz functions, allow for 

the use of age ranges and counter some of the limitations of life tables.  Hazard models provide a 

more accurate method of statistically controlling for age related biases and relative risk (Gage 

1994). 

Public Health Theory 

 

The modern public health movement began as a response to the negative impacts of 

industrialization and urbanization (Numbers and Leavitt 1997).  The spread of epidemic disease 

drew attention to the poor living and working conditions of the lower classes. American public 

health was greatly impacted by the work of Edwin Chadwick, whose work in England reshaped 

thinking about pure water delivery, the removal of sewage, and the collection and disposal of 

trash.  Chadwick pushed forth the notion that publicly run works, and new technology, would 

improve the unhealthy living conditions of society.  This challenged the prevailing notion that 

poverty itself was the main cause of illness by refocusing attention on the environmental and 

 

27 

social factors that impact health.  In both England, and the U.S., statistical studies of health and 

disease became an important component of public health reform arguments (Melosi 2000a).  By 

the mid 1800s many cities has established city health boards that worked with government 

institutions such as the almshouse and local hospital (Duffy 1990b; Leavitt 1982; Melosi 2000b).  

However rapid urban growth soon necessitated major improvements (or the creation) of public 

works.  Additionally the advent of bacteriology had major impacts on the priorities of public 

health, as greater attention was thus paid to biological pollutants in water supplies, food, sewage, 

and refuse (Melosi 2000b).   

The miasmic theory of disease was the dominant theory prior to the development of the 

bacteriological theory of disease transmission, (Duffy 1990a).  This theory held that bad vapors 

emanating from sewage and wastewater were the cause of disease.  The transition to 

bacteriological theory in the later part of the nineteenth century was slow amongst the public.  

This is highlighted by the case of “Typhoid Mary” and the personal and public backlash to her 

imprisonment (Leavitt 1997). Public health campaigns worked to change popular attitudes and 

beliefs about infectious diseases.  At a time when public health services were still new in many 

parts of the country (Bernstein 1972), the public was urged to take charge of the health and 

cleanliness within their own homes (Tomes 1997). The public health movement had a direct 

impact on morbidity and mortality trends in the United States.  As cities worked with public 

health officials to clean up waste, provide clean drinking water, and to monitor the spread of 

food born illness (such as with milk) infant mortality rates declined, average life expectancy 

increased, and many types of epidemic diseases were controlled (Duffy 1990a; Halverson 1949; 

Melosi 2000a).  

 

28 

Social welfare has been a contentious issue throughout American history.  Prior to the 

formation of centralized institutional care in the mid nineteenth century, the primary form of 

social welfare was outdoor relief.  Outdoor relief was usually cash or goods given directly to 

destitute individuals, typically widows, children, the elderly, and the sick.  Outdoor relief was 

routinely challenged because proponents argued that those on relief did not actually need help, 

and that providing cash and food removed any incentive to work.  At this time destitution was 

believed to be caused by failure of moral character (Katz 1986b).  Weakened by social animosity 

and overburdened by the increase in individuals seeking aid, by 1850 outdoor relief was 

generally replaced by centralized government run institutions.  These poor farms, almshouses, 

insane asylums, juvenile detention facilities, jails, and hospitals because the dominant form of 

social welfare.  Distinctions were made between the able bodied poor and the infirm.  If an 

individual was deemed able bodied, they typically were placed in a poor farm where they were 

required to work for their room and board (Katz 1986a; Wagner 2005).  The infirm were 

funneled into hospitals. 

Hospitals were not always viewed as accepted places to receive medical care. When 

centralized non-private hospitals began to develop in the mid nineteenth century, they were 

highly stigmatized and viewed as dumping grounds for the urban poor (Waller 2014).  The Civil 

War marked a turning point for popular understanding and acceptance of medical institutions.  

Because of the Civil War a large cross section of the American male population experienced the 

reality of “modern” institutional medical care (Rosenberg 1987).  As both the quality of hospital 

care, and the quality of medical training improved, social attitudes towards institutional medical 

care changed (Christianson 1997).  Between 1850 and the early 1870s hospital growth increased 

dramatically, spurred by social welfare reform and public health activism (Rosenberg 1987; 

 

29 

Waller 2014).  Though major medical improvements had occurred, and the hospital was seen as 

part of good public stewardship, it wasn’t until the turn of the twentieth century that middle- and 

upper-class individuals began regularly using public hospitals (Waller 2014).  However, a major 

function of public hospitals remained the medical aid of the dependent poor.  Lovell (1943) 

highlights how the larger numbers of sick and impoverished immigrants arriving in California, 

both during the Gold Rush and the Dust Bowl, necessitated the early creation, and long-term 

continuance of public health policies and state-run institutions to care for the destitute.   

More often than not indigent individuals under state medical care died.  The institutional 

management of indigent bodies is the final segment of state-run social welfare (Hoffman 1919).  

As the cost of funeral expenses outpaced the economic means of many working-class families, 

internment in a government run county potter’s field was not uncommon, even if the individual 

had not been treated in medical institutions (Kleinberg 1977).  Changes in both public health 

policy, the large numbers of individuals living outside of their close kin networks, and the 

increase in the number of poverty-stricken individuals all served to make pauper burials a reality 

of American life.  

In order to address the consequences of institutionalization it is necessary to first examine 

the historical record and develop a cultural context of institutional life. Institutional burials and 

their cemetery records are often poorly maintained while the burial ground is in use, and records 

of who is buried there or where the cemetery physical is after it falls out of use is typical.  

Anthropologists are faced with the task of re-associating these remains with difficult to construct 

contexts.  The bioarchaeology of institutes is truly the bioarchaeology of poverty.   

 

The Industrial Revolution ushered in the emergence of a heterogeneous poor lower 

working class (Phillips 2001b).  Just as it is today, historically poverty was highly stigmatized.  

 

30 

The rise of wage labor resulted in increasing scrutiny of able-bodied individuals seeking alms.  

This negative attitude toward the dependent poor is reflected in institutional cemeteries.  

Nawrocki (1990) suggests that poverty is one factor that can explain the invisible nature of 

institutional burial grounds. The minimalist mortuary treatment, and lack of hesitation in 

removing these individuals, may also represent a gap in social memory.  

 

The nineteenth century is significant because it was during this time that social policies 

and medical science were first applied to social issues in North America (Phillips 2001A). These 

cultural developments transformed the social and environmental landscape via prisons, 

workhouses, and asylums.  “The universal response in Europe and the United States was 

aggressive action to preserve the social order by re-creating “normalcy” within the institutional 

environment” (De Cunzo 2006:168).  Prisons and asylums served as long term custodial homes, 

while almshouses and hospitals were short-term residences (Katz 1986c). Institutions were (and 

still are) places of othering, places of discipline, and places of monotony that served to institute 

moral management.  

 

Additionally, during the nineteenth century the burgeoning public health movement was 

viewed as a solution to the increasing impact of disease in America’s urban cities (Bernstein 

1972; Duffy 1990; Melosi 2000). These new public health movements worked in tandem with 

the rise of institutions to mediate the impact of the near epidemic proportions of infectious 

disease in urban areas.  The biological consequences of institutions and public health policies are 

tangible.  

Race and Class Issues in Public Health 
 

Not everyone benefited equally from public health initiatives as issues related to social 

class, race, and ethnicity impacted public health access.  Immigrants, and migrants, were 

 

31 

consistently associated with germs and contagions. They were stigmatized as the cause of a wide 

variety of social and physical ailments (Markel and Stern 1999,2002).  This issue has been well 

documented in many time periods and places in the United States.   

Shah (2001a, 2001b) chronicles the production of the Chinese as different and a threat to 

white norms within public health knowledge in San Francisco.  She argues that for over sixty 

years the Chinese were characterized as a health menace based on ideas surrounding their 

citizenship, conduct, and health.  Public health officials portrayed the Chinese as vectors of 

contagious disease, and as willfully defying public health code.  Through scientific observation, 

manipulated statistics, and mapping of public and private living spaces, public health officials 

portrayed the Chinese as threats to middle-class white ideals, and as deviant, inhuman creators of 

ill health (Shah 2001a, 2001b). Wallace (2017) argues that similar to Shah’s study of the Chinese 

in San Francisco, south Asian immigrants on the west coast were also the victim of 

discriminatory public health and immigration policies.   

The concept of disease is a powerful trope in the racialization of Mexicans and Mexican 

Americans.  Invoking them as a diseased “other” worked to construct social and cultural strife 

and internal borders against Mexicans and Mexican Americans in the United States.  Mexicans 

are historically (and currently) characterized as a socially under privileged population that 

creates public health problems (Molina 2016).  Public health trends emphasized the prevalence 

of disease amongst Mexican immigrants, depicting them as willful agents, rather than victims of 

the disease.  This was often used as evidence to support deportation and stricter immigration 

policy.  In historic Los Angeles when Mexican migrants applied for financial assistance or 

medical care, they were given train fare to get them out of the area, rather than being supplied 

with proper aid (Abel 2007). As health and hygiene norms increasingly became associated with 

 

32 

standards of “Americanness”, public health officials were able to determine who and what was 

considered an “American” habit, thus branding any deviation as a defiance of acculturation 

(Molina 2006).   

Ethnic affiliation was not the only precursor for unfair public health access as social and 

economic class also impacted access to health care.  Although many public health programs and 

policies were aimed at areas of low economic means, the urban poor were often targeted as the 

cause of contagions and epidemics. Often the correlation between social categories and deviance 

made by public health officials were spurious and caused by the way the public health agency 

measured deviancy and disease (Kadushin 1964). An excellent example of the impact of 

unbiased data is found in the handling of tuberculosis mitigation and reporting in New York City 

at the close of the nineteenth century.  When compulsory notification of contagious or 

communicable diseases was instituted, the city was able to recognize patterns of contagion by 

creating an early form of epidemiological statistics.  This allowed the proper focus of general 

social welfare to all social and ethnic groups, rather than unnecessarily targeting a specific group 

for medical discrimination (Fox 1978).   

Prior to the mid 19th century, the local dispensary was the primary means of providing 

care for the urban poor.  Dispensary’s provided medication, vaccinations, diagnoses, and played 

an important role in public health management.  By the 1920s the dispensary had been pushed to 

the wayside, replaced by institutional hospitals.  Because the urban dispensary no longer fit the 

public’s perception of health care, the urban poor lost this crucial health amenity (Rosenberg 

1997).  As the bacteriological theory of germ disease became more accepted, it caused an 

indirect impact on social and political reform.  The middle and upper classes sought to insulate 

themselves from the potentially hazardous conditions surrounding the working class.  As urban 

 

33 

slums worsened, and “diseases of the poor” spread, public health became a concern for all of the 

class (Duffy 1978:423).   

Structural Violence 

 

The biological impact of social inequality has been extensively documented across 

multiple cultures and time periods. Anthropologists have attempted to incorporate the theoretical 

social framework of structural violence into this work.  Sociologist Johan Galtung (1969) 

developed the term “structural violence” to describe the social structures that suppress agency 

and impair the social, economic, and biological potential of an individual or group. It is structural 

because it is embedded in the political and economic forces that constitute social structures and 

organizations. It is violent because it results in direct injury or death (Farmer et al. 2006, 

Nystrom 2014; Nystrom et al. 2016). Gender, ethnicity, and socioeconomic status play a role in 

creating the time and place specific vulnerability responsible for health-related inequality. Both 

social and biological distinguishing characteristics can serve as a pretext for discrimination, 

however no single axis can fully define or predict an increased risk for suffering (Farmer 2004, 

2006).  Poverty can also diminish the protective status conferred by specific genders, ethnicities, 

and religions as it can crosscut all of these categories. Although cultural and medical 

anthropology has repeatedly made the link between structural violence and disease (Bourgas 

1995, 2010; Scheper-Hughs 1992; Farmer 1996; Farmer et al. 2006, Singer and Clair 2003; 

Quesada et al. 2011), this concept has not been widely applied by bioarchaeology. Disease has a 

documented relationship with social inequity and the unjust exercise of power; issues that have 

played an important role in human disease history and thus human history in a wider sense.  

They also have a significant impact on modern populations, and are likely to have a significant 

influence on the emergent health profile of the twenty-first century (Singer 2009:xv).  

 

34 

 

Bioarchaeologists that have incorporated structural violence frameworks in their research 

have focused on direct physical violence as sanctioned forms of control and power (de la Cova 

2008, 2011; Geber 2015; Klaus 2014a, 2014b; Martin et al. 2010; Perez 2014; Robbins et al. 

2012; Schug et al. 2013). Although several studies have incorporated health and pathological 

data (de la Cova 2011, 2012, 2014; Robbins et al. 2012; Schug et al 2013), only Klaus (2014a, 

2014b) includes a broad range of health-related data to evaluate the long-term biological impact 

of structural violence.  This pattern of social violence leaves observable and quantifiable 

biological impacts on the body. Social inequality is embodied via risk and is visible in the 

different prevalence’s of disease, as well as the outcomes between different social groups.  The 

risk, be it actual or perceived, can itself be a measure of social violence (Nguyen and Peschard 

2003). The relationship between inequality and health disparities and disease processes is a form 

of structural violence enacted through cultural and governmental policies and rationalities. 

Historically the reformation of social welfare policies led to an increase in structural inequality 

(Nystrom et al. 2016).   

 

Klaus (2014a) suggests that structural violence, as an interpretive framework in 

bioarchaeology is relatively simple. “Socially constructed restriction of resources can and does 

cause harm and death, evidence of which can manifest in skeletal and dental tissue.  Under such 

conditions, disparities in health reflect a form of violence” (Klaus 2014a:35). 

Bioarchaeologically structural violence could be the driving social force behind the morbidity 

associated with conditions such as enamel hypoplasias, anemia, stunted growth, and infection 

(Klaus 2014a:34).  However, there are specific contextual circumstances in which it is 

appropriate to apply structural violence as a theoretical model. Additionally, to apply structural 

violence it is important to remember that a thoroughly and deeply embedded engagement with 

 

35 

archaeological and historic contexts is necessary (Buikstra 2006; Goldstein 2006; Klaus 2014a; 

Palkovich 1996), thus limiting the type of sites it can potentially be applied to.  

 

Because structural violence hinges on how social inequality is produced and exercised in 

a rigidly hierarchical society, it is historically contingent on specific social trajectories.  Klaus 

(2014a:35) argues that it is most applicable to Western contexts with capitalist-style political 

economies and cautions against applying it elsewhere.  Structural violence can also build upon a 

Foucaultian inspired thesis that in modernity violence is sublimated and transformed in historic 

(and modern times) into a more “insidious and pervasive ordering of bodies through institutional 

practices” (Nguyen and Peschard 2003:457). Thus, institutions become the perfect microcosm 

within which to examine the biological consequences of structural violence. The conditions 

experienced by inmates reinforce both social and health inequalities (Nystrom et al. 2016).  

Epidemiological Transition  

 

Another theoretical conceptual framework for discussing how disease patterns change 

overtime is epidemiologic transition theory.  It focuses on the complex changes in patterns of 

health and disease overtime and the interactions between these patterns and their demographic, 

economic, and sociologic determinants and consequences (Orman 1971).  The original model 

introduced by Orman (1971) sought to capture the changes in cause-specific mortality following 

the industrial revolution in the United States and Western Europe. It has since been integrated 

within a wider evolutionary framework (Barrett et al. 1998; Armelagos et al. 1996, 2005; 

Zuckerman 2014).  Although the demographic transition is an important theoretical component 

of many physical anthropological studies, within paleopathology the epidemiological transition 

is focused on more frequently.  

 

36 

 

The classic model is now referred to as the second epidemiologic transition, bounded by 

the first transition coincident with the rise and intensification of agriculture (Cohen & Armelagos 

1984), and a third transition of emerging and reemerging infectious diseases in the modern era 

(Barrett et al. 1998). Although many studies have addressed the characteristics and impact of the 

second epidemiologic transition (Omran 1971, 1983; Preston 1976; Higgs 1979; Preston and 

Haines 1991; Schofield and Reher 1991; Gage 1993, 1994, 2005; Barrett et al. 1998), critics 

have suggested that the model fails to recognize and incorporate the impact of culture, socio-

economic forces, political forces, and health policy in understanding epidemiological profiles 

(Defo 2014; Harper and Armelagos 2010).  

 

Armelegos (2014) argues that high levels of social stratification means that not all 

citizens benefited from the improved nutrition, improved sanitation, and medical advances often 

correlated with the decline in mortality seen during the second transition.  However, very few 

papers have examined socio-economic status as a condition of transition timing.  The few that 

have (de la Cova 2012, 2014; Kitson 2014; Sattenspiel and Lander 2014) support the notion that 

changing socioeconomic structures directly challenge the fallacy of a universal epidemiologic 

transition (Zuckerman 2014). Nineteenth century America saw rapid increases in population, 

increases in the amount of urban residents, and virulent epidemics.  Additionally, because this 

framework emphasizes both socioeconomic and ecological factors as primary determinants for 

disease mortality risk during the epidemiological transition (Barrett et al. 1998), the widening 

socioeconomic gap during this time is an important factor to consider. Not every group or 

population reached the second epidemiological transition at the same time (Barrett et al. 1998, 

Omran 1971, 1983).  But what has not been examined yet in depth is to what degree 

 

37 

socioeconomic or cultural disparities viewed archaeologically and skeletally can be used to 

examine epidemiological transition timing.     

 

The typical generalization of rural v. urban differences in mortality during the second 

transition follows that mortality was higher in urban than rural areas historically, but has shifted 

in more recent times.  However, the generality of this description is in question (Gage 2014:386).  

Simplifying geographic contexts to a rural v. urban dichotomy oversimplifies the demographic, 

educational, socioeconomic, and public health related differences between two locations.  

Additionally, this view fails to take into account any community-level variables affecting 

mortality differentials.  “Perhaps community characteristics do make a difference” (Gage 

2014:387).   

Summary 

This dissertation seeks to address the health of individuals interred at the Santa Clara 

 
 

Valley Medical Center historic cemetery by utilizing specific theoretical approaches.  To 

understand why pathological and demographic prevalence’s occurring at the cemetery theories 

regarding structural violence, paleopathology, epidemiological transitions, and public health will 

be used.  A contextual approach will be used to interpret the skeletal and mortuary data within 

time and place specific historic contexts.   

 
 
 
 
 
 
 
 
 
 
 

 

38 

Chapter 3: Historical Background  

 

“Most of the western states have been peopled by a steady influx of settlers from two or three 
older states. Minnesota, for instance, and Iowa have grown by the overflow of Illinois and Ohio, 
as well as by immigration direct from Europe. But California was settled by a sudden rush of 
adventurers from all parts of the world…  This mixed multitude, bringing with it a variety of 

manners, customs, and ideas, formed a society more mobile and unstable, less governed by fixed 

beliefs and principles than one finds in such Northwestern communities…” James Bryce 

1891:887-888 

 

 
 

Introduction 

Although there is a robust pre-historic record in the greater San Francisco Bay area, this 

historical background chapter focuses on the historic-era context of Santa Clara Valley, 

California. To understand the framework within which the Santa Clara County Infirmary and its 

burial ground were established and operated, it is necessary to focus on the areas more recent 

history. The Santa Clara Valley Medical Center (VMC), and its predecessor the County 

Infirmary/Hospital, developed in response to a multitude of regional and global historic events.  

This historical context provides a summary of the pertinent events surrounding the European 

exploration and settlement of the Santa Clara Valley, focusing on San Jose, a brief framework of 

medical care in early California, and a historical overview of the establishment of the Santa Clara 

Valley Medical Center and the historic era cemetery associated with the Infirmary.  

Historic Era Context 

Spanish Period: 1777-1810 
 
 

In January 1777, Father de la Peńa and several Spanish soldiers set out with their families 

from Mission San Francisco de Asis to establish a mission on the banks of the Guadalupe River 

(Garcia 1997).  This settlement would become the Mission de Santa Clara de Asis (Mission 

Santa Clara), and served to solidify Spain’s claim to the area.  Spain’s method of colonization 

 

39 

consisted of three complimentary institutions: the pueblo, the mission, and the presidio (Garcia 

1997:8).  Jose Joaquin Moraga founded the Pueblo de San Jose de Guadalupe in the general area 

of modern downtown San Jose by November 1777 (Rehor and Beck 2015).   This was the first 

pueblo in Alta California1, and the Spanish government hoped this could entice further 

settlement of the area (Pitti 2003). The presence of the Mission and Pueblo made the valley a 

place of central importance to the Spanish empire. 

 

The mission prospered, due in part to the rich agriculture soil in the surrounding territory.  

This agriculture was fueled by the manual labor provided by Ohlone neophytes (Pitti 2003).  The 

pueblo grew in size rapidly, roughly doubling every twenty-five years (from 1790-1846, Source: 

Pitti 2003:12).   Following the Mexican Revolution in 1810, Spain lost control of Alta California. 

The lack of Spanish supply ships resulted in the pueblo, and the San Francisco presidio, 

becoming increasingly dependent on the mission for sustenance (Garcia 1997:8).   

Mexican Period: 1810-1848 
 
 

The shift to Mexican rule had dramatic impacts on the mission and surrounding 

community.  The 1834 Act of Secularization resulted in the redistribution of land previously held 

by the mission/pueblo (Garcia 1997).  This act gave residents enough land to establish large herd 

of cattle, and also gave residents a ready source of cheap labor to work in the fields by taking this 

land away from the surviving Ohlone.  Between 1834 and 1836 over eight million acres of land 

were opened to private ownership (Garcia 1997:14).   

 

During this time period, inhabitants of Alta California were dealing with not only major 

changes imposed by the Mexican government, but with the influx of American settlers.  Tensions 

1 A historic geographic region that roughly corresponds to present day California, Nevada, Utah, 
and Arizona.  

 

 

40 

were high, and by 1844 a small civil war had begun.  The 1844 Revolution was short lived, but it 

created uncertainty amongst the foreign-born population with regards to the province’s power 

base (Garcia 1997:21).  By 1845 several nations had challenged Mexico’s claim on Alta 

California.   In 1846 immigrants were arriving in larger numbers, including the Bear-Flaggers2 

under the command of U.S. Army officer John C. Frémont (Pitti 2003: 29).  Many Californios3 

did not oppose the impending American takeover and laid down their arms or joined them.  The 

Mexican American War, begun in 1846, was relatively short lived, and on February 2nd, 1848 

Mexico signed the Treaty of Guadalupe Hidalgo and ceded Alta California to the United States 

(Pfaelzer 2007).   

American Period: Post 1848 
 
 

Although the influx of immigrants to date seemed daunting, it was nothing compared to 

what was to come.  On January 24th, 1848, just nine days prior to the signing of the Treaty of 

Guadalupe Hidalgo, gold was discovered in the Sierra foothills (Garcia 1997, Pitti 2003).  The 

gold strike not only brought waves of foreigners into California, but also caused a mass exodus 

from the Santa Clara Valley, so much so the area was nearly depopulated.  So much food went 

unharvested that it rotted in place, causing near catastrophic shortages of food and inflated prices 

(Garcia 1997).   Perhaps it was then, that the value of the agricultural potential of the valley was 

truly recognized.  The population of Alta California in 1848 was estimated to be around 150,000 

(Pfaelzer 2007).  By mid-1849 the population doubled and had become so large and diverse that 

managing the new growth under existing governance was impossible.  In 1850 California was 

granted statehood.   

2 American immigrants that formed the Bear Flag Revolt  
3 Spanish speaking individuals living in Alta California 

 

 

41 

 

Many individuals that did not strike it rich in the gold mines did not return home, 

choosing rather to say in the Santa Clara Valley and turn to agriculture.  The rich growing soil 

and intensive cultivations earned the area the title “Valley of Heart’s Delight”.  Santa Clara 

Valley quickly became one of the largest producers of fruit in the world, propelled by the 

completion of the trans-continental railroad in 1869.  A robust fruit canning, drying and packing 

industry soon sprung up alongside the orchards (Munro-Fraser 1881:528).  

Early 20th Century: 1900-1940 
 

By 1914, Santa Clara County produced half of all the prunes grown in the United States 

(Irvine 1914).  There were fifteen large fruit and vegetable canneries, twenty packing houses, 

and several fruit preserving plants which produced an estimated $10,000,000 in manufactured 

goods, and employed seven thousand people (Irvine 1914).  The Santa Clara Valley lagged 

behind other nearby cities, such as San Francisco and Oakland, with the speed of urbanization 

and industrial growth (Pitti 2003:80). However drastic changes to area politics and industry 

began in the late 1930s and early 1940s.  This period, sometimes referred to as the “second Gold 

Rush”, ushered in an era of increased federal spending, U.S. military presence, and the early 

foothold for the technological industry (Pitti 2003).   

Immigration Trends 

 

Immigration is an important component of the peopling of the historic United States.  

Gerber (2011) notes three waves of voluntary international migration that had a substantial 

impact on the demographics: (1) 1840-1850; (2) late 1890s-WWI; and (3) post 1965.  Debates 

over immigration, specifically who should be allowed to immigrate, have been ongoing for much 

(if not all) of American history.  Between 1820-1920 over 35 million Europeans entered the 

 

42 

United States, with only 1% being denied entry.  During that time frame roughly one million 

immigrants from Asia, Mexico, Canada, and other parts of the western hemisphere entered the 

country (Gerber 2011).  Although European immigrants faced discrimination, individuals from 

non “white” countries (the definition of what was considered “white” varied drastically by time 

period) were confronted with severe discrimination, both cultural and political in nature.  For 

example between 1820 and 1920, 25% of Chinese immigrants were denied entry into the 

country.  This was exacerbated by exclusionary legislation (the Chinese Exclusion Act and the 

Page Act) that further limited immigration from China (Pfaelzer 2007).   

California’s immigration patterns are unique both in terms of the rapid influx of 

individuals and their regions of origin.  Prior to European contact California was home to a 

robust Native American population. It is estimated that prior to 1850 between 150,000 and 

300,000 Native Americans lived in California. By 1860 it is estimated that only 32,000 Native 

Americans survived (Pfaelzer 2007).  The rapid population decline was due to tensions caused 

by the Spanish mission system, epidemic disease, and later the influx of American settlers into 

the area (Pitti 2003a).  Following the Mexican American War, and ceding of California to the 

United States, individuals of Spanish and Mexican decent living in Alta California were forced 

to renegotiate their ethnic identity.  These Spanish-speaking individuals became known as 

Californios (Pitt 1966; Pitti 2003a).   

Though many Californios were born in Alta California, they were treated as foreigners, 

many of the American migrants lumping the Californios together with recent immigrants from 

Mexico (Pitt 1966).  Following the systematic loss of their land, many of the disenfranchised 

Californios in Santa Clara County found employment at the New Almaden quicksilver mine 

(Pitti 2003b). The discovery of gold in the Sierra foothills in 1849 set the stage for an 

 

43 

unpredicted wave of immigration into California.  California transformed practically overnight 

from a Mexican territory with approximately 150,000 residents (including native people, 

Mexicans, and Californios) to a formally recognized state with the population nearly doubling in 

size in less than a year (Commonwealth Club of California 1946; Pfaelzer 2007).  Although 

Africans first entered Alta California in 1769 in connection with a Spanish expedition (Ruffin 

2014a), African and African American populations in California and specifically Santa Clara 

County remained low (Ruffin 2014b).   

California’s geographic position made it the prime gateway for Asian immigration and 

the logical terminus of the westward Manifest Destiny migration. California had a larger Asian 

population than the rest of the United States combined (Commonwealth Club of California 1946; 

Coolidge 1909; Pfaelzer 2007), although European immigrants still comprised a majority of the 

population (Commonwealth Club of California 1946).  Chinese migration was substantially 

halted by the passage of anti-Chinese legislation (Coolidge 1909; Pfaelzer 2007).  Between 1880 

and 1940 Asian immigrants still comprised between 2-7 percent of the total population of Santa 

Clara County.  Asian immigrants situated themselves as an integral part of the California 

agricultural industry.  Overlapping waves of first Chinese, then Japanese, and Filipino 

immigrants ensured a large Asian population, even after the Chinese Exclusion Act (Tsu 2013). 

In the early 20th century, attention turned to the Japanese population as a potential “threat” to the 

white population.  The Japanese were viewed as threats because of their high birth rates, low 

infant death rates, and landownership (State Board of Control of California 1978). American 

migrants, however, were not immune from hostility.  The Great Depression and Dust Bowl 

created a population of American migrants and refugees that headed west in search of better 

living and working conditions.  However, the “Okies” were seen as anti-California acculturation, 

 

44 

and a burden on state housing, healthcare, and benevolence (California State Chamber of 

Commerce 1940; Jamieson 1942). 

County Hospital 

 

“…everything conductive to the welfare of the waifs of humanity has been done, so that their 
sufferings may be assuaged and their pillows smoothed as they fall into the grave”. – Munro-

Fraiser, J.P. 1881:148 

On March 31, 1855 Santa Clara County Supervisors, in accordance with an act to provide 

 

for the counties indigent sick, formed the “Board of Directors of the Infirmary of the County of 

Santa Clara” (Shortridge 1896:143).  In this organized effort to care for the indigent sick, the 

county was to bear two thirds of the expense, and the city of San Jose the remaining third (Foote 

1888).  At the same time, a county physician was appointed, and paid $50 a month towards the 

maintenance and medical attention paid for the indigent sick (Foote 1888).  It soon became 

apparent that a centralized location for treatment was required, and the Old Levy property was 

rented at a cost of $40 a month (Foote 1888).  Rapid city expansion soon rendered the Old Levy 

property inadequate, and arrangements were made to purchase the Sutter house from the Merritt 

Brothers for $5,500.  The Sutter house was located northeast of the city limits and included 

twenty-five acres.  The city occupied the premises until February 1856, when the property 

owners failed to provide a proper deed (Foote 1888).   

 

While waiting to find appropriate accommodations, Dr. G.B. Crane was contracted to 

care for the sick in their homes for a cost of $4,600 a year.  Dr. Crane demanded strict 

stipulations in his contract, where he was not to care for more than seven patients a day without 

additional pay.  This continued for several years until in 1860 the need for a larger hospital 

became apparent. An act of state legislature authorized counties to acquire land not to exceed 

160 acres to establish an infirmary and associated buildings to care for the indigent (tenBroek 

 

45 

1957:288) The city purchased the property of Hiram Cahill, which contained twelve acres 

situated on the south side of South Street just west of Los Gatos Creek.  The existing buildings 

were repaired and enlarged, and a pest house4 was built near the creek.  There were objections to 

having the infirmary, specifically the pest house, so close to the city limits.  In 1868 the board 

purchased one hundred fourteen acres from John S. Conner (See Figure 1), at a cost of $12,400.  

The buildings were moved from the Cahill property, and the old lot was divided and sold.  In 

1875 a contract to build a new infirmary was awarded to W.O. Breyfogle for $14,633.70.  

Messers, Lazen and Gash were contracted as the architects (See Figure 2).  To defray some of 

the costs of the expansion and new build, 81 acres of the Conner property were sold to different 

parties (Foote 1888).   

 

Figure 1. 1876 Map of Santa Clara County Showing County Infirmary and John S. Connor 

Property - Source: Thompson & West 1876, David Rumsey Map Collection. 

 

4 A quarantine building for infectious diseases 

 

 

46 

Figure 2. Infirmary, Santa Clara Co. 1876.  Lithograph.  Source: Thompson & West 1876, 

David Rumsey Map Collection. 

 

 

The Infirmary was a Gothic style building with six wards that could accommodate 65 

patients.  It included all of the modern amenities with gas, water, and modern medical equipment 

(Munro-Fraser 1881:148).  The institution was said to be “dedicated to Sickness, Poverty and 

Charity – a temple which is an honor to Santa Clara County, and is considered a model of its 

kind throughout the state” (Munro-Fraser 1881:148).   

 

Until 1883 the County Infirmary also served as an almshouse, where invalids in destitute 

circumstances were cared for.  In 1883, in an attempt to alleviate the costs of indigent relief, a 

county almshouse (also referred to as the county farm) was established in Milpitas (Foote 1888). 

Thus in Santa Clara County the medical care of dependents was entirely separated from custodial 

or almshouse care.  The hospital provided care for the indigents with severe medical conditions, 

while the slightly more able bodied destitute men occupied the almshouse (California, 1921).  

 

47 

 

The 1871 relocation was the last major move for the county hospital, as the Santa Clara 

Valley Medical Center still occupies that location today. The remaining property was used as a 

ranch, which supplied the infirmary and almshouse with “fruits, vegetables, eggs, butter, and a 

sum of money that is added to the funds by the sale of the superfluous products” (Mars 1901:75).  

The farm remained an important part of the daily operations of the hospital, and the acres used 

for production, as well as the numbers of cows, horses, hogs, and poultry were routinely listed as 

assets in official state level reports (State of California, 1902-1922).  The presence of farm 

animals on the property is apparent in maps as late as 1929 (See Figure 3).  A barn was also 

noted on the property, a farmer is listed on the payroll (Rehor and Beck 2015:2-8), and Jacob 

Albert lists his occupation as hospital gardener on the 1910 census (U.S. Census 1910, ED 67, 

page 6A).   

 

Later additional buildings including a tuberculosis hospital, Old Ladies’ Home, Old 

Men’s home, isolation hospital and pest house, and residences for nurses and superintendents 

were added (See Figure 4).  The Old Ladies’ Home cared for aging indigent women because the 

almshouse in Milpitas did not have proper accommodations for females (State Board of Charities 

and Corrections 1905).  The Infirmary was routinely noted as being “one of the best county 

hospitals in the state” (State Board of Charities and Corrections 1915:156).  In addition to 

structural expansion, the County Infirmary developed its service, treatments, and the population 

that it served (See Figure 5).  The 1906 San Francisco earthquake temporarily halted new 

development plans.   

 

The earthquake demolished the Tuberculosis Sanatorium, and severely damaged the main 

hospital building.  Three patients died during the earthquake, while seven others were seriously 

injured (Rehor and Beck 2015:2-10).  However, the hospital itself incurred only minor damages.  

 

48 

The second story of the main building was partially salvaged by lowering it to the ground floor 

and using it as a women’s ward until 1961.  The nearby Agnews State Hospital (asylum) lost 101 

patients and 11 employees when nearly every structure on the property was destroyed (State 

Board of Charities and Corrections 1906:54).   A county bond election was held to allocate 

money to repair damage to county buildings, including the infirmary.  In 1907, a new E-shaped 

wood frame building was constructed to serve as the new main infirmary building (Rehor and 

Beck 2015:2-10).  The new building (see Figure 6) is reported to have cost over $100,000 (State 

Board of Charities and Corrections 1908:125). 

The 1918 influenza epidemic spurred further hospital development, and in 1920 a new 

isolation unit was built.  In 1925, a 20-bed addition was added to the isolation unit. Expansion 

continued throughout the late 1920’s, including the addition of a pediatric ward and 

preventorium5 building (Roehr and Beck 2015:2-10).    By the early 1930’s the County Hospital 

was providing care for approximately 400 indigent individuals a day.  In 1946 the hospital 

provided a new tuberculosis sanatorium, blood bank, dentist, and physiotherapy.  It was also 

accredited as a nursing school, and provided graduate training in medicine, surgery, and 

obstetrics (Roehr and Beck 2015:2-11).   

The nursing school was initially established in 1905, and construction of a dedicated 

Nurses Hall began in 1906.  When it was completed in 1920, it accommodated up to thirty 

nursing students.  In 1913, the Infirmary became a well-respected teaching hospital. (Rehor and 

Beck 2015:2-12).  In addition to the physical changes of the campus, the infirmary underwent 

several name changes.  Records indicate that around 1912 it changed from County Infirmary to 

5 A preventorium is a space for individuals infected with tuberculosis that did not yet have the 
active form of the disease.  Its purpose was to prevent further spread of disease. 

 

 

49 

the Santa Clara County Hospital, and finally to the Santa Clara Valley Medical Center in 1966 

(Rehor and Beck 2015:2-12).   

 

 

 

 

 

 
Figure 3. 1929 County Surveyor Map Close-up - Showing Encroachment of Milk house, 

Horse barn and Cow Barn. Image Source Roher and Beck 2015. 

50 

 
Figure 4. 1929 Campus Map - Cemetery Boundary Highlighted in Red. Image Source 

Roher and Beck 2015. 

Figure 5. The County Hospital - Front Entrance Source: Mars 1901:77. 

 

51 

 

 

 

Figure 6. County Hospital Approximately 1907-08.  Source California 1908. 

 

The Infirmary Cemetery 

 
 

As previously mentioned, scant historical references have been located regarding the 

historic-era cemetery associated with the County Infirmary.  To date, no burial records have been 

located and the earliest map documenting the cemetery is a 1915 Sanborn Insurance Map, which 

unfortunately only gives a partial depiction (See Figure 7).  The clearest picture of the cemetery 

boundary is from the 1929 campus map (See Figure 4).   

 

The cemetery was most likely established after 1871, following the Infirmary’s relocation 

to the Connor property.  It is unknown if a cemetery was established at the Infirmary’s prior 

location at the Cahill property.  An exact end date is also currently unknown.  The latest map the 

cemetery appears on is a 1935 county surveyor record.  On the November 1937 insurance map, 

 

52 

the cemetery no longer appears and three buildings are depicted in what was the northern extent 

of the cemetery (Rehor and Beck 2015:2-13).   

 

Because of the cemetery’s association with the County Infirmary, it most likely also acted 

as a charitable institution.  Thus, the cemetery contained individuals buried at the counties 

expense, direct hospital/almshouse internments, and individuals from the greater community that 

could not afford burial elsewhere.  Specific burial records for this cemetery have not been 

located, gleaning information from other sources, such as Coroner Inquest reports is further 

complicated by the presence of additional potter’s field6 locations in the county.  Nineteenth and 

early twentieth century inquest records and death certificates are also vague and inconsistent.  

Often the place of burial is not always indicated, and although some individuals are listed as 

buried at the expense of the County, the inability to determine which potter’s field an individual 

went to complicates the matter. To date only two Coroner’s Inquest reports have been located 

that identifies the County Infirmary Cemetery as the place of burial. 

Because the infirmary was operated at the expense of the county, they were required to be 

transparent with their costs and operations.  For example, in an 1899 semi-annual report the 

County lists expenses of $715.30 incurred by “digging graves,” “burying indigents”, and 

“burying ex-Union soldiers” (The Evening News July 27 1899).  Although some soldiers 

received indigent burials, their status as veterans required specific burial treatments and they 

were not allowed to be buried in a potter’s field (State of California 1901:596).   

Services, such as burial of the indigent dead, were put out to bid by the County.  The County 

then published the name of the individual, or firm, that won that bid as well as the cost of the 

6 Burial ground where indigent and unknown individuals are buried. 

 

 

53 

contract.  For instance, in 1886 Trueman & Woodrow won the contract for $10 per burial, with 

$2 extra for coloring the coffins (The Daily News February 2 1886:3).  By 1899, multiple 

 

 
Figure 7. 1915 Sanborn Insurance Map - reformatted along match lines to show partial 

cemetery.  Image Source Roher and Beck 2015. 

 

companies were vying for the contract, with the San Jose Undertaking Company submitting a bid 

for $3.50 per burial, but W.B. Ward won the contract by underbidding at $2.93 per plain 

redwood coffin, $5.00 per black painted coffin, and $10 for redwood coffins with handles, 

varnish, and an inner lining (The Evening News August 8th 1899:4).  The county routinely paid 

multiple entities every month for different components of the indigent burial process.  In 

February 1902, the Infirmary fund receipts (Figure 8) note separate payments for digging graves 

($18), burying indigents ($20) and burying ex-Union soldiers ($50).  The February 1902 list of 

claimants owed money by the county (Figure 9) note that Peter Sex was owed $18 for opening 

 

54 

graves, A.B. Tyron was owed $20 for coffins, and W.B. Ward Undertakers were owed $50 for 

burial (likely the charge for the ex-Union solider burial).  

 

 

Figure 8. Infirmary Fund record book – Image from February 1902 account.  Image taken 

by author.  Archival source Santa Clara County Archives Clerk-Recorder Records 

Collection number 2009-009 through 2009-164  Series XII Miscellaneous 1840-1985 Sub-

series 5: Classified Allowances Infirmary fund 1896-1904.  

 

 

55 

 

 Figure 9. For County Needs Supplies and Labor Required During January Name of 

Claimants San Jose Mercury News February 16 1902 Volume LXI Page 7.   

Other Local Cemeteries 
 

The infirmary cemetery was not the only location the county buried indigent individuals.   

Potter’s field sections at Oak Hill Cemetery and Mission City Memorial Park were also used 

(Roher and Beck 2014:7-43).   

Oak Hill Cemetery (seen in the lower right corner of Figure 1) was the only municipal 

cemetery operating in San Jose from 1849-1870.  Originally designed as a joint Protestant and 

Catholic cemetery, it also sectioned off a portion for a potter’s field.  Although burial records 

were kept from the beginning, in June 1862 Marshal Jasper D. Gunn, the cemetery 

superintendent, absconded with the cemetery funds and all records.  They were unfortunately, 

 

56 

never retrieved so the earliest death certificate on file for the cemetery is 1862.  The cemetery 

underwent significant expansion in the 1870s.  At this time, the first burials of individuals of 

Chinese ancestry occurred in the western portion of the cemetery.  By 1900, several Chinese 

organizations had worked together to deed land for their own cemetery.  In 1878, a new potter’s 

field was allotted between the Chinese section and the Catholic section.  By 1888 it contained 

nearly 400 interments.  The original potter’s field had been near the center of the cemetery, and 

at that time, it was estimated to have held nearly one thousand individuals.  In 1913, the City of 

San Jose sold the cemetery to a private management group, the Oak Hill Cemetery Association 

(Maggi et al. 2002).  It is still in use today.   

The burial ground now known as Mission City Memorial Park was founded by the Santa 

Clara’s board of trustees in 1850-1851. It has been called simply “the graveyard”, Town of Santa 

Clara Cemetery, Santa Clara City Cemetery, Santa Clara Protestant Cemetery, and since 1972 

Mission City Memorial Park (Lichtenstein 2005:9).  Mission City Memorial Park has multiple 

potter’s field sections within the boundary of its cemetery, the earliest mention being a July 1862 

ordinance for the operation of the cemetery that notes that persons not owning burial lots could 

only be buried in the public potter’s field portion of the cemetery (Lichtenstein 2005:9).  One 

potter’s section was in use from 1913-1937, and the other from 1937-1954.   Individuals that 

received indigent burials at Mission City Memorial Park have “County Hospital” or “Santa Clara 

County Hospital” listed as their place of death (Dejanvier 2014). 

 

Conclusion 

The Santa Clara Valley underwent significant demographic, political, and cultural 

changes during the late 19th and early 20th century.  The rapid influx of immigrants following the 

Gold Rush, the west-ward migration associated with Manifest Destiny, and the agricultural 

 

57 

potential of the area made it a hub of commerce and trade.   Migration to California, and 

specifically Santa Clara County, was unique not only in its tremendous volume, but in its region 

of origin. Even as late as 1940, two out of every three Californians had been born outside of the 

state (Commonwealth Club of California 1946:230).  From the standpoint of nativity, the 

majority of Santa Clara County was comprised of individuals of European (both foreign and 

native born), Chinese, Japanese, Filipino, Californio, Native American, African American, and 

Mexican ancestry. The demographic makeup of the state and county, at this time, is skewed 

heavily male: there was a 12:1 male to female ratio in California in 1850, which did not equal 

out until roughly 1940 (Commonwealth Club of California 1946).  In the 1890s the average age 

in Santa Clara County was 46, 20 years older than cities of similar sizes like Chicago (The 

Evening News 1896).   A lack of children is also noted in population data, with individuals under 

the age of 20 accounting for roughly 30% of the population from 1900-1940 (Commonwealth 

Club of California 1946).  

The Santa Clara County Hospital cemetery, and the skeletal sample exhumed from it, 

represents a unique time and place in United States history.  Those governing Santa Clara 

County quickly realized that larger institutional structures were necessary to manage the fast-

paced growth of the low socioeconomic portions of the population.  The individuals migrating to 

the Santa Clara Valley in the 19th and early 20th century were far from the more traditional 

caregiving structures of family and community. “This growth of county hospitals [in California] 

was caused primarily by the acute need for a substitute for home life” (Cahn 1936:144). There is 

a lack of rigorous investigation into the health trends amongst 19th and 20th century immigrants 

and poor in an area central to Americas economic, territorial, and populational expansion: 

California.  The skeletal sample used in this dissertation provides an opportunity to better 

 

58 

understand the health of immigrants and low socio-economic status individuals in the late 19th 

and early 20th century Western United States.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

59 

 

 

Chapter 4: Research Questions & Expectations 

 

Introduction  

This dissertation research seeks to examine the complex processes that led to potential 

social and health inequalities by examining a large-scale historical cemetery from California; the 

Santa Clara Valley Medical Center (VMC) Historical Cemetery.  The primary objective of this 

research is to understand the health patterns present within the VMC burials while incorporating 

both the mortuary archaeological and historical context of the burial ground. Furthermore, this 

research will study the health of the excavated individuals while specifically examining the 

biological impact of the county’s efforts towards public health initiatives, public policy toward 

the poor, and prevailing medical practices of the time.  This research also seeks to focus on the 

comparison of the VMC sample with similar samples from indigent and non-indigent historical 

cemeteries.  These comparisons will serve to establish the relative health of the VMC sample.   

 

 

Research Questions and Expectations  

With this research, I propose to address the following broadly defined research questions 

pertaining to the VMC collection:  

Question 1: Does institutionalization and or structural violence lead to identifiable 
biological impacts? 

 
 

Santa Clara County was an early adopter of public health policies, creating a means to 

care for the indigent sick as early as 1855 (Shortridge 1896).  The presence and impact of 

communicable diseases was a major health concern during the 19th and early 20th centuries 

(Duffy 1990a, 1990b).  Santa Clara County was forced to contend with epidemic and endemic 

 

60 

diseases in both the urban city center and rural countryside.  The rapid population growth, and 

burgeoning migrant population, soon overwhelmed the initial public health systems put in place 

during the mid-1800s, forcing new policy implementation that focused on broadly improving 

sanitation, food purity, and infectious disease.  

 

Historical records indicate that hospital patients, or inmates as they were called, were 

treated at the hospital for periods ranging from several days, weeks, months, or even periods 

longer than ten years. Thus, the institutional policies of the hospital should potentially have 

visible biological impacts. Personal effects will be used to separate hospital patient internments 

from burials of individuals from the wider community.  It is expected that hospital burials will 

show signs of increased biological stressors, and more individuals with multiple stressor events 

than other burials at VMC. The increased variability and quantity of pathological reactions in the 

hospital burials are expected due to institutional policies and issues accessing timely medical 

care. 

 

Immigrants and lower socioeconomic migrants entering the Santa Clara Valley at this 

time faced structured risk, referred to as structural violence, which was created by the prevalent 

social forces of the time. Time and place specific vulnerability, caused by embedded political 

and economic forces, has specific biological consequences. Even though the hospital was created 

to serve indigent community members, were all indigents given equal access?  If structural 

violence was present in the area, it should be discernable within the pathological biological 

reactions present across VMC sample.  If structural violence impacted the patterns of health and 

stress present at VMC, it is expected that higher rates of infectious disease and untreated 

conditions would be present in the non-hospital burials.  

 

61 

Question 2. At this time, we know that major issues such as the second epidemiological 
transition, public health reform, immigration, and socioeconomic status impact the health 
and nutrition of people. Given the nature and historical context of VMC how did these 
events effect people at VMC?  
 
 

Previous bioarchaeology studies of health (Grauer and McNamara 1995; Higgins and 

Sirianni 1995; Higgins et al. 2002; Lanphear 1988, 1990; Leher et al. 2010; Milligan 2010; 

Ubelaker and Jones 2003) have used selective criteria for examining the health of past 

populations.  These studies focus on prevalence rates of pathogenic and activity-based stressors 

(dental hypoplasias, porotic hyperostosis, periosteal lesions, pathognomonic lesions) that are 

used to examine the comparative health of the sample. This sample is expected to exhibit high 

levels of biological stress both from activity-based stressors and pathogenic stressors. This study 

expands upon the on-site collected data and subsequent report by incorporating more detailed 

comparison of the prevalence, location, and co-occurrence of pathological and degenerative 

changes.  Specifically, I test whether incidence of the biological stressors is statistically different 

between age, sex, and ancestry groups. In addition, I test for statistical differences in different 

combinations of pathological conditions and age, sex, and ancestry groups. It is anticipated that 

the number and variability of pathological conditions will be greater for adult males in the 

sample than female or subadults.   

 

 There is a general consensus that the second epidemiological transition at the end of the 

Industrial Revolution ushered in widespread trends of decreased infant mortality, increased life 

span, decreased infectious disease mortality, and an increase in degenerative diseases (Barrett et 

al. 1998; Gage 2005).  However, it has been argued that not all populations would have reached 

this transition at the same rate (de la Cova 2008).  Populations that were disadvantaged with 

regards to equal access to resources would still be facing higher rates of infectious disease and 

increased mortality rates that are typically associated with the first epidemiological transition 

 

62 

(Gage 2005; Orman 1977). Therefore, the impact of public health initiatives, immigration, and 

socioeconomic status will be considered when evaluating the VMC sample.  Specifically, the 

VMC sample will be compared to samples from other historic burial grounds.  It is anticipated 

that the VMC sample will show high rates of infectious disease and a higher mortality risk than 

other populations due to the low socioeconomic and migrant status of the individuals interred 

there.   

Question 3: Putting the cemetery in context with the historical record suggests a set of 
expectations of particular kinds of pathologies. How do these expectations compare with 
the pathologies documented in the skeletal remains? 

 
 

As previously stated, to date no burial records or inmate specific hospital records have 

been located for the entire time period the cemetery was in use.  City and county level public 

health documents are available that note disease prevalence and health issues in the area.  Some 

of the diseases noted include infectious processes that impact the skeleton, primarily 

tuberculosis, syphilis, coccidiomycosis, and generalized infection.  Additionally, illness such as 

pneumonia, phthisis, and small pox are noted, which despite being fast acting disease, still hold 

the potential for generalized skeletal response. While pathologies that can be determined from 

skeletal remains are limited to long term chronic issues (due to bone remodeling timing), and 

several pathogonomic diseases, the historical record tends to under-represent chronic multi-focal 

disease processes.  It is anticipated that the skeletal sample will exhibit a wider variety of 

pathological conditions sample wide, and per individual, than the historical record.  The low 

socioeconomic and migrant nature of the sample should also result in higher rates of infectious 

disease processes being present than the larger county, state, or county wide historic record.   

 

63 

Question 4: How does VMC compare to similar cemeteries in terms of the consequences of 
structural and institutional behavior? 
 
 

Observations related to the health and nutritional status of the VMC sample are compared 

with similar samples.  Similar studies show high mortality and morbidity rates during the time 

the VMC cemetery was in use.  Although several historical cemetery samples are used in the 

comparison, two specific sites will be the main focus: Milwaukee County Institution Grounds 

(MCIG), Milwaukee Wisconsin, and Alameda-Stone, Tucson Arizona. Both samples provide for 

a comparative study of health as they represent a similar time period and/or context in which the 

VMC cemetery was in use. The MCIG sample allows for comparisons with another indigent 

sample from the same time period.  The Alameda-Stone cemetery was selected because of its 

rural western context and 19th century timeframe. In addition, the demographics established for 

each cemetery are compared with the VMC cemetery.  The comparison of prevalence rates for 

the various assessed pathologies by age, sex, and ancestry are used to address the similarities and 

differences between subsets of each sample. It is anticipated that VMC will be more similar to 

MCIG due to the institutional nature of the burial sample.   

Question 5: Are there changes in the cemetery in terms of the spatial organization, and 
might these be attributed to change over time or differential treatment of health? 
 
 

There is an unfortunate assumption that potter’s field burials are devoid of material 

culture.  Though they tend to have fewer grave goods, there is still ample material culture that 

can have traditional mortuary archaeological analysis applied. The analysis of grave goods, 

coffin construction, and spatial patterning in conjunction with biological categories such as age, 

sex, ancestry, and pathological conditions will be conducted to determine if additional health 

patterns and cemetery use patterns are present.  Currently the 2015 site report by Rehor and Beck 

provides only a cursory analysis of the sites artifacts and spatial patterning.  Additionally, 

 

64 

analysis of the grave goods and coffin construction is performed to see if there are any temporal 

distinctions within the cemetery. Clustering by biological profile or categories of grave goods 

indicates differential treatment of specific burial categories.  Similarly clustering of temporarily 

diagnostic artifacts would elucidate the timing of burials within the grater cemetery.   

 

Summary 

These questions are not independent, but together they help me frame an interpretation of 

the cemetery that takes into account the historic nature of the Santa Clara Valley, the historic 

nature of the institution, and the biological stressors created by these unique trajectories. The 

skeletal analysis, mortuary analysis, analysis of associated historic documents, and comparisons 

of VMC to other samples all serve to explore the relative health of the cemetery.  This is an 

opportunity to contextualize Santa Clara County and California’s health within larger U.S. 

history in the late 19th and early 20th centuries by using primary skeletal and mortuary 

archaeological data.   

 

 

 

 

 

 

 

 

 

 

 

65 

 

Chapter 5: Materials & Methods 

 
This chapter outlines the primary research sample used for this study and the data collected from 

Introduction 

the sample.  The methods used in the data collection, as well as a discussion of the comparative 

skeletal samples is also included.   

Introduction to Excavation 

 

In February of 2012, construction crews working on a new building at SCVMC 

discovered intact coffins and isolated human skeletal remains.  The construction plans could not 

be altered to avoid the burials, so a controlled excavation was conducted to remove burials 

within the project area, identify the physical extent and period of use of the cemetery, and 

attempt to identify the individuals interred there.  From July 2012 thought January 2014, URS 

and subcontractor D&D Osteology excavated a total of 998 in situ burials that included the 

remains of 1,004 individuals (Figure 10). After analysis in the on-site field laboratory, in October 

2014 the remains were transferred to California State University, Chico for a 10-year curation 

period to allow for additional research. At the end of this 10-year period (2024) the remains will 

be cremated by the county and reinterred.  The county has also requested a tiered return of the 

remains, which will begin in 2019.  

The exact boundaries of the approximately 2.4 acre cemetery have not been confirmed. 

This size estimate is based on a 1929 county survey map, the only map located thus far that 

depicts the entire boundary of the cemetery. Approximately 35% of the anticipated cemetery was 

excavated through this project.  It is highly likely that additional burials are present in the 

unexcavated portions of the cemetery currently covered by existing hospital infrastructure. The 

 

66 

sample is overwhelmingly adult (967 adult, 20 subadult, 17 fragmentary), and male (643 male, 

100 female, 261 indeterminate).  This research project includes all burials from the excavated 

area of the cemetery.  

 

Figure 10. SCVMC Excavated Burials.   
On-site data collection protocols 

Biological Profile  

Of the total 1,004 individuals, 743 have sex assessments and 987 have estimations of age 

(493 of whom have specific age range estimations).  The age and sex assessments consider 

multiple factors from several areas of the skeleton, with the number of indicators used being 

 

67 

conditional on the completeness and preservation of the burial.  The overall poor preservation 

seen throughout the cemetery is one reason there are so many individuals with indeterminate sex 

assessment and non-specific age estimations (i.e. only “Adult”).   

 

On-site osteologists recorded paleopathological observations for all individuals who 

exhibited signs of skeletal stress.  Ortner’s (2003), Identification of Pathological Conditions in 

Human Skeletal Remains, was the main reference used when making the differential diagnosis.  

Conditions were divided into the following categories: infectious disease, inflammation and non-

specific infections, developmental defects, degenerative conditions, neoplasms and tumors, 

nutritional deficiencies, and other.  At SCVMC, 79% of the total sample (795 individuals) 

exhibited some form of pathology. Many of the individuals not exhibiting pathological changes 

were burials whose poor preservation prevented assessment. 

On-site osteological data collection relied heavily on protocols outlined in Standards for 

Data Collection from Human Skeletal Remains (Buikstra and Ubelaker 1994).  The data 

collected included: an inventory of skeletal element presence and absence as well as the 

completeness of each element; estimations of sex and age; observations of dental pathologies; 

observations of pathology; observations of non-metric traits; and post-cranial measurements 

(cranial metric data was not collected on site due to a lack of appropriate equipment). A brief in 

situ osteological assessment was completed for each burial, with a more detailed analysis being 

conducted later on-site. Descriptive notes and photographs were also collected. Ancestry 

assessment was not preformed onsite at the beginning of the project (approximately first 600 

burials), so a re-analysis was done via photographs after the project was completed. 

Age 

Age estimations for adult burials were based on multiple lines of evidence, with the 

scoring of several cranial and pelvic features (when present).  Primary methods for age 

 

68 

estimation of adults included auricular surface (Lovejoy et al. 1985); pubic symphysis phases 

using the Suchey-Brooks method (Brooks and Suchey 1990) or the Todd method (Todd 1920); 

fourth sternal rib end following the Iscan method (Iscan et al. 1984a, 1984b, 1985); and cranial 

suture fusion using the Meindl and Lovejoy (1985) method. Secondary age indicators such as 

overall body size, and degenerative changes such as osteoarthritis, osteoporosis, and dental 

attrition were also considered.  Age estimation for subadults was based on dental development 

and epiphyseal fusion (Baker et al. 2005, Schaefer et al. 2009). It should be noted that generally 

osteologists are excellent at aging younger individuals because age related changes are due to 

growth and development, allowing for a finer degree of specificity.  As the skeleton ages, these 

indicators shift to degenerative changes, making the age estimations broader.  Additionally, there 

is an “age wall”, where individuals older than 50-60 tend to look alike, so the finely detailed age 

estimations are lost and instead ranges such as 50+ must be given.    

Sex 

Biological sex estimation was completed using standard methods outlined in Buikstra and 

Ubelaker (1994), focusing on the pelvis and skull.  With regard to pelvic features, the sciatic 

notch width was the most commonly used sex estimation as it was the most common feature 

preserved in the skeletal sample.  Other features of the pelvis, specifically the pubic were poorly 

preserved.  Interpretation followed Blanchard (2010) and Walker (2005), where scores of 3-5 are 

likely male, a score of 1 is likely female, and a score of 2 is indeterminate.  Further interpretation 

of sciatic notch contour considered Bruzek (2002).  When the pubic bone was present;shape, 

sub-pubic angle, and presence or absence of a ventral arc and preauricular sulcus was recorded 

following Buikstra and Ubelaker (1994).   

Secondary methods included scoring non-metric cranial traits and measurements of 

articular surfaces. Cranial traits scored (per Buikstra and Ubelaker 1994) included nuchal crest, 

 

69 

mastoid process, supraorbital ridge, mental eminence, contour of the supraorbital margin, and 

angle of the ascending ramus of the mandible.  When the humeral head, glenoid fossa, or femoral 

head were present the appropriate diameter or height measurement was taken.  These 

measurements were used to estimate sex based on Trotter (1970 in Bass 2005).    

Ancestry 
 

Ancestry was assessed based on cranial traits which have been demonstrated to correlate 

with regional ancestry (Gill 1998; Gill and Rhine 1990; Hefner 2007, 2009; Rhine 1990; Scott 

and Turner 1997). Individuals were categorized as: Asian, African, European, Latino, or 

Indeterminate. Probable assessment of ancestry required a minimum of three strong indicators 

supporting that classification.  If fewer than two traits were scorable, or if the present traits were 

ambiguous, ancestry was classified as indeterminate.  The relative strength of traits (see Table 1) 

was based on multiple sources (including Anderson 2008; Bass 2005; Birkby et al. 2008; Brooks 

et al. 1990; Gill 1998; Gill and Rhine 1990; Rhine 1990; Scott and Turner 1997; and White et al. 

2011).  Preference was given to traits classified in the work of Hefner (2007, 2009).   

Table 1. Non-metric traits used to ancestry assessment.  Table source Rehor and Beck 

2015:5-5.  

 

 

70 

Archaeology  
 

Burial associated artifacts were recorded in the field while in-situ, as well as described on 

the excavation forms during the collection process.  Most artifacts received only a cursory in-

field analysis, while unusual artifacts such as coins, jewelry, or any artifact that could provide 

information regarding individual identity or date of burial was further examined in the field 

before removal to the URS’ laboratory in Oakland, CA. Field examination of artifacts included 

gentle washing, soaking in alternating baths of citric acid or baking soda/vinegar to remove 

corrosion.  Leather and fabric artifacts were dry-brushed and set out to dry before being bagged.  

All burial associated artifacts were cleaned and washed at the URS’ laboratory.  Artifacts were 

sorted by material and group, following the classification system from the Anthropological 

Studies Center’s SHARD How-To Manual (2008), which is informed by South’s (1977) 

functional artifact description categories.  A unique catalog number was assigned to each artifact, 

incorporating the originating burial’s provenance number.  Burial associated artifacts were 

divided into two main categories; mortuary and cultural.  Mortuary artifacts are any object 

directly associated with the coffin itself.  Cultural artifacts include items placed in the coffin on 

or with the body  

 

Coffin locations were recorded using a total station by individuals from the Foothill 

College department of Applied Anthropology.  Surveyors recorded each corner of the coffin, 

which was used to document the coffin shapes (Rehor and Beck 2015). 

 

In July 2016, a validation study was conducted on a sub-sample of 63 individuals 

Validation Study 

 

(currently housed at California State University, Chico) to assess the accuracy of the data 

collected on-site.  Overall discrepancies between laboratory and site data were minimal. During 

 

71 

laboratory analysis four individuals were assessed as probable or possible male/female, while the 

on-site analysis had given a definitive assessment of male/female.  In each case, the specific 

portion of the skeleton used onsite to assess sex (i.e. the sciatic notch) was not observable in the 

laboratory due to the poor preservation and the fragmentary nature of the remains. There was a 

single individual with an age discrepancy (aged 30-40 onsite but 60+ in lab) due to conflicting 

auricular surface scores.  There were not any major discrepancies with the pathological data.  

The ancestry assessments have some discrepancies (n=4), but this may be due to the methods 

used. This validation study demonstrates confidence in the on-site osteological assessment.  I 

acknowledge that future laboratory analysis of these remains may contradict some of the on-site 

analysis, but I remain confident in the larger assessments and trends that can be made from the 

on-site data.  

Paleopathology & Indicators of Health 

 

This research uses the osteological and archaeological information recorded on the 

primary excavation forms. The data was transcribed from the primary forms and standardized.  

An examination of the pathological, age, sex, and ancestry trends present among the SCVMC 

skeletal remains was used to establish morbidity patterns for the sample. A study of the general 

health and nutritional status of the sample included an examination of the presence and absence 

of specific and non-specific disease possesses.  Variables examined include: porotic 

hyperostosis, periosteal lesions, and pathognomonic lesions (tuberculosis, syphilis, mycosis). 

References consulted for interpretation of trauma and pathology on-site included Aufderheider 

and Rodriguez-Martin (2006), Mann and Hunt (2005), Netter (2003), Ortner (2003), and 

Waldron (2009). The poor preservation of the skeletal remains prohibits the inclusion of stature 

and growth measurements. Out of the total 1,004 burials 79% of the total sample (795 

 

72 

individuals) exhibited some form of pathology. Records from the county and state board of 

health were compared to the skeletal data to provide additional context for assessing the impact 

of public health initiatives.  Specifically, the potential for differential treatment and access to 

health-related resources based on social inequalities was examined in order to address research 

question one and two.   

 

Age and sex estimations recorded on-site were used to separate the sample into subsets.  

These subsets consist of general categories such as male vs. female.  The prevalence rate for 

specific pathogens and non-specific indicators of stress will be compared across the subsets.  In 

addition to sex-based subsets, specific age-based categories were established. The categories will 

follow categories used on-site: fetus (in utero or perinatal); infant (0-3 years); child (4-10 years), 

juvenile (11-17 years); subadult (<18 years); adult (>18 years), young adult (18-34 years); 

middle adult (35-49 years), and older adult (>50 years). Ancestry assessments recorded on-site 

will be used to separate the sample into the following categories: Asian, African, European, 

Latino, Mixed-Other, and Indeterminate. However, as previously stated, ancestry assessment was 

not conducted on-site routinely until after the 600th burial. URS employees at San Francisco 

State University reassessed some individual burials in person. No individuals were previously 

scored as Native American.  

Demographic Analysis 

 

A demographic analysis employing various Siler and Gompertz mortality models, as well 

as correspondence and transition analysis was used to compare the osteological age-at-death 

assessments of the 493 SCVMC individuals with specific age estimations.  A mid-point was 

taken for each osteological age estimation (i.e. an age estimation of 40-60 was recorded with a 

midpoint of 50).  The data set includes a Hazard Function, Gompertz Hazard, and a Siler Hazard 

 

73 

(Chamberlain 2006; Gage 1991; Holman 2001; Konigsberg and Frankenberg 2002; Konigsberg 

and Herrmann 2002; Trask 2010; Wood et al. 1992, 2002) run in R using Lyle Konigsberg’s 

hazard model code (available at http://konig.la.utk.edu). The output a1, b1, a3, and b3 parameters 

were then input into Nick Herrmann’s paleodemographic modeling program to compare each 

data set. The parameters were graphed using their respective models.  The log likelihood ratio 

and c2 tests of the individual a and b parameters were estimated in the MLE computer program 

(Holman 2001).  Hazard analysis generates survivorship and mortality models. Survivorship is 

the probability that an individual will survive to a specific age (Chamberlain 2006).  The 

probability of surviving beyond a specific age ranges from 1.0 (a 100% chance of being born) 

and 0.0 (a 0% chance of survival beyond the maximum recorded age). Mortality is the 

probability of a segment of the population that will die within a given age interval (Chamberlain 

2006).   

 

Historical Archives 

Historical records associated with the SCVMC hospital and cemetery, as well as Santa 

Clara County were used to identify cultural factors that would have impacted the skeletal sample.  

Specifically, the Santa Clara County Hospital patient intake register, 1880 U.S. federal pauper 

and indigent census, U.S. census data, accounts from various local newspapers, coroner’s 

reports, California Board of Health biennial report, and the California Board of Charities and 

Corrections biennial report were used to further elucidate the socio-political context of the time.   

The California Board of Health biennial report and California Board of Charities and Corrections 

biennial report are used to examine the city and counties efforts towards public health initiatives 

and their impact on the death rates within the county.  These sources will be examined to address 

research questions two and three.  The historical sources will be used to address questions related 

 

74 

to public health and institutionalization.  They will also be used to address expectations based on 

the comparison of the skeletal sample with the historical record.   

In particular the Santa Clara County Hospital Patient Intake Register Volume 5 is used to 

establish expected demographic, examined causes of death, and to examine the different 

populations being treated and dying at the hospital.  Information in the ledger including the 

categories of name, age, marital status, nativity, cause of death, date of death, date of burial or 

removal, and additional remarks (which noted if the individual received a county burial or if they 

were buried out of the area).  The records of 3,076 individuals were transcribed and coded into 

an Excel database. 

Historic Age 
 
 

The age recorded in the ledger was used.  There always exists the potential for slight 

errors in reported versus actual age, but the documented ages were accepted at face value.  Only 

20 individuals did not have a recorded age.  Stillbirths were recorded with an age of 0. 

Age data was categorized into five categories: infant (<1 year), juvenile (1-20 years), young 

adult (20-35 years), adult (35-50 years), older adult (50+ years). 

Historic Sex  
 
 

Sex was not recorded in the death record ledger, so the sex was interpreted based on 

individual names.  Every individual was classified as male, female, or unknown.  For names with 

questionable sex relation, the cause of death was first consulted (i.e. if the individual had a 

ruptured uterus = female), and if that wasn’t conclusive the census was consulted to see if that 

individual could be located and sex could be determined.  Stillbirths where no first name was 

given, and no sex was recorded (many stillbirths were listed with Surname, Infant, Sex i.e. 

“Canfield, Infant boy”) were listed as unknown. 

 

75 

Historic Ancestry 
 
 

The location of nativity was recorded.  If the individual was born within the United States 

the state was documented, but if they were born outside of the United States only a country 

designation was recorded in the ledger.  Nativity is unfortunately not the same as ancestry, 

referring specifically to the location of an individual’s birth, rather than the ethnic or ancestral 

group they identify with and how skeletal material is classified.  The nativity data was used to 

examine larger migration trends within the county death ledge sample but is unfortunately not 

directly comparable with the skeletal data.  

Historic Pathology 
 

The cause of death was directly transcribed, then matched and coded to the CDC top ten 

causes of death for the years covered by the ledge (1925-1933). For example, “pulmonary TB” 

was coded as tuberculosis, and “Chr. Endocarditis” was coded as heart disease. Causes of death 

that did not match the 13 causes of death listed by the CDC during 1925-1933 were coded as 

other.   

Mission City Memorial Park 
 

An index of burials at Mission City Memorial Park was compiled from the cemetery’s 

internment records (1874-1997) by Larry DeJanvier and made publicly available on the Santa 

Clara County Historical & Genealogical Society website7. The website scraping tool import.io 

was used to convert the website data into structured csv files.  The scraped data was cleaned and 

organized (i.e. fixing any parsing issues).  Categories included in the data are: last name, first 

name, middle name, birth date death date, age, sex, place of death, and location of burial.  Deaths 

7 https://www.scchgs.org/onlineindexes/missioncem.html 
 

 

 

76 

are the county infirmary were noted as “S.C. County Hospital”, “Santa Clara County Hospital” 

and “County Hospital”.   Mission City Memorial Park had an active potter’s field from 1913-

1937 (Rehor and Beck 2015:7-43).   

 

Comparative Skeletal Samples 

 

As previously stated, there are only a small number of well-documented historical 

cemetery excavations.  Milwaukee County Institution Grounds (MCIG) and Alameda-Stone 

excavations served as the primary comparative samples.  MCIG and Alameda -Stone are two of 

the largest 19th and 20th century cemeteries excavated to date (aside from SCVMC).  

Additionally, their geographic, temporal, and cultural contexts are in part complimentary to 

SCVMC.  Both Alameda-Stone and MCIG have also been highly contextualized in both their 

archaeological and historic settings (Milligan 2010; Richards 1997; Goldstein 2012; Goldstein et 

al. 2012a, 2012b; Heilen and Sewell 2012; Heilen et al. 2012; Sewell et al. 2012). This presents a 

unique opportunity for the systematic analysis and comparison of three of the largest excavated 

historical cemeteries in the U.S.  To date, these cemeteries have not been compared to each 

other.  The Voegtly Cemetery will also be used as a comparative sample to include a cemetery 

with a vastly different context (community burial ground) and location (East Coast). See table 2 

for site summaries.  

 

Milwaukee County Institution Grounds  
 
 

 In 1991, 1992, and 2013 portions of the Milwaukee County Institution Grounds 

(Milwaukee, Wisconsin) cemetery were excavated.  This cemetery was in use from August 1882 

until July 1925 (Richards 1997; Richards and Kastell 1993) As results from the 2013 excavations 

are still forthcoming; data from the 1991 and 1992 excavations will be used.  The excavated 

 

77 

sections yielded a total of 1,649 burials.  1,061 were adult remains, and 588 were classified as 

subadult’s.  MCIG was established to provide a burial ground for not only Milwaukee’s various 

institutions, but members of the wider community that could not afford burial fees elsewhere, as 

well as unidentified individuals. 

Milligan’s (2010) dissertation examined pathological and nutritional conditions within a 

sub-sample of both the adult (n=491) and subadult (n=373) remains.   A majority of the subadult 

remains were less than 1 year of age (88.3%). The adult burials include 406 males, 57 females, 

and 28 indeterminate individuals. Milligan’s (2010) study looked at several factors related to 

nutritional stress and infectious disease and thus will serve as the main MCIG data set for this 

research project.  Specifically, the paleopathological analysis included the following: liner 

enamel hypoplasias, porotic hyperostosis, cribra orbitalia, long bone metrics, periosteal 

reactions, osteomyelitis, pathologies associated with tuberculosis and treponemal infection, and 

Time Period  No. of 

1882-1925 

Individuals 
1,649 

Source 

Milligan 2008, 
2010 

1860’s – 
1881 

1,386 

1833-1861 

724 

Heilen & Gray 
2010, Heilen 
2012 
Uberlaker & 
Jones 2003 

degenerative processes.   

Site Name 

Location 

Milwaukee, 
Wisconsin 

Milwaukee 
County 
Institution 
Grounds 
Alameda-Stone  Tucson, Arizona 

Voegtly  
Cemetery 

Pittsburgh, 
Pennsylvania 

Table 2. Historical Cemetery Comparative Sample. 

Alameda-Stone 
 
 

The Alameda-Stone cemetery was originally used by the community members of Tucson, 

Arizona from the early 1860’s through 1881.  It was excavated as part of the Joint Counts 

Complex Archaeological Project in 2006.  The project completely excavated 1,083 grave 

 

78 

features (representing 1,381 individuals), 736 post-cemetery period features, 3 prehistoric 

features, and several prehistoric and historical artifact scatters (Heilen 2012, Heilen and Gray 

2012).  The individuals buried there were of diverse cultural, religious, and biological 

backgrounds, making this cemetery a unique comparison site.  The archaeologists and biological 

anthropologists working on this project worked diligently to re-associate the cultural affinity of 

individual graves to fulfill burial agreements with potential area descendant groups.   

 

As reported in the 2010 technical report (Trask 2010), the Alameda-Stone cemetery 

sample included a total of 226 females, 314 males, and 846 indeterminate individuals.  The 

sample includes 730 adults, 650 subadults, and 6 individuals of indeterminate age. Factors 

assessed related to nutritional stress and paleopathology were as follows: linear enamel 

hypoplasia, periosteal reaction, osteomyelitis, pathologies associated with tuberculosis and 

treponemal disease, neoplasms, degenerative conditions, cribra orbitalia, and porotic 

hyperostosis (Leher et al. 2010; Lincoln-Baab and McClelland 2010). 

Voegtly 
 
 

The Voegtly Cemetery was in use from 1833 to 1861 and is associated with the Voegtly 

Evangelical Lutheran Church in Pittsburgh, Pennsylvania.  The proposed highway expansion 

was going to impact the cemetery, thus 724 burials were exhumed and analyzed by Doug 

Ubelaker and colleagues from the Smithsonian Institution (Ubelaker and Landers 2003:1). 

Extensive osteological analysis was performed on the sample including demographic and 

pathological examinations.  The pathological observations included trauma, periosteal lesions, 

lytic lesions, tuberculosis, degenerative joint disease, Harris lines, cribra orbitalia, and dental 

health including carious lesions and enamel hypoplasia’s.   The Voegtly sample included a total 

of 76 females and 95 males.  The sample includes 249 individuals under the age of 1, and an 

 

79 

additional 187 between the ages of 1-5.  The remaining individuals include 86 under the age of 

25, 130 between the ages of 25-50, and 34 individuals over the age of 50.   

Statistical Analysis  

In order to examine the relationships between age, sex, ancestry, pathology, and artifact 

categories statistical analysis, including frequencies and descriptive statistics were performed.  

Two principle methods employed include contingency tables using Chi-Square and 

Correspondence Analysis. 

Chi-square tests (with Fisher’s Exact tests or Yates Correlation as appropriate), were 

calculated to determine if there was an association between age, sex, ancestry, pathology, and 

artifact categories.  Because all 2x2 contingency tables had an N >40, if a cell had a value of <10 

a Yates Correction was also tabulated.   

Correspondence Analysis allows for more than two variable categories to be compared to 

each other. Correspondence analysis transforms contingency tables information into a two-

dimensional graphic used to visualize patterns, relative dispersion, and total variance.  

Correspondence analysis relies on contingency table profiles, masses, and chi-square distances 

(Hefner 2007). All correspondence analyses were conducted using R 3.2.3.  The specific R code 

was provided by Dr. Hefner.     

 

 

Spatial statistics  

A spatial autocorrelation average nearest neighbor test was performed in ArcGIS.  The 

average nearest neighbor test determines if the selected geospatial attribute is spatially clustered 

or dispersed. If the nearest neighbor ratio (index) is less than 1, the pattern exhibits clustering.  If 

the ratio is greater than 1, the trend is towards dispersion. When conducting a nearest neighbor 

 

80 

analysis the boundary effect must be taken into consideration.  The nearest neighbor statistic 

assumes that there is boundless space, so when a finite area is investigated that may sever 

potential connections between nearest neighbors, and the results are biased by raising the average 

distance between nearest neighbors (Carr 1984, Pinder et al. 1979:431). 

A midpoint was established for each burial as the average nearest neighbor test requires a 

single attribute for the spatial analysis.  Biological profile, coffin shape, and artifact data was 

added to the coffin GIS attribute table.  This allowed individual attributes to be selected and 

analyzed using the average nearest neighbor test.   

Summary 

The methods used in this study are based upon accepted measures of health and mortuary 

 
 

analysis as discussed in Chapter 2.  The goal of the comparative analysis is to examine indicators 

of health between samples using data types they have in common.  No two data sets are identical.  

The skeletal samples are impacted by deferring levels of preservation, research goals of the data 

collectors, and how the data was collected, categorized, and documented.  The statistical tests 

used attempt to limit the differences between data sets.  Similarly, it is acknowledged that 

archival data, such as the Santa Clara County Hospital patient intake register, are not infallible.  

Archival documents are subject to the inherent biases of their textual evidence and are often 

biased towards particular privileged groups.  The historical narrative created by the historical 

documents must be carefully considered.   

 
 

 

 

 

 

81 

Chapter 6: Results from VMC 

Introduction 

 

  This chapter addresses the Santa Clara Valley Medical Center historic-era cemetery 

(VMC), while chapter 7 addresses the results of comparisons with similar cemeteries and 

archival material.  The complete VMC skeletal sample was used. 

 

 

Skeletal Results 

This section presents the results of data constructed from skeletal analysis.  

Demography of Skeletal Sample 
 
  

The age and sex assessments considered multiple factors from several areas of the 

skeleton, with the number of indicators conditional on the completeness and preservations of the 

burial.  Of the total 1,004 individuals, 743 have sex assessments and 987 have estimations of age 

(493 of whom have specific age range estimations). The overall poor preservation seen 

throughout the cemetery hindered more detail assessments for many burials. The cemetery is 

overwhelming adult (see Table 3) and male (see Table 4). The lack of females (7%) and 

subadults (6%) presents unique challenges for demographic reconstruction and comparison. The 

493 individuals with specific age estimations are the focus of the demographic work.   

 

 
 
 

 

Age 
Sub-adult (<25) 
Adult (25-59) 
Older Adult (60+) 
Indeterminate 
Total 

Count 
63 
746 
168 
27 
1004 

Frequency 
6% 
74% 
17% 
3% 
100% 

Table 3. VMC Broad Age Category Distribution. 

82 

Sex 
Male 
Female 
Indeterminate 
Total 

Count 
720 
75 
209 
1004 

Frequency 
72% 
7% 
21% 
100% 

Table 4. VMC Broad Sex Category Distribution. 

  

Age 
 
Age categories were recorded as both fine and course levels of detail.  The data was originally 

recorded as infant (<1 year), subadult (1-20 years), young adult (20-35 years), adult (35-50 

years), older adult (50+ years), and indeterminate (see Table 5, Figure 11).  Due to the relatively 

few number of young individuals in the sample, and to make statistical analysis more straight 

forward, the age categories were coarsened into subadult (<25 years), adult (25-50 years), older 

adult (50+ years), and indeterminate (see Table 6, Figure 12). 

 

 

 

 

 

 

 

Age Fine 
Infant 
Subadult 
Young adult 
Adult 
Older adult 
Indeterminate 
Total 

Count 

13 
15 
35 
746 
168 
27 
1004 

Frequency 
1% 
1% 
3% 
74% 
17% 
3% 
100% 

Table 5. Age Categories Fine Typology. 

83 

Age - Fine Categories

800

700

600

500

400

300

200

100

0

Count

 

Infant

Subadult

Youngadult

Adult

Older adult

indterminate

Figure 11. Age categories by count. 

Age Course 

Sub-adult 

Adult 

Older Adult 

Indeterminate 

Count 

Frequency 

63 

746 

168 

27 

Total 
 

 

 

Table 6. Course Age Categories. 

1004 

6% 

74% 

17% 

3% 

100% 

84 

 

 

 

 

 

 

Figure 12. Coarse Age Categories. 

An overwhelming (91%) portion of the sample is comprised of individuals over the age 

of 20 (See Figure 13).  Since only approximately 35% of the total cemetery was excavated it is 

possible subadults existed within the cemetery but were segregated into a “babyland” that was 

not excavated.  Another possible explanation is that children were buried elsewhere, possibly 

cared for by the many Benevolence Societies in the area.  The death of a child is treated 

differently from adult deaths (Curl 1972; Mitford 1963; Sweeney 2014). There is a social stigma 

associated with being buried in a potter’s field, and children may have been spared this.  The 

demography of the Santa Clara Valley was also heavily skewed to adult males due to the large 

amount of immigrant and migrant workers in the area working in agriculture and canning. This 

data is also represented visually in the age colored-coded map in Figure 14.   

 

 

85 

VMC Age at Death

180
160
140
120
100
80
60
40
20
0

Sex 

0-1

1-5

6-10

11-15 16-20 21-25 26-30 31-35 36-40 41-45 46-50 50-inf

Figure 13. VMC Age at Death. 

N

 

Sex categories were recorded as fine, and course.  Fine categories are possible male, 

probable male, male, possible female, probable female, female, and indeterminate. These 

categories were coarsened to make statistical analysis more straightforward; the coarse 

categories are male, female, and indeterminate (see Table 7, Figure 15).    

Males comprised 72% of the total sample (90.5% of the sex-able sample when 

indeterminates are removed).  The lack of females is somewhat surprising, but not totally 

unexpected.  Similar to the lack of subadults, it’s possible that females are buried in a separate 

section of the cemetery that was not excavated.  It’s also probable that this is also an effect of the 

overall demographic proportions of the area at the time.  The large number of indeterminate 

individuals (21%) is largely due to preservation issues.  See Figure 16 for a map with sex color-

coded.   

 

86 

 

Figure 14. Map of burials colored coded by age categories. 

Sex 

Male 

Female 

Indeterminate 

Total 

Count 

Frequency 

720 

75 

209 

Table 7. Course Sex Counts. 

1004 

72% 

7% 

21% 

100% 

87 

 

 

Sex

Count

 

Male

Female

Indeterminate

Figure 15. Course Sex Counts. 

800
700
600
500
400
300
200
100
0

 

  

Ancestry 
 
 

A majority of the burials (n=589; 58.9%) did not have a conclusive ancestry assessment.  

Of the remaining 411 burials the most prevalent ancestry assessed was the combined 

Asian/Latino (n=251; 61%), followed by European (n=106; 24%) and African American (n=54; 

12.25%).  With only 41% of the cemetery having ancestry assessments, further comparative and 

descriptive statistics were not run. 

 

The males and females were compared using hazard models (see Table 8 for a and b 

Demographic Analysis 

 

values).  As seen in table 9, the log-likelihood difference was -179.016 , (though it should be 

noted that the program used for the log likelihood ratio is conservative and nearly always results 

in statistically significant differences) indicating that there are no significant differences between 

the male and female skeletal sample in terms of mortality and survivorship ratios.   

 

88 

 

Figure 16. Map of burials color-coded by course sex. 

Sex 

a1 

b1 

a3 

b3 

Female 

Male 

0.002361463 

1.01 

0.017429365 

0.027701375 

0.02982873 

1.0135133 

0.1711696 

0.02877075 

Table 8. a and b values males v. females. 

Sex 

X2 

Female v. Male  358.032 

df 

2 

Log likelihood 

p 

difference 

-179.016 

<0.0001 

Table 9. Log likelihood difference males v. females. 

The probability density, Figure 17, demonstrates that males and females in the sample 

 

 

have the same probability of being a specific age at death.  The probability of mortality (Figure 

 

89 

18), as well as probability of survivorship (Figure 19) is nearly identical between males and 

female. This may be a byproduct of the disparity between the number of males and females in 

the sample.   

 

0.1

0.08

0.06

0.04

0.02

0

0

 

 

Probability Density Function

Female
Male

20

40

Age

60

80

100

 

Figure 17. VMC Male v. Female Probability Density Function. 

90 

0.6

0.5

0.4

0.3

0.2

0.1

0

0

 

 

 

Mortality Hazard

Female

10

20

30

40

Age
50

60

70

80

90

100

 

Figure 18. VMC Male v. Female Mortality Hazard. 

Figure 19. VMC Male v. Female Survivorship. 

 

91 

Pathology 

Nonspecific Infection 
 

Periostitis and Osteomyelitis 

In the sample 42% of individuals (n=424) had observable non-specific infections (see 

Table 8). In terms of the sex frequency of non-specific infections among males it is 49% and for 

females is it 66%.  Localized infections involving 1-2 skeletal elements occurred in 57% of 

individuals with periostitis (n=240).  Systemic infections involving 3+ skeletal elements 

occurred in 43% of individuals with periostitis (n=184). For age the frequency of non-specific 

infections for subadults is 41%, adults 39%, and older adults 62.5%.  Included in the non-

specific infection totals are individuals with osteomyelitis and localized chronic non-specific 

infections.   

Osteomyelitis (see Figure 20 and 21) is an infectious condition that begins within a 

bone’s marrow spaces and primarily affects the endosteal surface. Osteomyelitis can result from 

a multitude of stressors including the introduction of pyogenic bacteria, viruses, fungi, and 

multicelled parasites (Mast and Horwitz 2002; Ortner 2003:181).  Osteomyelitis was 

documented in thirty-five individuals (males=25, females=3, and 7 individuals of indeterminate 

sex).  Localized chronic infectious such as sinusitis, mastoiditis (infection of the mastoid), or 

otitis media (ear infection) were documented in thirty-five individuals (males = 27, females = 7, 

and one juvenile of indeterminate sex).  Four of the individuals with mastoiditis had evidence of 

surgical intervention: three unilateral mastoidectomies and one bilateral mastoidectomy (see 

Figure 22).   

 

92 

Specific Infections 

Coccidioidomycosis (Valley Fever) 

     Two adult males were identified as having fungal infections consistent with 

Coccidioidomycosis, aka Valley Fever.  Coccidiodomycosis is found in warm, arid, desert-like 

regions in the Western Hemisphere.  This fungus is endemic to large portions of California 

(Yang et al. 2011), the desert Southwest, and parts of Mexico and South America (Brown et al. 

2013; Ortner 2003:326).   The organisms are found in alkaline, sandy soil, commonly 10-30 cm 

beneath the surface (Brown et al. 2013;186), and are thus routinely encountered by construction 

workers, agricultural workers and archaeologists. The bone foci may be solitary or at multiple 

sites with symmetrical involvement (Resnick and Niwayama 1995:2510). The bone lesions tend 

to be lytic and may be associated with periosteal reactions.  The most characteristic aspect of 

coccidioidomycosis lesions is that they are common in areas typically spared by other infections 

including bony prominences, small bones such as carpals, tarsals, and patella.  Destructive rib 

and vertebral body lesions as well as lesions of the skull may be present (Ortner 2003:326-327). 

Treponemal Infections 
 

Both acquired and congenital syphilis was observed in the sample.  Eleven individuals were 

diagnosed with tertiary syphilis (see Figure 23).  Ten of these individuals were adult males, and 

one was an older adult of indeterminate sex.  The diagnosis of tertiary syphilis included 

documenting saber shins, carries sicca, and nongranulomatous and gummatous inflammation of 

long bones (Ortner 2003).  

 

 

93 

Figure 20. Burial 685 overview, hematogenous osteomyelitis. 

 

 

 

94 

Figure 21. Close up of Burial 685 right femur hematogenous osteomyelitis. 

 

 

 

 

 

Figure 22. Burial 218 mastoidectomy, left mastoid.  

 

95 

Age 

Subadults   Adults  Older 

Indeterminate  Total 

Category 

Males 

Females 

21 

4 

Indeterminate  1 

Adults  

241 

95 

18 

30 

8 

2 

Total 

26 

289 

105 

n/a 

n/a 

4 

4 

357 

30 

37 

424 

Table 10. Non-specific infections by Age and Sex. 

Figure 23. Burial 732 tertiary syphilis with saber shins. 

 

 

 

96 

Congenital syphilis was identified in three individuals; two young adults and one subadult.  

Each diagnosis was based on the presence of severe enamel defects (see Figure 24) and the 

pathognomonic enamel defects known as Hutchinson’s Incisor and Mulberry Molar’s (Figure 

25) (Hillson 1996; Hillson et al. 1998).  Congenital syphilis is passed from infected mothers to 

the fetus in the womb (Ortner 2003).   

 

Figure 24. Burial 736 enamel defects and calculus, congenital syphilis.  Photo courtesy of 

Karen Gardner. 

 

 

97 

Figure 25. Burial 736 mulberry molar, congenital syphilis.  Photo courtesy of Karen 

Gardner.  

 

 

Tuberculosis 
 

Ten individuals were diagnosed with possible tuberculosis infections.  The individuals were 

all adult (males = 7, females = 2, and one adult of indeterminate sex. Each diagnosis was based 

on characteristic skeletal lytic lesions associated with tuberculosis, especially lesions of the 

vertebra and plural surface of the ribs (Ortner 2003).  Because skeletal lesions in patients with 

tuberculosis are rare, the number of individuals with active tuberculosis at the time of their death 

may have been much higher; especially given known rates of historical prevalence.  Poor 

preservation of the thoracic cavity may have also impacted the number of diagnoses.   

For each indicator of health the sample was examined for observable differences based on 

Age and Sex Differences 

 

age or sex.  Tables 11-14 summarize the totals for males and females respectively.  Pearson’s 

 

98 

chi-square was run to test the statistical significance of differences between the age and sex 

categories with significance set at the p<0.05 levels.   

  A significant difference does not exist between males and females for non-specific 

infections (c2 = 2.497, df= 1, p= 0.114062).  A significant difference does not exist between 

males and females for tuberculosis (c2 = 0.557, df= 1, Yates Correction p = 0.4553), 

Coccidioidomycosis (c2 = 0.209, cf = 1, Yates Correction p = 0.6477), and Tertiary Syphilis (c2  

= 0.233, df =1, Yates Correction p= 0.6293).  Congenital Syphilis was not examined by sex due 

to the subadult status of individuals with Congenital Syphilis.  

The sample was also examined for age-related differences between those classified as sub-

adults, adults, and older adults. The lack of individuals in specific categories (i.e. zero young 

adults with Coccidioidomycosis or only Adults having Tuberculosis) prevented Chi-squares tests  

Sex 

Male 

Female 

Present 

Absent 

357 

30 

363 

45 

Table 11. Non-specific infections by sex. 
Absent 
Sex 

Present 

Male 

Female 

7 

2 

713 

73 

Table 12. Tuberculosis by sex. 

Sex 

Male 

Female 

Present 

Absent 

2 

0 

718 

75 

Table 13. Coccidioidomycosis by sex. 

 

99 

Sex 

Male 

Female 

Present 

Absent 

10 

0 

710 

75 

Table 14. Tertiary Syphilis by sex. 

from being run. The only comparison that could be run is non-specific infections and there 

statistically significant difference between age categories (c2 = 31.6662, df = 2, p = < 0.00001), 

see table 15. 

Age 

Subadult 

Adult 

Older Adult 

Present 

Absent 

26 

289 

105 

37 

457 

63 

Table 15. Non-specific infections by age. 

 

Mortuary Archaeological Analysis 

Coffins 
 

All of the internments at VMC occurred in redwood coffins.  As a county institution the 

hospital was required to publicly advertise calls to bid on the contract for indigent burial 

services.  Though the undertakers contracted to perform these services varied over the years, 

each was required to provide the burial containers.  Redwood was a convenient and cost-

effective resource, with lumber mills present in the nearby Santa Cruz Mountains.  Coffin 

construction and dimensions were analyzed to explore shape and construction patterning within 

the cemetery.  Coffin shape and decoration reflects the prevailing mortuary trends and should 

 

100 

reflect changes in attitudes towards death.  Potter’s burials should reflect larger burial container 

trends, but retain only the most basic, least expensive, portions of prevailing mortuary beliefs.   

 

Length 

Coffin length was gathered from the burial excavation record forms.  The specificity of 

the measurement varied depending on who took the measurement, with some individuals 

rounding to the next ¼ inch, and others recorded to the third decimal place.  To standardize the 

measurements the recorded number rounded down if <.5, and up if >.5.  Coffin length that was 

noted to be disturbed, impacted by the backhoe, or highly damaged so as to potentially obscure 

the true coffin length was removed from the calculations.  The unit of measurement to inches, as 

is standard for historical site recording. Length ranged from 21-92 inches.  Length is also very 

close to a normal distribution (see Table 16, Figure 26).  

72.38446089 
Mean 
73 
Median 
72 
Mode 
Std dev 
5.93734184 
Table 16. Coffin Length. 

Figure 26. Coffin Length Counts, length in inches. 

 

 

101 

An average coffin length of 73 inches equates to roughly 6 feet long.  This is not 

unexpected as a six-foot length is a standard cut of milled lumber (Rangel 2016).  A range of 

variation exists; with the shortest coffins belong to subadults. All coffins less than 50 inches in 

length contained subadults, indicating that even in the potter’s field variation in coffin 

construction was performed for children.  This is logical, as using a larger burial container would 

not be an economical decision.     

Depth 

Coffin depth (height of the side board) was gathered from the burial record forms.  The 

measurements were rounded down if <.5 and up if >.5.  The unit of measurement was 

standardized to inches, and burials where true depth could not be determined were removed. 

Depth ranged from 1-22 inches (see Table 17, Figure 27).  

 

Mean 

Median 

Mode 

std dev 

6.75 

7 

7 

 Table 17. Coffin Depth. 

2.25 

 

102 

Figure 27. Coffin Depth Counts. 

 

The range of coffin depths may be a result of taphonomic processes, as well as overall 

coffin size.  Nearly all of the coffins were slightly to severely crushed from the pressure exerted 

from the parking lot above them.  However, the average depth was 6.75 inches, with the 

 

descriptive statistics approaching a normal distribution.   

Width 

Coffin width was gathered from the burial record forms.  The measurements were 

rounded down if <.5 and up if >.5.  The unit of measurement was standardized to inches, and 

removed burials noted to be damaged thus obscuring true maximum width.  Width measurements 

were taken at both the shoulder and foot regions of the coffin.  The widest measurement, which a 

majority of the time was the shoulder width, was selected as each coffin’s width measurement. 

Width ranged from 5-50 inches (see Table 18, Figure 28). 

Mean 
Median 
Mode 
Std dev 

17.04 
17 
17 
3.00 
 Table 18. Coffin Width. 

 

103 

Figure 28. Coffin Width Count. 

 
 

Coffin width, similar to the length appears to conform to a standardized size of a 1 ½ foot 

width at the shoulder, with the descriptive statistics conforming to a normal distribution.   

 

 

Shape 

  

The shape of the coffin was recorded as hexagonal (widest at the shoulders), rectangular 

(straight on all sides), tapered (trapezoidal), double, other, and indeterminate (see Table 20, 

Figure 21). It should be noted that double does not indicated two stacked burials (those were 

each recorded for individual coffin shape), but rather a hexagonal coffin inside a larger 

rectangular box. 

Hexagonal coffins comprised a majority of the sample (74%), followed by rectangular 

(15%), and tapered (5%).  This is not surprising, as hexagonal coffins were the most typical 

shape during this time period (Bell 1990; Coffin 1976).  See Figure 30 for a color-coded map of 

burials by coffin shape.   

 

 
 

 

104 

Coffin 
Shape 
Hexagonal 
Rectangular 
Tapered 
Double 
Other 
Ind 
Total 

Count 
745 
149 
53 
7 
6 
44 
1004 

Frequency 

74% 
15% 
5% 
1% 
1% 
4% 
100% 

Table 19. Coffin Shape Count & Frequency. 

 
 
 
 

 

 

Figure 29. Coffin Shape Counts. 

 

105 

Figure 30. Burial Map color coded by shape. 

 

 

 

 

 

 

 

106 

Grave Goods 

Clothing Related Artifacts 
 

Buttons 

 

Buttons were recorded by type (bone, ceramic, clay, cuprous, ferrous, indeterminate, 

plastic, Prosser, shell, wood, wool), and presence/absence per burial (see Figure 14).  Burials 

were also recorded as no buttons, one type of button present (see Figure 31 or 32), or multiple 

types of buttons present (see Table 20 and Figure 33). 

 

 
Burial with buttons 
Burials without buttons 
Burials with multiple types 
Burials with one type 

 
669 
335 
279 
390 

Table 20. Button Pattern Types by Burial Count. 

Figure 31. Total Number of Buttons by Button Material Type. 

 

 

 

107 

Figure 32. Count of Button Material Types in burials with a single type of button present. 

 

 

 

Prosser buttons were the most common button type overall (46%), followed by ferrous 

(31%) and shell (11%).  Just over half (n=390, or 54%) of the burials had only a single button 

type present.  They followed the overall trend with mostly Prosser (57%), followed by ferrous 

(19%), then shell (19%).  Burials with multiple buttons (n=279) contained 3 times the overall 

number of buttons (n=2229).  The burials with multiple button types exhibit a different overall 

button count pattern.  Ferrous buttons (n=884, 40%) outnumber Prosser (n=856, 38%).  It’s 

possible that these buttons are related to pants with multiple buttons closures. Ferrous buttons 

occur in 220 burials, and in 49 burials (22%) ferrous is the only button type.   

 

108 

Figure 33. Count of button material type in burials with multiple types of buttons. 

 

 

Other Clothing Fasteners 

The clothing fastener recorded on the excavation forms were assigned to 11 different 

categories (safety pin, suspender, buckle, rivet, collar stud, grommet, fastener, garter, hook and 

eye, clasp, corset stay; see Figure 34).  The most prevalent types of clothing fastener were safety 

pins (n=345 from 249 burials) followed by grommets (n=175 from 87 burials), rivets (n=143 

from 47 burials) and suspender claps (n=133 from 82 burials).   

Jewelry 
 

Seven jewelry categories were identified (ring, earring, charm, medal, pendant, locket, 

and brooch).  Rings were the most prevalent jewelry type with n=28 (from 24 burials, four 

individuals had a ring on each hand).  Overall jewelry was not a well-represented grave good 

 

109 

Figure 34. Clothing Fastener Count. 

  

 
type, which is not unexpected given the lower socio-economic status of the individuals buried at 

VMC (see Figure 35).  Of the 28 rings six were 14 or 18 carat gold wedding bands (see Figure 

36), two were silver, and the rest were plated or non-precious metal.  For example, the gold 

plated ring recovered from Burial 932 was stamped WL & CO.  W.L. & Co marketed low karat 

solid gold rings that “Look Like Gold. Sound Like Gold. Wear Like Gold” that were sold for as 

low as 25 cents (see Figure 37). The remaining rings were unadorned bands (n=6) and signet 

rings (n=4).   

Rings were recovered from burials of males (n=15), females (n=6) and individuals of 

indeterminate sex (n=4).  There is a statistically significant association with rings and sex (c2 = 

9.246, p= 0.00236).  With regards to age rings were only recovered from burials of adults (n=18) 

and older adults (n=7).  There is not a statistically significant relationship between rings and age 

(c2 = 1.5616, p= 0.211434).   

 

 

110 

Figure 35. Jewelry Count by Type. 

 

Figure 36. Burial 199 two gold rings with makers marks and engraving.  Ring 1 hall marks 
HA (Hyde Aston Jewelers)/18 (18k gold standard)/Anchor (Birmingham England Assay 

Office)/Face (Queen Victoria)/Y (1873). Ring 2 engraved initials I (or A)/D/B.   

 

 

111 

 

Figure 37.  Advertisement for W.L. & Co Rings (Chicago Dry Goods Reported 1900). 

Rings from Burial 932 highlighted by red rectangle. 

  Religious Artifacts 
 
 

Religious artifacts (rosary, crucifix, saint medal) were found in 38 burials (see Figure 38). 

Rosaries, Crucifixes and Saint Medals are common markers of Catholicism. Medals were only 

counted as religious is the preservations was good enough to detect religious symbols or writing.  

Twenty six percent of burials had multiple religious objects (n=10). Multiple religious objects 

 

112 

occurred in the following combinations: Two contained a rosary and a medal; One contained a 

rosary, second crucifix, and medal; Four contained rosary and a second crucifix; Two had a 

medal and crucifix combination; and one contained two medals.  

Figure 38 Religious Artifact Count. 

 

Religious artifacts were recovered from male (n=21), female (n=8), and an indeterminate 

sex (n=1) burials.  There is a statistically significant relationship between religious artifacts and 

sex (c2= 11.6075, p = 0.000657.  Religious artifacts were recovered from subadult (n=4), adult 

(n=27), and older adult (n=6) burials.  There is not a statistically significant relationship between 

religious artifacts and age (c2= 1.2141, p=0.544959). 

 

Rosary’s were present in 15 burials including 8 males, 6 females, and an unsexed 

subadult.  There is a statistically significant relationship between sex and rosary presence (c2= 

18.6329, p=0.000016).  Rosary’s were recovered from subadult (n=1), adult (n=12), and older 

adult (n=4) burials. There is not a statistically significant relationship between age and rosary 

presence (c2= 0.4876, p=0.783635).  

 

113 

 

Crucifixes not related to rosaries were present in 10 burials including 8 males and 2 

females.   There is not a statistically significant relationship between sex and crucifix presence 

(c2= 1.3233, p=0.24998). Crucifixes were recovered from adult (n=12) and older adult (n=1) 

burials and there is not a statistically significant relationship between age and crucifix presence 

(c2= 1.0042, p=0.316287). 

Religious medals were recovered from 18 burials including 8 males, 6 females, and 4 

unsexed subadults.  There is a statistically significant relationship between the presence of 

religious medals and sex (c2=18.6329, p=0.000016).  Religious medals were present in subadult 

(n=4), adult (n=13), and older adult (n=1) burials.  There is a statistically significant relationship 

(c2=8.5618, p=0.01383) between religious medals and age. 

 

The presence and absence of specific grave good patterns was used to segment the burial 

 

Burial Categories 

 

population into three categories: unknown individuals (no personal artifacts), hospital direct 

internments (presence of hospital clothing button pattern, see Figure 39), and community 

members (all other artifacts).  Community members are the most prevalent group (n=700, 70%), 

followed by unknown individuals (n=179, 17.9%) and hospital direct (n=121, 12.1%).   Note that 

only primary burials were examined for burial categories, thus burials from other contexts were 

not included, thus n=1000.  See Table 21 for sex distribution, and Table 22 for age distribution. 

There is no statistically significant relationship between sex (c2 = 1.3437, df = 1, p = 0.510762) 

or age (c2 = 4.8054, df = 3, p = 0.307855) and the burial categories.   

 

 

114 

Figure 39. Burial 832 Hospital Internment button pattern. Image courtesy of URS.  

 

 

Burial Category 

Community 

Hospital Direct 

Unknown 

Male 

Female 

505 

97 

118 

57 

7 

11 

Table 21. VMC Burial Categories by Sex. 

Burial Category 

Subadult  Adult 

Older Adult 

Indeterminate 

Community 

Hospital Direct 

Unknown 

49 

7 

6 

506 

94 

139 

126 

18 

28 

19 

2 

6 

Table 22. VMC Burial Categories by Age. 

 

 

The sample was also examined for burial category related differences for indicators of 

health (see Tables 23- 25).  Only non-specific infection shows a significant difference (c2 = 

6.3588, df = 2, p = 0.041611).  Other indicators of health did not show significant differences: 

Syphilis (c2 = 4.2036, df = 2, Yates Correction p = 0.254635); Tuberculosis (c2 = 0.1052, df = 2, 

 

115 

Yates Correction p = .7457); Coccidioidomycosis could not be compared because it only 

occurred in the community burial category. 

 

 

 

Burial Category 

Community 

Hospital Direct 

Unknown  

Present 

Absent 

289 

64 

71 

411 

57 

108 

Table 23. VMC Non-Specific Infections by Burial Category. 

Burial Category 

Present 

Absent 

Community 

Hospital Direct 

Unknown  

7 

3 

4 

693 

118 

175 

Table 24. VMC Syphilis by Burial Category. 

Burial Category 

Present 

Absent 

Community 

Hospital Direct 

9 

2 

691 

119 

Table 25. VMC Tuberculosis by Burial Category. 

 

 

An average nearest neighbor test was conducted for multiple variables to determine if any 

Spatial analysis  

 

geo-spatial patterns exist. The results are presented in Table 26. 

 

116 

Expected 

Mean 
Distance 

1.03 
3.51 
3.10 
3.92 
1.19 
2.49 
1.17 

Nearest 
Neighbor 

Ratio 
1.12 
1.11 
0.866 
0.84 
1.07 
0.97 
1.05 

z-score 
7.11 
1.86 
-2.05 
-2.38 
3.48 
-0.70 
2.98 

p-value 
0.000000 

0.063 
0.011 
0.01735 
0.000492 
0.4851 
0.0029 

  
All burials 
Females 
Males 
Subadults 
Adults 
Older Adults 
Hexagonal Coffin 
Rectangular 
Coffin 
Tapered Coffin 
Double Coffin 
Hospital Button 
Community  
Unknown 
 

Observed 

Mean 
Distance 

1.15 
3.90 
2.69 
3.29 
1.27 
2.42 
1.24 
2.03 

3.55 
16.13 
2.57 
1.32 
2.18 

 

2.57 
3.99 
8.69 
2.87 
1.23 
2.28 

 

0.79 
0.89 
1.85 
.091 
1.064 
0.95 

 

-4.85 
-1.51 
4.32 
-1.78 
3.26 
-1.2 

 

<0.001 
0.13 
<0.001 
0.074 

0.001117 
0.2303 

 

Table 26. Average Nearest Neighbor Results, significant bolded. 

 

If the nearest neighbor ratio (index) is less than 1, the pattern exhibits clustering.  If the 

ratio is greater than 1, the trend is towards dispersion. As expected with a planned historic 

cemetery, when all of the burials are considered they form a highly statistically significant 

regular pattern, with a nearest neighbor ratio of 1.12 (p<0.000000).  Females are dispersed 

(neared neighbor = 1.11, p=0.063) and male burials are clustered (nearest neighbor = 0.86, 

p=0.011).  However, since males comprise over 70% of the sample, the clustering may be a 

product of sample size.   

 

When age is examined subadult burials are clustered (nearest neighbor = 0.84, p = 

0.01735), adult burials are dispersed (nearest neighbor = 1.07, p = 0.000492), and older adult 

burials are random (nearest neighbor = .97, p = 0.4851).  See Figure 40 for subadult burial 

locations.  Burials of subadults are concentrated in the southern and northwest portions of the 

cemetery.  

 

117 

Hexagonal coffins are dispersed (nearest neighbor = 1.05, p=0.0029), while rectangular 

coffins (nearest neighbor = .79, p<0.001) and tapered coffins (nearest neighbor =.89, p=0.13) 

cluster, although only rectangular coffins reach statistical significance.    

With regards to burial categories the hospital direct burials do cluster (nearest neighbor = 

.091, p=0.074) see Figure 41, although slightly above the p=0.05 significance threshold.  The 

community member (nearest neighbor = 1.06, p = 0.001117) are dispersed.  Given that 

community members are the largest burial category (n=700), this may be a product of the sample 

size.  Unknown individuals (nearest neighbor = 0.95, p = 0.2303) are randomly dispersed.   

Comparing Coffin Shape with other variables  

 

 

In order to investigate any potential patterns among the coffin shape variables chi squared 

and correspondence analysis was conducted comparing coffin shape with coffin length, width, 

depth, age, sex, button patterns, and jewelry.   

Sex 

The chi-squared tests indicated that there was no statistically significant relationship 

between coffin shape and sex (Chi squared = 2.59, p=0.2739, Cramers V = 0.0584), see Figure 

42 and Table 27.  However, a two-way correspondence analysis revealed that males group with 

hexagonal coffins, and females with rectangular and tapered (see Figure 43, inertia = 0.0034), 

with 100% of the variation being explained by sex.     

Age 
 

Similar to sex, a simple chi-squared analysis did not reveal any statistically significant 

relationships between coffin shape and age (χ2 = 2.34, p= .67, Cramers V = 0.035), see Figure 44 

and Table 28. However, the correspondence analysis (inertia= 0.0022) revealed a relationship  

 

 

118 

Figure 40. Burials by age, Subadult burials (<25 years of age) are red. 

 

 

119 

 
Figure 41. Map showing hospital button category individuals, individuals with hospital 

button pattern in red. 

 

120 

Figure 42. Coffin Shape by Sex. 

  

Hexagonal  
Rectangular 
Tapered 

Male 
556 
97 
37 

Female 

50 
14 
5 

Table 27. Coffin Shape by Sex. 

 

 

Figure 43. Correspondence Analysis of Sex v. Coffin Shape. 

 

121 

 

  
Hexagonal 
Rectangular 
Tapered 

Figure 44. Coffin Shape by Age. 

Subadult  

45 
11 
3 

Adult 
548 
112 
43 

Table 28. Coffin Shape by Age. 

 

Older Adult 

134 
21 
7 

between rectangular and tapered coffin with subadults, and hexagonal coffins and adults/older 

adults (See Figure 45).   

 

At first glance there is little variation between the descriptive statistics (mean, media, 

Coffin Dimensions 

 

mode) for coffin length, width, or depth by coffin shape.  Most of the shapes follow a near 

normal distribution (See figures 46-48 and Tables 29-31).  The lack of size variation by shape 

may indicate that regardless of shape, specific coffin dimensions were being required to bury the 

indigent dead.   

 

 

122 

Figure 45. Correspondence Analysis of Coffin Shape by Course Age Group. 

 

 
 

 

123 

Figure 46. Coffin Length by Shape. 

 

Hexagonal 

Rectangular 

Coffin Length  
Mean 
Median 
Mode 

Table 29. Coffin Length Descriptive Statistics (length in inches). 

72.64 
73 
72 

72.39 
74 
75 

Tapered 
71.86 
72.5 
72 

Figure 47. Coffin Width by Shape. 

124 

 

 

 

Coffin Width 

Hexagonal 

Rectangular 

Mean 
Median 
Mode 
Table 30. Coffin width descriptive statistics (width in inches). 

15.89 
16 
16 

17.25 
17 
17 

Tapered 
16.04 
16 
16 

Figure 48. Coffin depth by shape. 

 

Coffin Depth 

Hexagonal 

Rectangular 

Tapered 

Mean 
Median 
Mode 
Table 31. Coffin depth descriptive statistics (depth in inches). 

6.93 
7 
6 

6.33 
6 
6 

6.38 
7 
7 

 

 

 

 

Coffin dimensions and shape coffin shape does not equate to temporal pattern as they 

occur in all sections of the cemetery.  The standardization of the size amongst the shapes perhaps 

suggests that specific dimensions were required for these burials.  The shape preference may 

have been determined by the specific funeral home that was subcontracted to handle indigent 

burials, which varied by year.   

 

125 

Artifacts  

Buttons 
 
 

Button types, and pattern variations were examined for differences between geospatial 

location, age, sex, button co-occurrence, and coffin shape patterns (Figure 49).   

 

 
 

Figure 49. Button patterns by coffin shape. 

 

Four distinct button patterns were identified; no buttons, a single type of button, multiple 

types of buttons, and the previously discussed hospital gown pattern, which were evenly 

represented by each, coffin type.  

Single Button Type Burials 
 
 

Single button type burials were examined for patterns with sex, age and coffin shape.  

With regards to coffin shape, correspondence analysis indicates that burials with a single button 

type are co-occurring with rectangular and tapered coffins, but burials without the single button 

 

126 

type correspond with hexagonal coffins (chi square = 1.325, inertia = 0.0014), with 100% of the 

variation being explained by presence/absence, see Figure 50.   

Figure 50. Burials with single button type Correspondence Analysis by Coffin Shape and 

pattern presence absence. 

 

 

 

A correspondence analysis examining single button type burials by sex and coffin shape 

(chi square = 3.28, intertia = 0.02) reveled that males with only one type of button as associated 

with tapered and rectangular coffins, while females are associated with hexagonal.  100% of the 

variation is explained by sex, see Figure 51.  

 

127 

 

Figure 51. Burials with single button type correspondence by sex and coffin shape. 

 
 

A correspondence analysis was also performed examining single button type burials by 

age and coffin shape (chi square = 3.848, inertia = 0.0118).  Subadults corresponded with 

rectangular coffins, while adults and older adults were both associated with tapered and 

hexagonal coffins, see Figure 52.   

 

128 

 

Figure 52. Burials with single button type correspondence analysis by age and coffin shape. 
 

Multiple Button Burials 
 
 

There are 279 burials with multiple types of buttons (M = 218, F = 13).  A 

correspondence analysis was performed (chi square = 2.39, intertia = 0.018), indicating that 

hexagonal coffins are associated with both males and females, but males are more likely to be 

associated with rectangular coffins, and females with tapered, see Figure 53.  

 

129 

 
Figure 53. Burials with multiple button types correspondence analysis by sex and coffin 

shape. 

All Button Categories 
 
 

The three button categories (no buttons, multiple styles of button, single types of button), 

were examined to see if any sex-linked patterns existed, see Table 32. 

 

Male 
Female 

No Button 

Multiple Button 
Types 
218 
13 

212 
36 
Table 32. Button categories by sex count. 

Single Button Types 

291 
27 

 

130 

A correspondence analysis (Chi square = 12.65, p= 0.003, Cramer’s V = 0.1207, inertia = 

0.0159) indicated that male is associated with multiple button types and single button types, 

while females are more likely to have no buttons, see Figure 54.   

Figure 54. Button categories by sex. 

 

 

Button Co-Occurrence 
 
 

Buttons within the multiple button type burials were examined for type co-occurrence.  A 

multiple correspondence analysis was performed (see Table 33, Figure 55). Button types with a 

positive co-occurrence include; cuprous/clay/ferrous, Prosser/clay/ferrous, Prosser/bone, and 

ferrous/cuprous.   

 

131 

Table 33. Button co-occurrence correspondence analysis transformed variables. 

 

 

Figure 55. Button type correspondence analysis. 

Religious Artifacts 
 
 

 Correspondence analysis (chi squared = 2.054, inertia = 0.079) indicates that males with 

religious artifacts are associated with tapered and hexagonal coffins, while females are 

associated with rectangular coffins, see Figure 56.   

 

 

132 

Figure 56. Burials with Religious Artifacts by Sex and Coffin Shape. 

 

 

 
 

Summary 

This analysis clarified several major trends in the SCVMC cemetery.  First the cemetery 

is comprised of mostly adult males, but this is not surprising considering the historical context of 

the area.  Males and females faced the same mortality and survivorship rates. The lack of 

subadults, specifically younger individuals under the age of 10, indicates that the subadults are 

either in an unexcavated portion of the cemetery or were buried elsewhere.  Of the individuals 

assessable for ancestry, Asian/Latino is the most prevalent category. 

 

133 

 

Overall, the sample shows evidence for specific and non-specific disease.  The high rates 

of non-specific infections, including localized and systemic, suggest that many individuals 

interred in the cemetery were afflicted with chronic, acute infections.  The low rates of 

tuberculosis and syphilis may be due to issues of preservation and low rates of skeletal 

involvement in disease expression.   

Coffin size appears to be standardized to 6 feet by 1 ½ feet, no matter what the coffin 

shape was.  Females correspond with tapered and rectangular coffins, while males are more 

closely associated with hexagonal.  However, even though tapered and rectangular coffins 

cluster, females as a whole do not.  Subadults correspond with rectangular coffins, while adults 

and older adults are more closely grouped with the hexagonal and tapered.  The presence and 

absence of buttons was not associated with a specific coffin shape or age range, but females were 

more likely to not have any buttons.  Males were more likely to have multiple buttons types, and 

single button types.  Religious artifacts were all related to Catholicism, were found in burials of 

both sexes and all ages but did not cluster spatially.  Grave goods were used to segment the 

burial population into three categories: community members, unknown individuals, and hospital 

direct interments.  A majority of burials are community members (70%) with a wider variety of 

personal grave goods than the hospital direct internments (12.1%), or unknown individuals 

(17.9%).  

 

The next chapter, chapter 7, will examine how the VMC burials compare to the 

historical record and similar skeletal samples.  A discussion of the relative health of the VMC 

sample is included in the next chapter.  

 

 

 

134 

Chapter 7: Comparative Studies Results 

 

Introduction 

 

 

The previous chapter examined the results of analysis of the skeletal sample from VMC.  

The following chapter compares the results from Chapter 6 with the historical record and other 

similar skeletal samples.  These skeletal samples represent similar times periods, contexts, or 

regional locations as VMC.   

 

Comparing with historical records  

 

Santa Clara Infirmary Death Record 
 

The Hospital Death Records Volume 5, April 27th, 1925-December 21st ,1933, contains 

detailed accounts of the name, age, marital status, nativity, cause of death, date of death, date of 

burial, and name of the funeral home used (Figure 57) of individuals that died at the Santa Clara 

County Infirmary.  Additionally, individuals that were buried by the county are noted. Although 

this record does not include individuals buried within the SCVMC cemetery it is the best 

available primary document with which to begin to understand the larger death related trends at 

the hospital during this time period.   

Although the hospital deaths are comprised overwhelmingly of older adults (53%), 

infants (12%) and juveniles (10%) make up nearly a quarter of all deaths (see Table 34).  

Therefore, a lack of young individuals being treated (and dying) at the hospital can be ruled out.  

The large number of adult individuals in the cemetery is also in line with the hospital deaths. 

Examining all of the hospital deaths provides a wider lens into the deaths of Santa Clara County 

poor, as this data includes individuals that could afford private burials.  Although the hospital 

 

135 

was solely for individuals needing financial and medical aid, not all socio-economically 

disadvantaged individuals are the same.  Therefore, it is also necessary to compare the 

Figure 57. Hospital Death Records Volume 5 Page 44. Santa Clara County Archives 
Collection 2008-013 Medical Examiners-Coroner’s Office Records Box 8 Volume 5. 

 

Age Category 

Infant (<1) 

Juvenile (1-20) 

Young Adult (20-35) 

Adult (35-50) 

Older Adult (50+) 

Count 

376  

295  

298  

456  

1631 

Frequency 

 12% 

10% 

 10% 

 15% 

53% 

Table 34. VMC All Hospital Deaths Age at death distribution. 

 

 

136 

VMC skeletal data specifically with hospital deaths that received county burials versus those that 

did not (see Tables 35 and 36).    

 

County (48%) and private (55%) burials at the hospital are comprised mostly of older 

adults which is to be expected based on the other data sets.   However, surprisingly 27% of 

county burials are infants versus only 8.5% of private burials.  What might account for this 

disparity between the infant deaths receiving county burials (27%) and the infant burials 

recovered during excavation (1%)?  See Figure 58. The age of infants is recorded in greater 

details than adults, with the months and sometimes minutes of life noted.  Of the infant county 

burials, 68% (115 out of 170) are individuals that are noted as stillbirths, or neonatal deaths that 

lived less than 1 month.  The stigma surrounding early neonatal death constitutes a unique social 

variable compared to other death age categories.  The death of a child is treated differently from 

adult deaths (Curl 1972; Mitford 1963; Sweeney 2014), and stillbirths are treated differently 

from other infant deaths. The high number of county stillbirth burials may be related to the 

prohibition of unbaptized stillbirths being buried in consecrated ground.  However, the lack of 

infant burials at VMC (see Figure 58 and 59) may indicate that stillbirth or not, child burials are 

treated differently, and they may have been buried at a more formal burial ground. In terms of 

sex the county burials have a more similar male to female ration to VMC than the private burials 

(see Table 37).  There is a statistically significant difference (c2 = 225.1909, df = 2, p < 

0.00001).   

 

 

 

 

 

137 

Age Category 

Infant (<1) 

Juvenile (1-20) 

Young Adult (20-35) 

Adult (35-50) 

Older Adult (50+) 

Count 

170 

45 

51 

63 

300 

Frequency 

 27% 

7% 

 8% 

 10% 

48% 

Table 35. County Hospital Deaths county burials age at death distribution.  

Figure 58. Age-at-death distribution of VMC and county burial hospital deaths. 

 

138 

 

 

 

 

 

 

 

Age Category 

Infant (<1) 

Juvenile (1-20) 

Young Adult (20-35) 

Adult (35-50) 

Older Adult (50+) 

Count 

206 

250 

247 

393 

1331 

Frequency 

 8.5% 

10.3% 

 10.2% 

 16% 

55% 

Table 36. County Hospital Death private burial age at death distribution. 

 

Figure 59. Hospital private burials and VMC age at death distribution. 

 

 

 

Sample 

VMC 

Male 

720 (90%) 

Hospital deaths private burial  1522 (64%) 

Hospital deaths county burial  454 (79%) 

Female 

75 (10%) 

854 (36%) 

119 (21%) 

Table 37. Sex distribution of VMC, and Hospital Deaths. 

 

139 

The categorical age and sex data seem to indicate that the VMC burials represent a 

different subset of the overall county burials and hospital deaths.  Employing demographic 

hazard modeling helps to illustrate this fact (Table 38).  The VMC skeletal sample was compared 

to the hospital deaths receiving county burials. 

Sample 

VMC 

α1 

β1 

α3 

β3 

0.2205644 

1.18344488 

0.0005764 

0.10841117 

County Burials 

55.98467287 

178.7523891626  0.002066865 

0.050613834 

Table 38. α1, β1, α3, and β3 parameters for VMC and county burials. 

 

The hazard models indicate that there is a significant difference between VMC and the 

hospital deaths with county burials (c2 =393.1268, df = 2, loglikelihood difference = -196.5634, 

p= <0.0001). The large number of subadult deaths in the hospital county burial population skews 

the mortality hazard (Figure 60).   

 

 

140 

 

Figure 60. Probability density function of VMC and Hospital Deaths with county burials. 

 

The difference in the large subadult population in the hospital deaths skews the mortality 

hazard (see figure 3).  Additionally, the comparison of osteological age estimations, which are by 

nature broad, to actual age at death presents another explanation for some of the variation 

between all hospital deaths and the SCVMC cemetery. The demographic modeling also 

illustrates that SCVMC is different from the county burials (see figure 60), supporting the 

possibility that the SCVMC burials represent a different subpopulation of county burials.  

The probability of mortality (see Figure 61) is different between the two samples.  At 

VMC the probability of mortality rises dramatically after age 45, while the probability of 

mortality among the hospital deaths with county burials, past infancy, doesn’t begin to rise until 

age 70.  The vast difference in these ages is likely a result of differences in the data.  Aging older 

individuals in osteology is difficult, and a with the VMC sample age specific estimations are cut 

 

141 

off at 50+.  The county hospital death register records actual, specific age at death.  Therefore 

there are many individuals with precise ages well past 50.  The oldest individuals in the county 

hospital death register that received county burials are 94 years old (Arthur Bulman, date of 

death September 9th, 1925 and Ramona Hernandez, date of death February 1st, 1931).  

 

Figure 61. Mortality hazard for VMC and Hospital deaths with county burials. 

 

The probability of surviving to the next age interval can be seen in Figure 62. 

Survivorship declines dramatically at VMC at approximately age 35, while the survivorship 

declined for hospital deaths with county burials drop immediately.  However, both groups 

approach a 10% probability of surviving to the next age interval just before age 60.  The 

disparity between survivorship between the two groups may be related to the type of data used: 

skeletal v. death records. 

 

 

 

142 

Figure 62. Survivorship of VMC and Hospital Deaths with county burials. 

 

 

Nativity 
 

According to the hospital ledger, for county burials 63% were born in the United States 

and 35% were foreign born (see table 6). It may be possible to infer general ancestry based on 

last name that would not work for married females and thus was not conducted. Interestingly 240 

individuals (59% of individuals born in the U.S.) were born in California.  This is undoubtedly a 

byproduct of the date of the death ledger (1925-1933).  California was not officially a state until 

1850, and the oldest individual with a California nativity was born in 1849.  Additionally, by this 

time period many first generation born individuals would have U.S. nativity locations.  

Therefore, the foreign-born nativity (see table 39) highlights only a fraction of the total possible 

ancestral diversity. If earlier ledgers were available, the nativity would surely be slightly 

different.   

 

143 

Foreign born individuals (n=211) were documented from 35 countries (see table 40).  The 

status of places the countries was considered at the time of birth of the individual. This is why 

Hawaii or Prince Edward Island are listed as their own countries, as they were incorporated into 

larger territories at a later date.  The largest group of individuals (n=40; 19%) are from Mexico, 

followed by individuals from China (n=18; 8.5%).  When viewed from larger geographic regions 

(see Table 41), Europe is the most prevalent region with 57% of foreign-born individuals. 

 

 

Category 

Count 

Frequency 

United States 

Foreign Born 

Unknown 

403 

211 

22 

63% 

33% 

4% 

Table 39. Hospital Ledger County Burial Nativity. 

Health 
 
 
The  top causes of death from 1925-1933 (see Table 42) per the Center for Disease 

Control (CDC) were tabulated into thirteen categories: diseases of the heart, pneumonia and 

influenza, nephritis, cancer and other malignant tumors, intercranial lesions of vascular origin, 

tuberculosis, accidents excluding motor vehicle, diarrhea/enteritis/and ulceration of intestines,  

 

 

 

 

 

 

 

144 

Nativity 
Mexico 
China 
Italy 
Germany 
Philippines 
Ireland 
Denmark 
England 
France 
Switzerland 
Canada 
Portugal 
Austria 
Scotland 
Spain 
Sweden 
Australia 
Russia 
Holland 
Hungary 
Nova Scotia 
Azores Islands 
Bohemia 
Central America 
Czechoslovakia 
Finland 
Hawaii 
Luxenberg 
New Zealand 
Norway 
Prince Edward Island 
Porto Rico 
Slavonia 
South Sea Island (Fiji) 
Wales 

N 
40 
18 
18 
16 
16 
14 
9 
9 
7 
7 
6 
6 
5 
5 
5 
4 
3 
3 
2 
2 
2 
1 
1 
1 
1 
1 
1 
1 
1 
1 
1 
1 
1 
1 
1 

Table 40. Foreign born county burial nativity by country. 

 

 
 
 
 
 
 

 

145 

Region 

Count 

Frequency 

North America 

Central America 

South America 

Europe 

Asia 

Africa 

Australia  

9 

42 

0 

120 

37 

0 

3 

4% 

20% 

0% 

57% 

17.5% 

0% 

1.5% 

Table 41. Foreign born county burials by larger geographic region. 

 

premature birth, syphilis, motor vehicle accidents, diabetes, and other (causes of death not 

included in the top CDC list).  All county burials in the volume 5 death register were coded 

based on the listed cause of death to correspond with the CDC categories (see Table 43).  

Diseases of the heart (20%) is the most prevalent cause of death among the county burials (Table 

43).  Heart disease is a very broad category and thus encompasses a number of pathological 

conditions.  An additional issue to consider is the nature of cause of death reporting.  The 

immediate cause of death that is listed on death certificates or death registers is the “…disease, 

injury, or complication that directly precedes death” (Kircher and Anderson 1989). Thus, heart 

failure can be precipitated by numerous pathological conditions.    

There are some stark differences with the second and third highest causes of death when 

compared with the CDC numbers.  Tuberculosis (16%) is the second highest cause of death 

amongst county burials but remains the 6th leading cause of death between 1925-1933  

 

 

146 

1927 
“” 

“” 

Cancer 
and other 
malignant 
tumors 
Nephritis 

“” 

“” 
“” 

“” 

“” 

1928  1929 
“” 

“” 

1930  1931  1932 
“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

“” 

Intercranial 
lesions of 
vascular 
origin 
Nephritis 

“” 
“” 

“” 
“” 

“” 
“” 

“” 
“” 

“” 
“” 

“” 

“” 

“” 

“” 

“” 

“” 

Motor 
vehicle 
accidents 

“” 

“” 

“” 

1933 
“” 

Cancer 
and other 
malignant 
tumors 
Pneumonia 
and 
influenza 
 
“” 
 

“” 

“” 
“” 

“” 

“” 

1925 
Disease of 
the heart 
Pneumonia 
and 
influenza 
 
Nephritis 

1926 
‘’’ 

“” 

“” 

“” 

“” 

Cancer and 
other 
malignant 
tumors 
Intercranial 
lesions of 
vascular 
origin 
Tuberculosis  “” 
Accidents 
“” 
excluding 
motor 
vehicle 
Diarrhea, 
enteritis, and 
ulceration of 
intestines 
Premature 
birth 

Premature 
birth 

Diarrhea, 
enteritis, 
and 
ulceration 
of 
intestines 
Motor 
vehicle 
accidents 

Syphilis 

“” 

“” 

“” 

“” 

Diabetes 
mellitus 

“” 

Diarrhea, 
enteritis, 
and 
ulceration 
of 
intestines 

Table 42. Top 10 causes of death nationwide. “”” indicates that cause of death ranking 

matches the previous year.  Data source: 

https://www.cdc.gov/nchs/data/dvs/lead1900_98.pdf. 

  

 

 

 

 

147 

Number afflicted 
169 
129 
124 
103 
55 

41 

33 

21 

19 

Percentage 
20% 
16% 
15% 
12% 
6% 

5% 

4% 

2.5% 

2% 

Cause of Death 
Disease of the heart 
Tuberculosis 
Premature birth 
Pneumonia and influenza 
Cancer and other malignant 
tumors 
Nephritis 

Diarrhea, enteritis, and 
ulceration of intestines 
Intercranial lesions of 
vascular origins 
Accidents (non-motor 
vehicle) 
Syphilis 
Motor vehicle accident 
Diabetes 
Other (Misc.) 

15 
2 
2 
116 

2% 
.3% 
.3% 
14% 

Table 43. Hospital Death Register causes of death by CDC categories for county burials. 

 
nationwide per the CDC data.  This also indicates that amongst the VMC skeletal sample 

tuberculosis rates are under-represented, likely hampered by both preservation issues and the 

nature of skeletal tuberculosis expression.  Premature birth (15%) is the third highest cause of 

death amongst county burials but nation-wide it never reached higher than the 8th leading cause 

of death during these years.   

Infectious Disease 
 

Forty five percent (n=287) of the county burials cause of death was an infectious process 

(see Figure 63).  These diseases include infectious processes that can impact the skeleton, such 

as tuberculosis and syphilis.  A comparison between the reported infectious causes of death in 

the register and non-specific infections including tuberculosis and syphilis in the VMC skeletal 

sample was conducted. 

 

148 

 

Figure 63. Number of individuals with an infectious cause of death from the hospital death 

register. 

 
 

In the VMC skeletal sample 452 individuals (45%) were diagnosed with non-specific 

infections (n=424), syphilis (n=14) or tuberculosis (n=10).  The resulting chi-square (c2 = 

0.0018, df = 1) was not significant (p=.066511).   

 

 

Comparative Samples 

Demography  
 

A demographic analysis employing various Siler and Gompertz mortality models, as well 

as correspondence and transition analysis was used to compare the osteological age-at-death 

assessments of the 493 SCVMC individuals with specific age estimations, to other historic 

samples. These comparative samples were selected due to their date, location, or context (see 

Table 44). 

 

 

149 

Site 
Mission 
City 
Memorial 
Park 

Alameda-
Stone 

Location 

Date 

Type 

N 

Source 

San Jose, CA 

1913-1937  Pauper 

1,097 

www.scchgs.org/ 

Tucson, AZ 

1860s-1881  Community  1,386 

Trask 2010 

Pittsburgh, PA  1833-1861  Community  724 

Voegtly 
Milwauke
e County 
Institution 
Ground  Milwaukee, WI  1882-1925  Pauper 

Table 44. Comparative Samples. 

1,649 

Ubelaker & Jones 
2003 

Milligan et al. 2008, 
Milligan 2010 

 

 

 
A mid-point was taken for each age estimation (see Table 45). For cemeteries where only 

broad categories were present, i.e. Young Adult 20-35, a mid-point was taken for that category. 

Each site had a Hazard Function, Gompertz Hazard, and Siler Hazard run in R using Lyle 

Konigsberg’s hazard model code (available here: http://konig.la.utk.edu/). The output α1, β1, α3, 

and β3 parameters (see table 46) were then input into Nick Herrmann’s paleodemographic 

modeling program to compare each site. The parameters were graphed using their respective 

models. The log likelihood ratio and chi-square test of the individual α and β parameters were 

estimated in the MLE computer program (Holman 2001, see Table 47).  Note that the log 

likelihood ration program is very conservative, and typically results in a significant result. The 

similarities and differences between SCVMC and each of the sites were examined in an effort to 

identify similar sites to SCVMC.  

 

 

 

 

150 

Sample 

VMC 

Mission 
City 
Memorial 
Park 
Milwaukee 
County 
Institution 
Ground 
Alameda 
Stone 
Sections 1 
& 2 
Alameda 
Stone 
Sections 
3,4,5 
Voegtly  

0-1 

5 

1-5  5-
10 
2 

6 

152  25 

11 

10-
15 
4 

11 

15-
20 
12 

16 

20-
25 
14 

30 

25-
30 
20 

25 

30-
35 
26 

28 

35-
40 
64 

45 

45-
40-
45 
50 
131  55 

50-
infinity 
134 

48 

59 

647 

346  20 

0 

10 

0 

5 

7 

0 

0 

3 

0 

0 

74 

0 

61 

0 

356  0 

168  0 

33 

0 

196  0 

0 

0 

0 

320  0 

97 

60 

0 

8 

292  0 

73 

249  187  42 

17 

14 

13 

27 

34 

25 

30 

14 

34 

Table 45. Comparative sites age estimation midpoint counts. 

Sample 

VMC 

Mission City 
Memorial Park 
Milwaukee 
County 
Institution 
Ground 
Alameda Stone 
Sections 1 & 2 
Alameda Stone 
Sections 3,4,5 
Voegtly  

 

 

 

α1 

β1 

α3 

β3 

0.2205644 

1.18344488 

0.0005764 

0.10841117 

0.31161008 

1.9349520359 

0.00076708 

0.6649949 

0.331610079 

1.9349520359 

0.000767081 

0.066499494 

0.07631628 

0.986144957 

0.00339331 

0.08802352 

0.32785313 

0.634082397 

0.00678635 

0.0601861 

0.31875885 

0.6703823 

0.25720704 

-0.6682745 

Table 46. Sample α1, β1, α3, and β3 parameters. 

151 

Sample 

Comparison 

VMC v. Mission 
City Memorial Park 
VMC v. 
Milwaukee County 
Institution Ground 
VMC v. Alameda 
Stone Sections 1 & 
2 
VMC v. Alameda 
stone Sections 3,4,5 
VMC v. Voegtly 

312.216 

324.896 

39.2706 

358.032 

789.02 

2 

2 

2 

2 

2 

c2 

df 

Log Likelihood 

P 

Difference 

-156.081 

-162.448 

-19.6353 

-179.016 

-391.51 

<0.0001 

<0.0001 

<0.0001 

<0.0001 

<0.0001 

Table 47. Statistical results for demographic comparisons between cemetery samples.  

Mission City Memorial Park 
 
 

The age at death information from Mission City Memorial Park (MCMP) was 

extrapolated from information recorded on headstones, and thus represents the specific age at 

death of those individuals.  In order to compare this data to the VMC skeletal age ranges, the 

MCMP numbers were also normalized into the mid-point age range categories (see Figure 64).   

 

Though similar, there are differences between the demographic profile of SCVMC and 

MCMP.  The population that both samples derived for should be the same during life 

(individuals that lived and died in Santa Clara County that received county funded burials), so 

the differences may stem from issues comparing osteological with historic data, or differential 

burial practices.  The MCMP sample has a large number of infants, specifically still births and 

individuals that died shortly after (n=152; 14%) compared to VMC (n=5; 1%).  The MCMP data, 

as well as the County Hospital Death Register (post 1925), demonstrate that infant deaths were 

occurring at the hospital.  The lack of infant burials at VMC suggests that infant burials were 

treated differently, either by being segregated into a different portion of the cemetery that was 

 

152 

not excavated, or that infants were buried elsewhere (like MCMP). Both burial populations are 

dominated by older individuals. The MCMP sample has a larger number of individuals over the 

age of 50 (n= 647; 59%) compared to VMC (n=154; 31%), though the over 50 age category is 

the largest individual age category at VMC.  This corresponds to other historic demographic data 

regarding the older age structure of Santa Clara County.   

Figure 64. Age at Death results for VMC and MCMP. 

 

 

153 

. 

 

Figure 65. Probability density function for VMC and MCMP. 

The hazard models indicate that there is a significant difference between VMC and 

 

MCMP regarding mortality and survivorship.  The probability density (Figure 65) demonstrates 

that while individuals at MCMP have a higher probability of dying at birth, that the overall 

mortality of individuals buried at VMC faced a higher probability of dying around the age of 50 

than individuals from MCMP whose probability of dying (after infancy) is highest at around age 

70.   

 

The probability of mortality (see Figure 66) is also different between the two samples.  

This may be a byproduct of issues in providing specific age estimates in skeletal samples over 

the age of 50-60 and the more detailed age at death data from the MCMP headstones.  At VMC 

the probability of mortality rises dramatically after age 40, while the probability of mortality at 

MCMP does not rise until after age 60.   

 

154 

 

Similar to the mortality hazard, the probability of surviving to the next age interval (see 

Figure 67) is lower for individuals from VMC than MCMP. Survivorship declines dramatically 

at VMC at approximately age 35, while the survivorship decline at MCMP does not begin until 

approximately age 50.  By the age of 55, individuals at VMC have less than a 10% probability of 

surviving to the next age interval.  The MCMP samples does not face a less than 10% probability 

of surviving until age 80.  The disparity between survivorship between the two groups may be 

related to the type of data used (skeletal v. headstones) or could be indicative of risk differences 

between the samples.  

 

 
 

 

Figure 66. Mortality Hazard of VMC and MCMP. 

 

155 

 

Figure 67. Survivorship VMC and MCMP. 

There is a statistically significant relationship between sex (c2= 77.5888, df = 1, p 

 

<0.00001), see Table 48.   

 

 

 

Sample 
VMC 
MCMP 

Male 
720 
464 

Female 
75 
173 

Table 48. Individuals by Sex at VMC and MCMP. 

Alameda Stone 
 
 

During the course of excavation and analysis at Alameda Stone the cemetery was divided 

into five areas (designated 1-5).  With the exception of the military section (area 1) the divisions 

were mainly arbitrary.  Cemetery areas 1 and 2 are the southern portion of the cemetery, while 

areas 3-5 are the northern portion of the cemetery. Section 2 was predominantly male (69%) and 

Euroamerican or Hispanic.  This disproportionate sex ratio suggested that a recent migrant 

 

156 

population was interred in this area (Trask 2010:372).  Cemetery area 3 comprises the bulk of the 

civilian section with over half of the total individuals recovered during the project.  This section 

has an equal distribution of males and females that were primarily young to middle age adults, 

however there is also a larger number of fetal and infant remains (Trask 2010:373).  Cemetery 

area 4 is highly disturbed with a larger number of indeterminately sexed remains. Area 4 has a 

large number of individuals under the age of 2 (Trask 2010:373).  Cemetery area 5 is the smallest 

with only 32 individuals.  There is an even male to female ration, but the area is comprised of 

young adults and individuals less than 12 years old (90%) (Trask 2010:373-374). The southern 

portion of the cemetery (areas 1-2) is primarily composed of young to middle-aged adult males, 

with a lower number of young children and females.  The northern portion of the cemetery (areas 

3-5) is more diverse in regard to age, sex, and biological affinity when compared to the southern 

portion. Therefore for the comparisons to VMC the cemetery areas at Alameda Stone were 

condensed into areas 1 & 2, and areas 3-5. 

Alameda Stone Sections 1-2 
 

 

The overall age structure of sections 1 and 2 from Alameda stone closely 

resembles the age structure at VMC (see Figure 68).  There is a noted lack of subadults, and a 

majority of individuals in sections 1-2 are adult males.  VMC has a larger proportion of older 

adults over the age of 50 (n=154; 31%), while Alameda sections 1-2 is comprised mainly of 

young to middle aged adults aged 25-45 (n=121; 82%).   

The hazard models indicate that there is a significant difference between VMC and 

Alameda Stone sections 1-2 regarding mortality and survivorship.  The probability density 

(Figure 69) demonstrates that individuals interred at Alameda Stone section 1-2 faced a higher 

 

157 

probability of dying younger than those interred at VMC.  Alameda Stone section 1-2’s highest 

probability begins at around age 35, while VMC’s occurs at approximately age 50.  

 

 
 

 

 

 

Figure 68. Age at death structure of VMC and Alameda Stone sections 1-2.   

 

Figure 69. Probability Density Function VMC and Alameda Stone sections 1-2.  

 

158 

The probability of mortality (see Figure 70) is slightly different between the two samples.  

At VMC the probability of mortality rises dramatically after age 45, while the probability of 

mortality at Alameda Stone section 1-2 is slightly earlier, rising around age 35.  

Similar to the mortality hazard, the probability of surviving to the next age interval (see 

Figure 71) is lower for individuals from Alameda Stone sections 1-2 than VMC. Survivorship 

declines at VMC at approximately age 35, while the survivorship declines at Alameda Stone 

sections 1-2 begins declining at approximately 20.  By the age of 55, individuals at VMC have 

less than a 10% probability of surviving to the next age interval.  The Alameda Stone sections 1-

2 sample encounters a less than 10% probability of surviving even earlier at age 45.   

 

Figure 70. Mortality Hazard VMC and Alameda Stone sections 1-2. 

 

 

 

159 

Figure 71. Survivorship VMC and Alameda Stone sections 1-2.  

There is not a statistically significant relationship between sex (c2= 0.1088, df = 1, p = 

 

0.74151), see Table 49.   

 

 

 

Sample 
VMC 
Alameda Stone 1-2 

Male 
720 
77 

Female 
75 
7 

Table 49. Individuals by Sex at VMC and Alameda Stone Sections 1-2. 

 
Alameda Stone Sections 3-5 
 

 

The age structure of sections 3-5 from Alameda Stone is very different from VMC (see 

Figure 72).  Sections 3-5 has a large number of infants (n=356; 32%) and subadults (n=201; 

18%) and a small number of older adults over the age of 50 (n=73; 6.5%). As previously stated 

VMC has a large proportion of older adults over the age of 50 (n=154; 31%), and very few 

subadults (n=43; 9%).   

 

160 

 

Figure 72. Age at death structure of VMC and Alameda Stone sections 3-5.   

 

     The hazard models indicate that there is a significant difference between VMC and Alameda 

Stone sections 3-5 regarding mortality and survivorship.  The probability density (Figure 73) 

demonstrates that individuals interred at Alameda Stone section 3-5 faced a higher probability of 

dying younger, both in terms of infant mortality and early adulthood, than those interred at 

VMC.  Alameda Stone section 3-5’s highest probability in adulthood begins at around age 35, 

while VMC’s occurs at approximately age 50.  

The probability of mortality (see Figure 74) is similar between the two samples.  At VMC 

the probability of mortality rises dramatically after age 45, while the probability of mortality at 

Alameda Stone section 3-5 is slightly earlier, rising around age 35.  

 

161 

Figure 73. Probability density function of VMC and Alameda Stone sections 3-5.  

 

Figure 74. Mortality hazard of VMC and Alameda Stone sections 3-5.  

 

 

162 

      Similar to mortality, the probability of survivorship in Alameda Stone sections 3-5 is 

generally lower than for VMC (Figure 75).  Those interred in Alameda Stone sections 3-5 faced 

a heavy risk of infant mortality.  Even at age five individuals in the Alameda Stone sections 3-5 

only have a 60% probability of surviving into the next age interval, while VMC has a 98% 

probability of surviving into the next age interval.   

     There is a statistically significant relationship between sex (c2= 230.0568, df = 1, p 

<0.00001), see Table 50.   

 

Figure 75. Survivorship VMC and Alameda Stone sections 3-5.  

Sample 
VMC 
Alameda Stone 3-5 

Male 
720 
217 

Female 
75 
199 

Table 50 Individuals by Sex at VMC and Alameda Stone sections 3-5. 

 

163 

 

 

 

 

Milwaukee County Institution Ground 
 

The age structure of MCIG is very different from VMC (see Figure 76).  MCIG has a 

large number of infants (n=346; 40%) and adults (n=394; 46%), as well as a smaller portion of 

older adults over the age of 50 (n=154; 18%). As previously stated VMC has very few subadults 

(n=43; 9%), a majority of adult individuals (n=296; 60%), and a large proportion of older adults 

over the age of 50 (n=154; 31%).   

The hazard models indicate that there is a significant difference between VMC and 

MCIG regarding mortality and survivorship.  Similar to Alameda Stone sections 3-5 the 

probability density (Figure 77) demonstrates that individuals interred at MCIG faced a higher  

Figure 76. Age at death structure of VMC and MCIG.  

 

 

164 

 

Figure 77. Probability density function VMC and MCIG.  

probability of dying younger, both in terms of infant mortality and early adulthood, than those 

interred at VMC.   

 

The probability of mortality (see Figure 78) is similar between the two samples after the 

risk of infant mortality.  At VMC the probability of mortality rises dramatically after age 45, 

while the probability of mortality at MCIG is slightly earlier, rising around age 35. Similar to 

mortality, the probability of survivorship at MCIG is lower than for VMC (Figure 79).  Those 

interred in MCIG faced a heightened risk of infant mortality.  Even at age one individuals at 

MCIG have a 60% probability of surviving into the next age interval, while VMC has a 98% 

probability of surviving into the next age interval.  

 

 

165 

Figure 78. Mortality Hazard of VMC and MCIG.  

 

 

Figure 79. Survivorship VMC and MCIG. 

 

166 

There is not a statistically significant relationship between sex (c2= 2.5788, df = 1, p= 

0.108306, see Table 51.   

 

 

Sample 
VMC 
MCIG 

Male 
720 
406 

Female 
75 
57 

Table 51. Individuals by Sex at VMC and MCIG. 

Voegtly 
 

 

The age structure of Voegtly is very different from VMC (see Figure 80).  The Voegtly 

cemetery has as a large number of infants (n=249; 36%) and subadults (n=273; 40%) with a very 

small number of older adults age 50+ (n=34; 5%). As previously stated VMC has very few 

subadults (n=43; 9%), a majority of adult individuals (n=296; 60%), and a large proportion of 

older adults over the age of 50 (n=154; 31%).   

 

Figure 80. Age at death structure of VMC and Voegtly. 

The hazard models indicate that there is a significant difference between VMC and 

Voegtly regarding mortality and survivorship.  The probability density (Figure 81) demonstrates 

that individuals interred at Voegtly faced a higher mortality risk earlier in life. 

 

167 

The probability of mortality (see Figure 82) is drastically different.  At VMC the probability of 

mortality rises dramatically after age 45, while the probability of mortality at Voegtly is 

consistent after age 5. This may be a result of the large number of individuals under the age of 5 

at Voegtly.   

Similar to mortality, the probability of survivorship at Voegtly is much lower than for 

VMC (Figure 83).  Those interred in Voegtly faced an extreme risk of subadult mortality.  By 

age five individuals at Voegtly have a 50% probability of surviving to the next age interval, 

while at that same age individuals at VMC have a 98% probability of surviving to the next age 

interval.  

 

Figure 81. Probability density function VMC and Voegtly.  

 

 

168 

Figure 82. Mortality Hazard of VMC and Voegtly. 

 

 

Figure 83. Survivorship of VMC and Voegtly. 

There is a statistically significant relationship between sex (c2= 108.5387, df = 1, p 

<0.00001), see Table 52.   

 

 

 

169 

Sample 
VMC 
Voegtly 

Male 
720 
95 

Female 
75 
67 

Table 52. Individuals by Sex at VMC and Voegtly. 

Each of the comparative samples required a slightly different approach in order to make 

 

Health 
 

 

 

 

the data comparable to VMC.  The Mission City Memorial Park is not included in the health 

comparison because causes of death are not available for those individuals.  Data for the 

Milwaukee County Institution Ground is derived from Dr. Colleen Milligan’s 2010 dissertation.  

Data for Alameda-Stone cemetery was provided by Dr. Joseph Hefner as well as the project’s 

site report (Heilen et al 2010).  Data from the Voegtly cemetery was derived from the report 

published by the Smithsonian Institution Press (2003).  Due to the lack of subadults in the VMC 

sample only adult results are discussed in detail.  Presence and absence data for periosteal 

reactions, tuberculosis, and syphilis was tabulated for each sample only from the adult 

population (see tables 52-55).   

 

 
 

 

Sample 

VMC 

Alameda Stone 

MCIG 

Voegtly 

Present 

Absent 

394 

164 

31 

8 

520 

526 

482 

156 

Table 53. Presence and absence of periosteal reactions in adults at each cemetery. 

170 

 

Sample 

VMC 

Alameda Stone 

MCIG 

Voegtly 

Present 

Absent 

10 

5 

6 

3 

904 

685 

525 

161 

Table 54. Presence and absence of tuberculosis in adults at each cemetery. 

Sample 

VMC 

Alameda Stone 

MCIG 

Voegtly 

Present 

Absent 

10 

3 

1 

0 

904 

687 

530 

164 

Table 55. Presence and absence of syphilis in adults at each cemetery. 

 

The prevalence rates for periosteal reactions (43%), tuberculosis (11%), and syphilis 

 

 

(11%) were higher at VMC than each of the comparative samples (Alameda Stone 24%, <1%, 

<1%; MCIG 6%, 1%, <1%; Voegtly 5%, 2%, n/a).  The chi-square rates for each comparison can 

be seen in Table 56.  The only statistically significant pathology was periosteal reactions, which 

was significant for each comparison. 

Summary 

This chapter provides the comparative results between the VMC skeletal sample and both 

 

 

associated historical documents and other comparative skeletal samples.  Looking first at the 

comparison between the VMC skeletal sample and the historical record, the skeletal sample and 

 

171 

 

Comparison 

Periosteal Reactions  Tuberculosis 

Syphilis 

VMC v. Alameda 
Stone 

c2= 64.8196; p 
<0.0001 

VMC v. MCIG 

c2= 215.8457; p 
<0.00001 

VMC v. Voegtly 

c2= 85.274; Yates 
Correction p 
<0.00001 

c2= 0.249; Yates 
Correction p 
= .6177 
c2= 0.0004; Yates 
Correction p = 
0.9499 
c2= 0.165; Yates 
Correction p 
= .6849 

c2= 1.385; Yates 
Correction p = 
0.2393 
c2= 2.547; Yates 
Correction p = 
0.1105 
n/a  

 

Table 56. Chi-squared results for pathological comparisons between samples. 

historic death register shows an identical prevalence of infectious pathologies.  However, the 

 

 

historic record has a much higher prevalence of tuberculosis, which suggests that the prevalence 

of tuberculosis diagnoses in the skeletal record is underrepresented.  This is likely a twofold 

issue of poor preservation, and the nature of skeletal involvement in tuberculosis disease 

progression. The age structure of the historic record is also very different from the skeletal 

sample, with many infants represented in the death register.  Similarly, the headstone data from 

county burials at Mission City Memorial Park also has a larger number of infant burials, unlike 

VMC. As previously mentioned, the lack of subadults in the skeletal sample may indicate 

differential burial treatment of subadults with them being buried elsewhere, or that there was a 

dedicated baby land where subadult burials were segmented into an unexcavated portion of the 

cemetery. Comparing the historic county burial deaths with nationwide cause of death 

prevalence also highlighted stark differences within the county burial population.  Individuals 

receiving county burials died from tuberculosis and premature birth at much higher rates that the 

nationwide average, indicating larger issues with communicable disease and maternal health. 

 

172 

 

The comparisons between the VMC sample and other similar skeletal samples provide a 

better context for assessing the overall health and demographic structure of VMC.  VMC is most 

similar to Alameda Stone sections 1-2, the sections interpreted as military and recent migrants.  

The prevalence of non-specific infections, tuberculosis, and syphilis is significantly higher in the 

VMC sample than MCIG, Alameda Stone, or Voegtly.   

 

The concluding chapter for this study will discuss the research questions and trends 

drawn from the results of the analysis of VMC provided in chapter 6, as well as the comparative 

analysis from this chapter.   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

173 

Chapter 8: Discussion 

This dissertation sought to examine the health and nutritional status of individuals 

Introduction 

 

 

 

interred in the Santa Clara Valley Medical Center historic cemetery.  This research concentrated 

on the interpretation of pathological characteristics, biological profile, and mortuary analysis 

within a framework of public health and structural violence.  The results reported in the two 

previous chapters (Chapter 6: VMC Results and Chapter 7: Comparative Results) provide data in 

these areas.  The following sections specifically address the goals and research questions of the 

current study using the results from the VMC sample and comparison with historical records and 

other skeletal samples.   

Question 1: Does institutionalization and or structural violence lead to identifiable 
biological impacts? 
 
 

Structural violence can also be viewed as inequality expressed through unfairness of 

distribution whose exchange is a political process. The bodies of the individuals interred at VMC 

became unentangled objects.  There is a minimal amount of commodification of the body, not 

necessarily the same as those individuals used as medical and anatomical specimens (see Figure 

84), but a small amount of social exchange has occurred with the transformative act of becoming 

a pauper burial.  Individual identities have been removed, yet there is still a level of social 

reciprocity that has occurred in providing a “proper” burial for these individuals.  This is done 

not to benefit the dead, but to benefit the social capital of the living associated with this task.  

 

 

174 

 

Figure 84. Record of Baby Warren, stillborn.  Cause of death Eclampsia.  Date of death 

December 23rd, 1931. Originally recorded as a county burial, but ultimately given to 
Stanford University.  Image source: County hospital death register Volume 5: 72-73.  

 
 

Santa Clara County, as early as 1855, was creating policies to aid the destitute, but these 

policies were just a stop-gap.  They cared for the destitute at the hospital, almshouse, and 

through outdoor relief, but did not appear to take measures to prevent the situations that 

precepted the illnesses.  Thus, the county created structural violence, or perhaps a better term is 

structural health inequalities.  Structural violence is the translation of large-scale social forces 

into biological reactions.  It is the embodiment of social mechanisms in the individual social 

experience (Farmer 2004, 2006).  

 

Immigrants and low socioeconomic migrants entering the Santa Clara Valley faced 

structured risk created by the prevalent social forces of the time.  Gender, ethnicity, and 

socioeconomic status play a role in creating the time and place specific vulnerability that leads to 

health inequality.  Even today there are significant mortality differentials based on these 

variables.  However, cultural differences do not automatically equal structural violence.  Both 

social and biological distinguishing characteristics can serve as a pretext for discrimination, 

however no single axis can fully define and predict an increased risk for suffering.  Poverty 

effaces the protective status conferred by specific genders, ethnicities, and religions.   

 

 

 

175 

“Poverty wields its destructive influence at every stage of human life, from the moment 

of conception to the grave.  It conspires with the most deadly and painful disease to bring 

a wretched existence to all those who suffer from it” – World Health Organization 

1995:5.  

 

“Understanding that the body is deeply historicized and socialized enables a cross-

cultural framework for understanding how social relations condition disease patterns and, more 

broadly, states of individual and collective affliction” (Nguyen and Peschard 2003:448).  The 

patterns of pathologies at VMC is related to these individuals’ lack of local social relations, 

which in turn, condition the disease patterns within this population. The relationship between 

inequality and health disparity and disease processes is a form of structural violence enacted 

through cultural and governmental policies and rationalities (Nguyen and Peschard 2003).  This 

ritualized pattern of social violence leaves observable, and quantifiable, biological impacts on the 

body. The cultural of inequality facilitates a “pathogenic biosocial spiral of socioeconomic 

exclusion and deteriorating health” (Nguyen and Peschard 2003:448).   

 

Social inequality contributes to ill health independently of income level.  But social class 

is too blunt of a ranking to capture the fine grain differences that occur within groups, just as low 

socioeconomic status does not account for variability within that group. Social circumstances are 

important in shaping quality of life.  Social connectedness is well established as an important 

component of health and well-being.  Social capital is composed of support networks, economic 

and social inequality, and access to resources (Szreter and Woolcock 2004; Wilkinson 1996). As 

connected to health outcomes, it is some variation of the presence or absence of a direct social 

support mechanism.  In groups where social capital is low, there are higher levels of stress and 

isolation, children’s welfare decreases, there is a reduced capacity to respond to environmental 

 

176 

health risks, and a reduced capacity to receive effective public health service interventions 

(Szreter and Woolcock 2004:78-84).   

To apply structural violence to a past population Klaus (2014) recommends specific 

requirements including: (1) historically contingent of specific trajectories of Western European 

capitalist style political economics; (2) Rigidly hierarchical society; (3) Consider its relationship 

to other forms of violence and power (4) Remember while agency is constrained, people should 

be expected to exercise as much agency as possible;(5)Thoroughly and deeply embedded 

engagement with archaeological and historical contexts.   

The pathological conditions and prevalence are VMC allows for an analysis of the 

embodiment of inequality.  The embodiment of inequality requires an epidemiological 

framework that relies on quantitative understandings of health. This framework can work under a 

Foucaultian thesis that in modernity violence is sublimated, transformed in historic (and modern) 

times into a more insidious and pervasive ordering of bodies through institutional practices 

(Nguyen and Peschard 2003:457).  Medical systems in different cultures, and at different times 

in history, differ in knowledge, methods, and the technologies used to diagnose and treat medical 

ailments.  However, medical therapy has always had a political dimension, and these therapeutic 

politics play an important role in creating and maintaining the social inequalities of health 

(Young and Leslie 1992; Burchell et al. 1991; Nguygen and Peschard 2003).   

Structural violence translates into affliction, or as Nguyen and Peschard (1003) referred 

to as the “pathogenic social spiral” from which it is exceedingly difficult to emerge.  Migration 

remains an important element of the equation, because it not only contributes to the erosion of 

extant forms of solidarity as people move further away, but it also facilitates the spread of 

infectious disease (p.464).  Migrant labor was often housed in insalubrious conditions, fulfilling 

 

177 

the prophecy of the diseased native (Packard 1989).  As the poor get sicker, and poorer, the cost 

of migrating and the social consequences rise. This triggers a defensive reaction on the part of 

the rich who do not want to shoulder the medical cost of inequality.  As a result, the pathogenic 

social spiral is often greeted with compliancy.  The lack of a social system removed previously 

available cultural buffers.   

Poverty is created structurally through interrelated power dynamics among “culturally 

constructed social classes, ethnic groups, genders, and other social groups, often through their 

interactions with institutions” (Spencer-Wood and Matthews 2011:2).  By examining disease 

prevalence rates, differences in health between social groups, and governmental/social policies 

we can begin to explore the biological consequences of structural violence.  

There are two ways to measure effects of structural violence in bioarchaeology: first by 

comparing prevalence differences between members of two groups – in this case it would be 

comparing the low socioeconomic sample (VMC) with an upper-class sample.  Since there is not 

an upper-class skeletal ample from this area, the second approach must be used: an analysis of 

well contextualized health outcomes by comparing the skeletal sample to the historical record.   

California’s rapid population growth coupled with the unique demographic profile of the 

burgeoning population resulted in an immediate and intense need for government welfare, 

specifically the rise of the county hospital. In 1855 the state legislature passed a Poor Law, 

pushing responsibility for the destitute sick to the county (Cahn and Bary 1936), leading to the 

formation of hospitals and almshouses in several counties, including Santa Clara.  “This growth 

of county hospitals was caused primarily by the acute need for a substitute for home life.  Of the 

adult population in 1860, approximately one-fourth were women, and therefore more than half of 

the adult population consisted of men single or living apart from normal family groups. Any 

 

178 

form of disability or destitution threw them upon the community and, although the kindness and 

mutual aid of the period were open-handed, the actual need of shelter and care was far greater 

than among a normally constituted population” (Cahn and Bary 1936:144).   

The 1901 Indigent or Pauper Act provided that every county shall relieve and support all 

pauper, incompetent, poor, indigent persons and those incapacitated by age, disease, or accident 

provided that they were not supported and relieved by their relatives or friends, or by their own 

means.  If the pauper had a spouse, children, parents, siblings, grandchildren, or grandparents 

living in the state the family was legally obligated to pay back the county for that individuals 

care (Cal. States 1901 CHAP CCX in Welfare Activities in California 1850-1934).  

In order to be admitted to the county hospital you had to prove you were a resident of the state 

for one year, a resident of the county for three months, had no family that could take care of you, 

no friends or family that could pay for your care, and that you didn’t own any assets that could 

be sold to pay for your care.  The hospital, specifically the superintendent and later a board, 

determined if the petitioner meet the criteria and if they had a condition that necessitated 

treatment.  In 1903 the State Board of Charities and Corrections was formed, and the supervision 

of county hospitals was placed under this jurisdiction.  The board sought to establish standards 

with respect to medical treatment and social policy.   

 

Not all individuals and ailments were treated the same at the Santa Clara county hospital. 

In 1903 the city passed a motion that no person shall be admitted to the County Hospital who is 

afflicted with any venereal disease, and the Superintendent was directed to refuse admission 

(Evening News April 21, 1903). Though the presence of individuals with venereal syphilis 

(n=10) in the VMC skeletal sample indicates that this city ordinance may have been short lived, 

or not fully enforced. In 1901 the county was also accused of refusing care to Chinese 

 

179 

individuals at the county infirmary (Figure 85).  Claims by the Superintendent that the hospital 

treated “dozens” of Chinese since 1874, may be more supportive of the refusal of admission 

claim than it is defensive, as individuals of Chinese origin were a major fraction of Santa Clara 

County during the late 19th century.    

Figure 85. San Jose Mercury News October 20th, 1901. 

 

 

 

By carefully examining and reconstructing the prevailing social systems individuals 

interred in this cemetery encountered, it is possible to explore issues of structural violence and its 

relationship to disease.  Even in the absence of specific burial records, these methods can still be 

applied.  Expanding the theoretical framework of structural violence not just to highlight the 

traditional bioarchaeological pathology categories, but the contextualization of them using 

historical documentation allows for the consideration of the differential application of the forces 

 

180 

that affect health.  A structural violence framework allows me to contextualize the disease 

prevalence rates and patterns at VMC within the social and political atmosphere the individuals 

lived in.  Therefore, issues such as the 43.5% of individuals with non-specific infections, is 

understood not just as “poor health”, but also as a consequence of both social, institutional and 

government policy and decision-making processes.   

 

The hospital direct internment burial category showed signed of increased biological 

stressors compared to other burials at VMC (Table 57).  Although many patients at the infirmary 

had short stays, a large proportion of the hospital population were long term custodial patients 

(Figure 86).  The 1914 state wide survey of county hospitals estimated that nearly 70% of all  

 

 

 

 

Category  

Sex 
Age 
Periosteal 
Reaction 
Fracture 
 

22.01 
4.49 

 

1 
1 
 

Χ2 
1.02 
2.24 

df 
1 
2 

p-value 
0.31 
0.32 

ϕ 
0.04 
0.05 

<.0001 
0.05 

 

0.15 
-0.07 

 

Table 57.  χ2 Non-hospital internment v. hospital direct internment sample. 

Figure 86. Probable Length of Stay based on hospital patients statewide in 1914.  State 

Board of Charities and Corrections 1916:60.  

 

181 

hospital stays could be considered custodial having been patients for more than 6 months.  A 

majority of the hospital population, 53% has stayed for over a year.  This would allow ample 

time for the long-term time frames necessary for the pathological conditions seen in the hospital 

patient population to be connected to the institution, and the treatment of the patients.  The 1880 

Federal Census of Defective, Dependent, and Delinquent Classes lists not only the name, 

occupation, and age/sex data for individuals residing at the hospital, but also lists the cause of 

their disability and the date that they entered the care of the hospital.  Although some of the 

individuals had been residents for only a few months, a majority had been there for 1-4 years.  

Those with longer residents list their chronic issues as kidney disease, gout, rheumatism, 

syphilis, tuberculosis, and old age to name a few (U.S. Census 1880).  This supports the 

assumption that the individuals in the hospital’s care were struggling with long-term illness that 

would impact the stress indicators skeletally.   

Although the historical record sheds light on some of the structural inequality in Santa 

Clara County, the skeletons provide direct evidence of the biological consequences of this 

inequality.   VMC represents the poorest of the poor of Santa Clara County.  These are not just 

the individuals that needed medical aid and were treated at the hospital.  These are people so 

socioeconomically disadvantaged that they, or their close social group, lacked the economic 

means for a private burial.   The health of low socioeconomic individuals in Santa Clara County 

appears to have suffered as a result of the action of the government and prevailing social 

systems, or phrased another way, structural violence has significant impacts on the health of 

these low socioeconomic individuals. 

 

182 

Question 2: At this time, we know that major issues such as the second epidemiological 
transition, public health reform, immigration, and socioeconomic status impact the health 
and nutrition of people. Given the nature and historical context of VMC how did these 
events effect people at VMC?  

 

Epidemiologic transition theory has been a guiding principle for examining the impact of 

economic, social, and environmental transformations in recent human history (Barrett et al. 

1998; Zuckerman 2014).  The second epidemiologic transition is characterized by a decrease in 

infant mortality, a decrease in maternal death, a decrease in infectious disease deaths, and an 

increased life span (Barrett et al. 1998; Orman 1971).  There is also a shift from acute infectious 

diseases, like whooping cough or measles, to chronic non-communicable disease such as 

cardiovascular disease or cancer (Zuckerman et al. 2014).  In the United States and Europe, the 

second epidemiologic transition typically begins in the mid 19th century. The timing of the 

transition is attributed to public health initiatives, the germ theory of disease, and improved 

hygiene (Cutler and Miller 2005; Gage 2005, Reinhard and Pucu de Araujo 2014).  

Although this framework emphasizes the impact of socioeconomic and ecological factors 

on disease mortality transition, the trend has unfortunately been to apply the transition uniformly 

across populations as large as countries or even continents.  This data conflation minimizes the 

differential experiences based on location, race, gender, and class (Barrett et al. 1998; McKeown 

2009; Fleischer and McKeown 2014).  It has been previously suggested that socioeconomic and 

local conditions, such as degree of urbanization, seem to influence the extent, nature, and timing 

of the transition (Dobson 1997; Woods 2000; Zuckerman 2014).  The transition status of the 

VMC skeletal sample can be interpreted from the infant mortality rate, number of infectious 

pathologies, and mortality curve. 

 

 

 

183 

Infant Mortality 

In the VMC skeletal sample, the near absence of infants (n=5/1004) would suggest that 

either the infant mortality rate is either shockingly low, or infants simply were not buried within 

the excavated section.  Newspaper articles such as the one seen in Figure 87 indicate that more 

subadults are likely elsewhere in the cemetery as no 7-week old infant was recovered. 

A low infant mortality rate is unlikely, especially once historical records are examined.  

Newspaper articles were routinely highlighting the dichotomy of California’s overall low infant 

mortality rate and San Jose’s higher infant mortality rate.  Headlines like “Infant Death Rate 

Apparently High Here” (Evening News February 6, 1917), and “Babes Dying Needlessly in San  

 

Figure 87. Child buried without Health Board Permit.  Evening News April 7, 1916 page 9. 
 

Jose” (Evening News March 31, 1917), see figure 88, juxtaposed with “Infant Mortality is at 

Minimum In State. California Given Honors for Having Lowest Rate in the Entire Country” 

(Evening News July 21, 1921).  For example in 1916 the mortality rate for children under the age 

 

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of two state wide was 23 per 100,000, but in San Jose the rate was more than double at 47 per 

100,000 (Evening News June 15 1917).   

The hospital death register shows that infant, and neonate mortality, continued to be high 

into the late 1920s-early 1930s.  Infant (<1 year old) deaths are 8.5% (n=206/2427) of private 

burials, and 27% (n=170/629) of the county burials.  Unfortunately, without knowing the number 

of live births and individuals surviving past 1 year, the mortality rate (per 1,000 live births) 

cannot be calculated.   

 

Figure 88. Excerpt from article blaming San Jose’s high infant mortality rate on mothers 
not knowing how to give proper care to their babies.  Image source: The Evening News, 

March 31st 1917 68(78):6.  

 

 

Disease 

 

In a ten year retrospective published in 1916, the California State Board of Health notes 

decreases in the death rate for tuberculosis (218.0 per hundred through to 194.5 per hundred 

thousand) and epidemic diseases (68.5 per hundred thousand to 33.1 per hundred thousand) 

 

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while noting death rate increases for diseases of the circulatory system, Bright’s disease (a 

kidney disease), nephritis, and cancer.  The death rate for “young persons” was decreasing, while 

the death rate for the middle ages and beyond was steadily increasing.  Infant mortality has also 

decreased during this ten-year period – ascribed to a drastic reduction in children under the age 

of two dying from diarrhea and enteritis (45.7 per hundred thousand to 27.8 per hundred 

thousand) (California State Board of Health July 1916:7)   

However, infectious disease rates are high (45%) in the VMC skeletal sample and the 

county burial portion of the death register (45%).  The VMC skeletal sample had the higher 

prevalence rates of periosteal reactions, tuberculosis, and syphilis than any of the comparative 

skeletal samples.  The county burials from the death register have high rates of tuberculosis 

(16%) and pneumonia/influenza (12%).   This is directly contrary to the larger state wide health 

state provided by the California State Board of Health.  Death from non-communicable diseases 

(aside from heart disease which can be due to both acute and chronic issues) are relatively low in 

the county burial portion of the death register.  Cancer (6.63%) and diabetes (0.24%) are 

relatively minor contributors to the overall causes of death.   

 

Mortality  

The VMC skeletal samples probability of mortality rises sharply at age 40. The Mission 

City Memorial Park and county burials from the death register does not see a rise in their 

mortality hazard until age 70.   It is necessary to consider how the lack of infants in the VMC 

sample may be impacting the hazard models, and the differences in comparing skeletal age at 

death data with recorded age at death.  However, all of the hazard modeling indicates that 

individuals from the VMC skeletal sample faced a higher risk of death earlier in life than the 

 

186 

other samples.  When compared to the other skeletal samples only Alameda Stone sections 1-2, 

the military and migrant sections, had an earlier mortality spike.   

The high rates of infant mortality provided by the historical record, high rates of 

infectious disease in both the skeletal sample and historic record, and higher risk of earlier 

mortality seen in both the skeletal sample and historic record of county hospital deaths indicates 

that this population had not yet reached the second epidemiologic transition.  This is another 

example of epidemiologic transitions occurring at different rates between populations, even at 

the same time and geographic location.   

Public Health 

Santa Clara County was an early adoptee of public health campaigns.    The department 

of Health of the city of San Jose began formal reporting in 1890, following an August 1889 

ordinance mandating health reports on the city (Curnow 1896:1).  In 1896 the City of San Jose 

general municipal ordinance No. 1654 An Ordinance in Relation to the Preservation of the 

Public Health included sections covering the privileges of the board of health; penalty for failure 

to abate nuisance; adulterated swill milk ; diseased or unsound meats, game, poultry, fish or 

other market products; articles exposed for sale shall be deemed for sale; police shall seize and 

removal articles unfit for human food; stalls where animals are kept to be cleaned – no swine 

allowed near dwellings; births must be reported; burial permits  - how granted; dead bodies – 

removal permits; physicians must report contagious and infectious diseases; hotel keepers and 

house holders must report scarlet fever, diphtheria and small pox; quarantine regulations – 

persons not to enter or depart from houses quarantined; penalty (General Municipal Ordinance).   

 

As early as 1902 (Figure 89) the decreased deaths rates from tuberculosis in Santa Clara 

County are being attributed to “…improved methods of treatment…inspection of food  

 

187 

 

Figure 89. Consumption Death Rate is Decreasing. Santa Clara County Favorably 

Reported by Health Officer Simpson Evening News (Published as The Evening News) - 

April 16, 1902 Volume XLI Issue 99 Page 3. 

products…improved sanitary methods and conditions [and enforcements of] sanitary precaution” 

(Evening News April 16 1902), i.e. public health initiatives.  However, as discussed in the next 

section, not all individuals benefited equally from public health policies. 

 

Immigration 

 

As discussed in the Question 1 section, foreign born individuals and recent migrants into 

the area faced animosity and discrimination in many aspects of their lives.  Public health 

initiatives often focused on the dangerous and ignorant “others” as the root cause of public 

nuisances and epidemics.  Health officials routinely pointed to the “willful ignorance of 

foreigners “and low socioeconomic individuals as the root cause of high infant mortality and 

high epidemic disease loads. Assistant Health Office Harold F. Gray is quoted as stating that 

“…need of instruction in the care of infants among the poorer classes of our citizens … who do 

not realize the condition of affairs” (The Evening News June 15 1917).  “Beginning with the 

agitation against foreigners in the gold fields, there has been virtually no period in California 

history without a campaign against some unpopular minority group: Latin Americans, Native 

 

188 

Americans [Indians], African Americans [Negros], Chinese, Japanese, Filipinos, and distressed 

Southern Whites “Oakies” have all been involved in this kind of conflict” (Cahn and Bary 

1936:135-136). 

It’s likely that the poor and indigent whites in Santa Clara County were more likely to be 

admitted and treated at the hospital, while those of other ethnicities may have only been admitted 

to the infirmary in critical situations, or just to be buried in the adjacent potter’s field.  Many of 

the indigent “white” individuals (noted in the historical record) may have been buried as the two 

other, nicer potter’s fields. As mentioned previously, there were specific requirements for being 

admitted to a county hospital. To be treated you had to submit a formal petition, prove that you 

had been a resident of the state for at least one year, a resident of the county for three months, 

had no property you could sell to pay for medical care, and no relatives that could support you.  

Thus, very recent migrants to the area would not have qualified for county medical care, even if 

they lacked the personal property and social network aspects of the requirements.   

 

The disease prevalence rates suggest that this, along with other prevailing social issues, 

may have prevented many from seeking medical care.  The hospital, even though it was created 

to care for the areas indigent sick, seemed to be doing everything it could to only treat the 

“types” of people they found suitable.  For example, in 1889 the county board of supervisors 

sought to have new maps of the county produced.  But they noted that it would be advisable to 

leave the county infirmary off of the maps because the maps were going to be highly visible and 

showing that the county had the infirmary (and almshouse) might encourage “undesirable 

immigration” (Evening News May 8 1889).   

Unfortunately, ancestry assessment was not possible on a majority of the sample.  Of the 

411 individuals with ancestry assessments 24% (n=106) were of European ancestry while the 

 

189 

remaining 76% (n=305) were of non-European ancestry (Asian/Latino or African American).  

The use of different ancestry assessments methods during the on-going analysis at CSU, Chico 

may provide additional degrees of specificity with regards to the ancestry assessments.   

The 1914 survey of statewide county hospitals also noted that individuals of “White 

European” descent are a majority of the hospital population (Figure 90).  Although individuals of 

non-European descent are only 7.5% of the total hospital population they are specifically called 

out as a “foreign problem”.  The survey of hospital patients showed that 42% of patients had 

been in the county over five years, 22% 1-5 years, 3 months – 1 year 14.6%, and 3 months of 

less 21.2%.  Interestingly of the 4,214 foreign born patients documented only 156 (3.7%) had 

been residents for less than a year.  Only 591 (14%) has been residents in the United States for 

less than 5 years before admission to a county hospital.  This indicates one of two things, (1) the 

counties may have refused admission to individuals that had been residents for less lengths of 

time, or (2) the demographic profile of California was changing.  Although individuals, or their 

parents, were foreign born by the 20th century migration trends were changing, and many 

Californians, though foreign born, were not new to the state or county (see Figure 91 and 90).  

However, length of residence does not seem to negate the larger negative health impacts of 

systemic racism and inequality. 

 

190 

 
Figure 90. Breakdown of “racial and national groups” among county hospital patients 

statewide in 1914.  Source: State Board of Charities and Corrections 1916:56.  

 

Figure 91. California foreign born population by world-region of origin.  Data source: The 

Population of California, 1946. 

 

 

 

191 

Figure 92. Native born v. foreign born. Data Source Population of California 1946. 

 

 

Question 3: Putting the cemetery in context with the historical record suggests a set of 
expectations of particular kinds of pathologies. How do these expectations compare with 
the pathologies documented in the skeletal remains? 
 

 

As illustrated above in the discussion of questions 1 and 2, an in-depth analysis of 

the historical record reveals stark health disparities in Santa Clara county during the late 19th and 

early 20th century.  In California as a whole, the death rate for infectious diseases, such as 

tuberculosis, was much higher for every non-white racial group than for whites (ex. TB for 

Mexicans 5x higher, flu and pneumonia deaths 3x higher).  Infant mortality rates were also 

higher among every non-white group (4x higher among Mexicans and 3x higher among Native 

Americans).  The high rates of infectious disease and high infant mortality rates are tied to 

poverty, unsuitable living conditions, and lack of medical care (Cahn and Bary 1936:224).  The 

 

192 

skeletal data conforms well to the historical, contextual data revealing unhealthy living 

conditions.  There is high nonspecific periosteal inflammation, high rates of infectious disease, 

and high rates of enamel defects.  The nature of these skeletal responses points to long term, 

chronic health issues.   

 

As discussed in Chapter 6, the VMC skeletal sample has a high prevalence rates of non-

specific infections (45%), documented tuberculosis (n=10), Valley Fever (n=2), and syphilis 

(n=10), amongst other pathological issues.  The low socioeconomic status of individuals given 

pauper burials, combined with the higher rates of individuals of non-European ancestry (70% of 

the assessable sample) indicates that the disease prevalence’s rates confirm to the expectations 

from the historical record.  The only component of the historical record that the skeletal sample 

does not meet is the high infant mortality rate.  The lack of infants within the skeletal sample 

does not mean that this population did not have a higher neonate and infant mortality rate, rather 

that they are just not present within the portion of the cemetery exhumed.   

 

Question 4: How does VMC compare to similar cemeteries in terms of the consequences of 
structural and institutional behavior? 
 
 

As discussed earlier in this chapter, issues stemming from structural violence and 

institutionalization may have produced the high rates of infectious disease documented in the 

VMC skeletal sample. The prevalence rates of every pathological category examined was higher 

at VMC than of each comparative sample (Alameda Stone, MCIG, and Voegtly).  The 

prevalence rates for periosteal reactions was double (43%) the next closest sample Alameda 

Stone (23%).  The high rates of non-specific infections are a proxy for viewing larger issues of 

systemic infection within the living population.   

 

193 

 

Admittingly there are theoretical issues that arrive when attempting to measure the 

consequences of structural and institutional behaviors based on the health of a population from 

skeletal data.  Wood et al. (1992) highlighted the issues of demographic nonstationary, selective 

mortality, and hidden heterogeneity.   As pointed out in Chapter 2, the VMC population, and in 

fact most of the population of California at this time, was demographically nonstationary.  

Migration and immigration were fundamental components of this population, similar to Alameda 

Stone (Leher et al. 2010:511).   With regards to selective mortality, the VMC skeletal sample is 

not representative of the entire population of Santa Clara County (i.e. they represent only 

individuals that received pauper burials), thus the skeletal data does not represent the entire 

population at risk for a specific hazard.  The skeletal data may overestimate the prevalence of a 

particular pathology when compared to the entire population (Wood et al. 1992).  Hidden 

heterogeneity, the different levels of susceptibility to health risks within a population (Wood et 

al. 1992), can be due to factors such as socioeconomic status, environmental variation, or 

genetics.  The unifying low socioeconomic status of the individuals interred at VMC reduces 

some of the potential hidden heterogeneity. Even if, based on some of the issues put forth in the 

Osteological Paradox and subsequent critiques, individuals with the infectious responses were 

the “healthier” portion of the population, the high rates of periosteal reactions, tuberculosis, and 

syphilis still point to a population under undue biological stress.   

 

The Voegtly Cemetery is populated by middle/upper class individuals and has a very low 

rate of infectious disease, though high infant mortality.  The higher socioeconomic status of the 

individuals buried there, as well as the Swiss-German nature of the church population (Ubelaker 

and Jones 2003) may have sheltered these individuals from the consequences of structural 

 

194 

violence and institutionalization.  Thus, in terms of this research question is not a comparable 

sample.  

VMC is more similar to MCIG in terms of pathologies, likely due to the institutional 

nature of the cemetery and the higher immigrant basis of the population.  However, the 

prevalence rates for all pathological categories investigated were much higher at VMC.  

Demographically VMC and MCIG have very different age structures, due mostly to the lack of 

subadults in the VMC population.  The lack of infants in the VMC sample is also likely what 

produces the drastic differences between the two samples hazard analysis.  The distribution of 

sex is, however, similar between the two samples with a majority being males (VMC = 90.5%, 

MCIG = 88%).   

 

What may account for the differences in pathology and demography seen between the 

two samples?  Although Milwaukee was a city with a heavy immigrant component, it was 

mainly comprised of immigrants from northern and western Europe (Milligan 2010:15). The 

population of Santa Clara County was heavily European, but more ethnically diverse in terms of 

county of origin, especially for individuals from outside of Europe.  Additionally, Milwaukee’s 

immigration patterns were more family based, while California attracted a higher rate of single 

males, or males away from families elsewhere.  Milwaukee’s economy was focused on industrial 

manufacturing and shipping (Leavitt 1982) compared to the agricultural focus of Santa Clara’s 

economy.  Milwaukee may have had better implementation of their public health programs and 

policies. These factors created very different contexts, though both samples are institutional 

potter’s fields, within which structural violence and institutionalization were bounded and played 

out.    

 

195 

VMC has higher rates of pathologies than either Alameda Stone sections 1-2 or 3-5. 

Demographically VMC is more similar to Alameda Stone sections 1-2, which is comprised of 

the military and recent migration sections of the cemetery.   The differences in both the 

pathologies and demography highlights the impact of structural violence and institutionalization 

at VMC.  Alameda Stone was selected as a comparative sample due to its rural western context 

and 19th century timeframe.  Though Alameda Stone is temporally earlier than VMC, having a 

sample with a similar rural western nature was important.   

Question 5: Are there changes in the cemetery in terms of the spatial organization, and 
might these be attributed to change over time or differential treatment of health? 
 
 

Neither coffin construction nor grave goods provided enough temporally diagnostic 

features to differentiate time periods within the cemetery.   

In terms of spatial organization several trends emerged.  Geo-spatial clustering was 

statistically significant for males, subadults, rectangular coffins, and the hospital button burial 

category.  Burials of subadults are concentrated in the southern and northwest portions of the 

cemetery.  This may suggest differential spatial patterning dependent on decedent age.  However, 

the lack of younger subadults, especially infants <1 year of age, as previously mentioned is not 

consistent with the historical record.  This suggests that the youngest individuals within the total 

cemetery may be buried in a segregated baby land.  Rehor and Beck (2015) estimated that 35% 

of the total cemetery was exhumed, thus it is possible that larger burial trends are being obscured 

by only having the northern most portion of the cemetery to examine.   

 

Rectangular coffins comprise 15% (n=149) of the coffins (see Figure 93).  They are 

found throughout the sample, and also cluster with other rectangular coffins.  Their presence 

across the cemetery suggests that their use is likely not temporally diagnostic.  The individual 

undertaking companies hired by the county for the one-year burial contracts may have used 

 

196 

several coffin suppliers, or purchased whichever style was the cheapest at the time.  The less the 

burial cost for the undertaker, the more profit there was to be made.  Specific coffin shapes or 

dimensions are not typically mentioned in the historic record.  Although the use of redwood as 

the material is frequently mentioned.   

The only glimpse into specific coffin style choices is the Monahan funeral records. Hocking, 

Arnold and Monahan Undertakers were routinely paid by the country for indigent burials and the 

burial of soldiers as evident in warrants published monthly by the county for individuals owed 

payment.  The funeral records available for three individuals interred at the County hospital note 

three different styles of burial container: homemade coffin lined with white silk (for a 4 hour old 

infant charged $10 for burial), redwood box (3 years old charged $7.50 for the coffin and burial), 

and no casket (75 years old, charged $15 for embalming and $12.50 for services). The 

homemade coffin was produced by Bill Hanser Sr., the redwood box was manufactured by 

“J.M.”, and the “no casket” is noted to be manufactured by the county hospital so perhaps there 

was still some form of burial container (Monahan Funeral Records 1914-1936; source Santa 

Clara Central Library).  The initials J.M. are also present as the individual that received the 

undertaker’s payment for the burials, so J.M. likely works for the company, suggesting in-house 

production of coffins. These burials each took place at the County Hospital Cemetery in 1917 

from the same funeral home, yet each received a different coffin.  This highlights the amount of 

potential variation in burial containers. They also note a coffin style of “hospital case” for a 

private burial in the Chinese section of Oak Hill cemetery but do not note the manufacturer, so it 

is possible that there was a standardized size and style of coffins utilized for some hospital 

internments. 

 

197 

The clustering of the hospital button burial category may indicate that individuals in 

charge of the burials waited until several hospital direct internments needed to occur before 

burial.  It also could simply suggest that multiple people died in close succession. 

Dispersion was statistically significant for adults, hexagonal coffins, and community 

members. However, each of these categories represents the largest single variable within the 

larger categories of age, coffin shape, and burial category.  The statistical significant may be a 

product of the overall sample size of each of these categories.  Individuals with non-specific 

infections (Figure 94) and syphilis (Figure 95) appear across the cemetery.  The burials with 

tuberculosis (Figure 96) are concentrated in the southwestern quadrant of the cemetery.  The 

placement of these individuals does not suggest any differential burial patterning based on 

illness. 

The results of this research suggest that the social and health inequalities seen in the 

Conclusion 

 

VMC skeletal sample can be understood by examining the county’s efforts towards public health 

initiatives, public policy toward the destitute, and the components of structural violence and 

institutionalization that intertwine with these factors.  The time and place specific vulnerability 

encountered by these individuals in life are shown to have specific biological consequences.  The 

individuals interred at VMC grappled with higher rates of infectious communicable disease and 

higher infant and neonate mortality rates than their middle- and upper-class counter parts.   

The reformation of social welfare in the 19th century led to increases in structural inequality.  

These conditions experienced by inmates of the hospital, and the larger lower socioeconomic 

community only reinforced social and health inequalities.   These institutionalized social 

inequalities resulted in physiological consequences observable skeletally in the high rates of 

 

198 

pathological reactions. The lack of social capital removed cultural buffers that were previously 

available to these individuals before moving to the Santa Clara Valley.  The interplay of 

migration, lack of social capital, a low socioeconomic status, ill health, and government health 

care created a pathogenic social spiral (Nguyen et al. 2003) that was exceedingly difficult to 

emerge from.  

The incorporation of a structural violence as an interpretative framework promotes the 

balanced integration of empirical bioarchaeological studies and social theory to interpret the 

skeletal data. A thoroughly and deeply embedded engagement, with both the archaeological and 

historic contexts in conjunction with the skeletal data, allows for a more nuanced analysis of 

pathological responses.    

 

 

199 

Figure 93. Burials by coffin shape. Rectangular coffins are red, all other shapes are yellow.  

 

 

 

200 

Figure 94. Burials with non-specific infections in red.   

 

 

 

 

 

201 

Figure 95. Burials with syphilis shown in red.  

 

 

 

 

 

202 

Figure 96. Burials with tuberculosis shown in red.   

 

 

 

 
 
 

 

203 

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204 

 
 
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