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dissertation entitled

THE MULTIPLE PATHWAYS OF NEIGHBORHOOD EFFECTS

presented by

Dan Cantillon

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THE MULTIPLE PATHWAYS OF NEIGHBORHOOD EFFECTS
By

Dan Cantillon

A DISSERTATION
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Department of Psychology - Urban Affairs

2002

ABSTRACT
THE MULTIPLE PATHWAYS OF NEIGHBORHOOD EFFECTS
By

Dan Cantillon

The role of neighborhood effects research on youth outcomes has been re-
acknowledged in psychology as census data and other social indicators have displayed
the extreme levels poverty endured by many residents in the urban areas of our nation.
While recent studies have found empirical support for neighborhood effects on youth
outcomes, most analyses have been limited in their assessment of the ways in which the
neighborhood context impacts youth. Using structural equation modeling, the current
study simultaneously assessed how neighborhood disadvantage impacts neighborhood-
level, family-level, and individual-level variables to ultimately inﬂuence the youth
outcomes of delinquency, drug and alcohol use, and conventional activity.

The results of this study found substantial support for the multiple pathways in
which neighborhood disadvantage impacts both positive and negative youth outcomes.
Speciﬁcally, neighborhood disadvantage was signiﬁcantly associated with higher rates of
delinquency and alcohol and drug use. Interestingly, the direct effect of neighborhood
disadvantage was stronger and more consistent when Ofﬁcial police data was analyzed
versus self-report data. Indirectly, it was demonstrated that neighborhood disadvantage
lead to less socially cohesive neighborhoods and ultimately higher rates of severe
delinquency. Employing social disorganization theory, the current study has further

delineated the indirect pathway from neighborhood structural disadvantage to

delinquency by unpacking the important neighborhood-level social processes
(community social organization) as hypothesized by Shaw and McKay. The current
study used sense of community as a measure of community social organization and
assessed how this variable transmitted the effects of neighborhood disadvantage on
informal social control, which was signiﬁcantly related to delinquency rates. The current
study also extended the assessment of the indirect pathways of neighborhood effects by
assessing how neighborhood disadvantage impacts youth outcomes via its impact on
parental support and monitoring and youth’s afﬁliation with delinquent peers. The
results indicated that neighborhood disadvantage signiﬁcantly decreased parental support
and monitoring, which lead to afﬁliation with delinquent peers and higher rates of
delinquency and alcohol and drug use.

Overall, the results of this study demonstrated the multiple pathways through
which neighborhood disadvantage exerts its deleterious effects on youth. The results
underscore the need for multilevel prevention and intervention programs, which target
neighborhood-level, family-level, and individual-level variables to reduce delinquency
and drug use. Moreover, given the strong direct effect of neighborhood disadvantage,
even multilevel programs and neighborhood development initiatives may have little
impact on decreasing delinquency and drug use and increasing positive youth outcomes.
In fact, to truly make an impact in disadvantaged neighborhoods, the results suggest that
signiﬁcant policy changes need to be made at the city, state, and federal level to address

both the causes and consequences of concentrated poverty.

ACKNOWLEDGEMENTS

I’d like to thank Bill Davidson for his support and guidance over the past ﬁve
years and particularly throughout the dissertation process. I’d also like to thank Deb
Bybee for all of her assistance throughout the data analysis process. I really appreciated
all the time she spent meeting with me and explaining the ﬁner details of structural
equation modeling as well as her continual feedback over e-mail. I am also certainly
indebted to all of the undergraduate 490s, particularly Heather Van Dyke, Hamza
Bunnya, and Anne Hussey, who spent an incredible amount of time traveling throughout
Lansing and talking to families and youth about their local neighborhood. Completion of
this work would also not have been possible without the expert GIS knowledge of Sam
Quon, who helped geoeode the sampled households, and more importantly, in the
creation of block-level buffers, which allowed me to use a neighborhood-level ofﬁcial
delinquency score for each youth. I’d also like to acknowledge the support and help I
received throughout this process from my family and friends. In particular, I appreciate
all the support I received from David Loveland and support and editorial assistance

provided by Jennifer Juras.

iv

TABLE OF CONTENTS

LIST OF TABLES ........................................................................... vii
LIST OF FIGURES .......................................................................... viii
CHAPTER 1
INTRODUCTION ........................................................................... 1
Sociological Theory and the Eternal Quest for Community .................. 4
The Old-Chicago School: Ecological Theory of Urban Dynamics
and the Development of Social Disorganization Theory ....................... 7

History of the Inﬂuence of SD Theory on Sociological, Criminological,
and Psychological Inquiry: The Rise, Fall, and Re-emergence of SD

Theory ................................................................................. 11
Current Neighborhood Effects Research ......................................... 23
Updated Systemic Models of Social Disorganization or Collective
Socialization ......................................................................... 25
Sense of Commtmity ............................................................... 28
Measuring SOC ...................................................................... 32
The Impact of Neighborhood Disadvantage on Parenting, Family
Processes, and Afﬁliation with Delinquent Peers ............................... 36
Neighborhood Selection Effects ................................................... 42
Summary .............................................................................. 44
CHAPTER 2
METHOD ..................................................................................... 56
Procedures ............................................................................ 56
Setting ........................................................................ 56
Participants .................................................................. 56
Recruitment Procedures ................................................... 57
Interviewer Training and Supervision ............................................ 58
Interview Procedure ................................................................. 60
F ace-Block Measures ............................................................... 60
Block Income ............................................................... 61
Block Stability .............................................................. 62
Sense of Community ....................................................... 62
Informal Social Control ................................................... 62
Ofﬁcial Crime & Delinquency ........................................... 63
Family Measures .................................................................... 64
Family Support and Monitoring .......................................... 64
Individual Youth Measures ........................................................ 64
Afﬁliation with Delinquent Peers ........................................ 64
Youth Outcome Measures .......................................................... 64
Minor Delinquency — self-report ......................................... 65
Severe Delinquency — self-report ......................................... 65

Alcohol and Drug Use ..................................................... 65

Conventional Activity ..................................................... 65
Data Analyses ........................................................................ 66
CHAPTER 3
RESULTS ..................................................................................... 70
Measurement Model ................................................................ 70
Structural Models .................................................................... 72
Conventional Activity ...................................................... 72
Minor Delinquency — self-report ......................................... 74
Minor Delinquency — ofﬁcial ............................................. 75
Severe Delinquency -— self-report ........................................ 76
Severe Delinquency — ofﬁcial ............................................ 77
Alcohol and Drug Use - self-report ...................................... 77
The Moderating Effect of Family Support and Monitoring on
Youth Outcomes ..................................................................... 79
CHAPTER 4
DISCUSSION ................................................................................. 97
The Role of Neighborhood Stability .............................................. 97
Official Delinquency vs. Self-Reported Delinquency .......................... 99
Measuring Community Social Organization .................................... 103
The Indirect Effect of Neighborhood Stability via Family
Support & Monitoring .............................................................. 104
The Role of Neighborhood Income ............................................... 106
Moderating Role of Family Support and Monitoring ........................... 107
Limitations ........................................................................... 109
CHAPTER 5
IMPLICATIONS FOR FUTURE RESEARCH .......................................... 110
APPENDICES .............................................................................. 113
Appendix A- Indicators of Latent Constructs .................................. 114
Appendix B— Correlation Matrix ........... T. -,\ ................................... 116
REFERENCES ............................. 118

Table 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Table 9

Table 10

Table l 1

Table 12

LIST OF TABLES

Signiﬁcant Findings From Recent Social Disorganization
Studies ........................................................................ 49

Sense of Community and Related Measures for Geographic
Communities ................................................................. 50

Racial/Ethnic Background of City’s High School Student &
Research Participants ....................................................... 69

Final Measurement Model Factor Loadings (N =103) .................. 81

Goodness of Fit Indices & Chi-Square Difference Results
for Conventional Activity .................................................. 82

Goodness of Fit Indices & Chi-Square Difference Results
for Minor Delinquency — self-report ..................................... 84

Goodness of Fit Indices & Chi-Square Difference Results
for Minor Delinquency — ofﬁcial ......................................... 86

Goodness of Fit Indices & Chi-Square Difference Results
for Severe Delinquency - self-report ..................................... 88

Goodness of Fit Indices & Chi-Square Difference Results
for Severe Delinquency — ofﬁcial ......................................... 90

Goodness of Fit Indices & Chi-Square Difference Results
for Alcohol & Drug Use - self-report .................................... 92

Goodness of Fit Indices & Chi-Square Difference Results
for Alcohol & Drug Use — ofﬁcial ....................................... 94

Moderating Effect of Family Support & Monitoring on
Youth Outcomes ............................................................ 96

vii

 

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Figure 10

LIST OF FIGURES

Hunter’s (1985) Three Social Orders ...........................

Conceptual Model .................................................

Measurement Model ...............................................

Final Measurement Model for Conventional Activity ........
Final Structural Model for Minor Delinquency - self—report

Final Structural Model for Minor Delinquency — ofﬁcial ....

Final Structural Model for Severe Delinquency — self-report
Final Structural Model for Severe Delinquency — ofﬁcial

Final Structural Run for Alcohol and Drug Use — self-report

Final Structural Run for Alcohol and Drug Use — official

viii

.......... 48

......... 55

......... 8O

......... 83

......... 85

......... 87

89

.91

93

......... 95

CHAPTER 1

INTRODUCTION

Over the last several decades, poverty has both spread and intensiﬁed across the
urban areas of the United States (Jargowsky, 1997; Jargowsky & Bane, 1991; Massey &
Eggers, 1990). What has been particularly insidious is the increasingly concentrated
nature of this urban poverty. As cities lost residents to the development of the suburbs
and beyond, impoverished urban neighborhoods became increasingly poorer, as those
with any resources ﬂed the area (Wilson, 1987, 1996). Much higher levels of poverty
within individual neighborhoods has thus exacerbated the detrimental impact of
individual family poverty. The spread and intensiﬁcation of this social cancer, poverty,
has been given a new name, concentrated neighborhood poverty, and has been used to
label and characterize neighborhoods in which more than 40% of the residents live in
poverty (Brooks-Gum, Duncan, & Aber, 1997).

Recent US. Census statistics continue to reveal that concentrated poverty is most
often found in urban minority communities, as the persistently high levels of residential
segregation continue to perpetuate racial, economic, and social inequality. Thus, even
though the general poverty rate of 11.8% in 1999 was reported to be the lowest in twenty
years, minorities (e.g., 23.6% of Aﬁican Americans) and children (16.9%) continue to be
dramatically over-represented (U. S. Department of Commerce, 2000). The case for
minority children is particularly troubling; 27% of poor Black children live in hi gh-
poverty urban neighborhoods, while this is only true for 3% of White children

(Jargowsky, 1997).

 

Poverty does not exist in a vacuum. Research has continually documented that
when family poverty is exacerbated by concentrated neighborhood poverty, social
problems such as drug abuse, crime and delinquency, health and mental health problems,
child maltreatment, and many other social ills also substantially increase (Aneshensel &
Sucoff, 1996; Coulton, Korbin, Su, & Chow, 1995; Crane, 1991; Sampson, 1987;
Sampson, Morenoff, & Earls, 1999; Wilson, 1987). One of the most disconcerting and
oﬁen discussed of these social problems is the endemic levels of violence that continue to
persist in many disadvantaged urban communities across America, particularly in
reference to youth. In fact, the level of violence that occurs in many American
communities constitutes a public health emergency (Hammond & Yung, 1993; Koop &
Lundberg, 1992). As reported by Koop & Lundberg, one million people die prematurely
each year as the result of intentional homicide or suicide, and the leading cause of death
for both Black and White teenage boys is gunshot wounds. National surveys have also
consistently indicated that those at greatest risk for victimization of violent crime are
youth (Snyder & Sickmund, 1999).

Thus, while the overall levels of both adult and youth delinquency and criminality
have substantially decreased since 1993 (Blumstein & Wallman, 2000), violence
continues to pervade the urban landscape and has many detrimental consequences for
those residents who are living in segregated and poor neighborhoods. In addition to the
obvious mortality issues, exposure to violence among children and adolescents has been
shown to increase mental health disorders such as depression, anxiety, and even post-

traumatic stress disorder (Aneshensel & Sucoff, 1996; Bell & Jenkins, 1993; Martinez &

 

Richters, 1993) as violence in extremely disadvantaged neighborhoods tends to be more
public and thus visible in nature (Pynoos & Nader, 1990).

The causes and consequences of poverty, violence and other social problems are
multiple and mutually reinforcing in the poor urban areas of our nation. While the role of
the local community or neighborhood has been re-acknowledged over the last decade
(Brooks-Gunn et al., 1997; Coulton, Korbin, & Su, 1996), the ﬁeld of neighborhood
effects still lacks a complete understanding of exactly how neighborhoods impact
residents, particularly youth. Thus, the main goal of the current study is to investigate the
various pathways disadvantaged neighborhoods impact youth outcomes such as
delinquency and conventional activities. This includes both the direct impact of
neighborhood disadvantage as well as its inﬂuence on other important variables in youth
development such as the family microsystem, neighborhood mesosystem, and the
inﬂuence of peer relationships.

The current study has several objectives. First, an updated systemic model of
social disorganization will be evaluated to assess if neighborhood disadvantage impacts
adolescent development and behavior. Second, it will be argued that sense of community
provides a more valid and applicable measure of community social organization than
previous methods used to assess the important mediating variables in SD theory. Third,
the current study will evaluate how the neighborhood context inﬂuences parental
monitoring and support and the impact of this important variable on adolescent
development and behavior. The interaction between parenting style and neighborhood
environment will also be assessed to see if different styles are utilized for different

neighborhood environments, or if parenting style differentially impacts youth outcomes

 

depending on the local community context. Finally, the relationship between the local
community context, parenting practices, and youth’s afﬁliation with delinquent peers will
be assessed.

First, an introductory section will deconstruct the oft-held notion that modern life
has decimated the existence and importance of community for urban residents (Fischer,
1982; Freudenberg, 1986; Slovak, 1986; Suttles, 1972). Second, the development of the
Old-Chicago school and Social Disorganization theory will be presented, including a
discussion of the rise, fall, and re-emergence of updated versions of SD theory. The next
major section will review psychological conceptualizations of ecology and human
development and integrate this paradigm with sociological conceptualizations of
community theory. Fourth, returning to this study’s guiding theoretical framework, the
literature on updated systemic SD models, particularly those with the outcome measures
of violence, crime, or delinquency will be reviewed. Finally, recent literature on how
neighborhood disadvantage impacts parenting and family processes and youth’s
afﬁliation with delinquent peers will be reviewed and a list of speciﬁc research questions
addressed by this study will follow.

Sociological Theory and the Eternal Quest for Community

While community psychology has only recently emerged as a sub-discipline in
psychology that is concerned with deciphering how the environment impacts behavior
(Levine & Perkins, 1997), the ﬁeld of sociology has been documenting how the social
structure inﬂuences human behavior and functioning for a much longer time. As a
discipline, sociology emerged after the onset of industrialism and capitalist economic

systems, which created large urban centers that dramatically altered the demographic,

 

political, and social composition of previously agrarian societies. In the United States,
the urbanization and industrialization of America radically changed the demographic,
economic, and social structure, particularly from the mid-19th century to early 20th
century. For instance, between 1840-1880 the percentage of the population which
resided in urban centers more than doubled, from 11 to 28% (Miller, 1973).

Classical sociologists such as Toennies (1957) and more modern sociologists such as
Weber (1962) and Durkheim (1933) usually receive the most credit for documenting how
the accoutrements of industrialism and technological innovation dramatically altered the
social and political organization of communities, and indeed, societies. Many of these
classic sociologists used ideal types, a heuristic tool, to compare and contrast the
differences brought about by industrialization, technological advances, and urbanization
(e.g., Tonnies - gemeinschaﬁ/gesselschaﬁ, Weber - traditional/rational, Sirnmel -
rural/urban). Whether labeled gemeinschaft, traditional, or rural, this ideal type was
always portrayed as superior, even on the rare occasions that some of its negative aspects
were mentioned, compared to the urban polar type. For instance, while peaceful and
communal images were presented in descriptions of the rural typology (e. g., traditional
and sacred) equally value-laden, but negative language was used to describe the urban
typology. In the modern urban world, sacred traditions supposedly became outdated and
obsolete and intimate relationships and communal solidarity were replaced by superﬁcial
relationships and anonymity. While both a strength and weakness of ideal types are the
oversimplication of complex social systems, the biases in descriptions of these ideal types

often went unchallenged and continue to go unchallenged.

 

For instance, whether in reference to the 19th, 20“], or 21St century, the development of
locomotives, mass public transportation, or the more recent development and expansion
of the information superhighway, these industrial and technological advances have
always been proclaimed to change the basic nature of our society. While being lauded as
truly innovative, there was and continues to be a backlash against such breakthroughs and
advances. Similar to the descriptions by the classic sociologists, the main thrust of the
argument seems to be that we are losing an essential element through all this change and
technological progress — community. But, rather than automatically decreasing a sense of
community and connectedness among people, the one true constant regarding these
modern developments is that another technological breakthrough will soon occur and, it
too, will be subsequently followed by the same voices of community decline and
disintegration. Thus, while the common lamenting of the past by politicians and
academics may seem a recent and valid phenomenon, the fact is that sociologists,
journalists, and ordinary citizens have always complained about the decay of our urban
society and the need to do something dramatic to return to “the mythical golden era of
peace and tranquility in American neighborhoods” (Bursik & Grasmick, 1993, p.1).

While there are new trends and challenges that have emerged in modern day
America, and even though the intent of the current study is to better understand how
disadvantaged urban contexts impact youth, it is ﬁrst essential to question the often
unchallenged assumption that the quality of life in urban areas is constantly declining.
This is simply not true. There are many communities today that meet people’s physical,
social, emotional, and psychological needs, and the fact remains that the quality of life

has substantially improved since the rise of urban centers in the mid-19th century (Suttles,

1972). It is important to understand this inherent bias, worldview, or really archetype, if
research on neighborhood effects is ever going to be utilized to improve neighborhood
conditions and people’s quality of life. At the same time that this is forceﬁrlly argued,
unfortunately, there are many dangerous and alienating neighborhoods which do not
support the positive development of youth and adults. While this study is concerned with
the later, it is argued that there is hope that these neighborhoods can be revitalized to
become positive contexts for youth and adolescent development. And, the very real
danger of a misplaced, collective nostalgia for a mythical era of our past is that it can
only serve to divert attention and resources from a comprehensive effort to rebuild the
physical and social infrastructure of disadvantaged urban neighborhoods.
The Old Chicago-School: Ecology] Theory of Urban Dynamics and the Development of
Social Disorganization Theogl

While an extensive review of sociological theory is beyond the scope of this
paper, a discussion of the development of sociology in the United States, and especially
1y at the University of Chicago, is warranted since the grounding theory of the current
study lies in the development of an ecological theory of urban dynamics and growth of
the city, particularly as expounded by Shaw and McKay (1942) in their explanation of the
structural causes or antecedents of delinquency in social disorganization theory. The
sociology department at University of Chicago is credited with being the ﬁrst institution
in the United States which assessed the impact of America’s urbanization in the early to
mid-19008. In The Cig, Park, Burgess, and McKenzie (1967) presented an ecological
theory, borrowed from biology’s attempt to understand how plant life adapted to

changing environments, regarding how humans adapted to their rapidly changing

environment. Speciﬁcally, the authors were interested in how people adapted to the rise
of urban centers. The old Chicago-school was concerned with measuring and assessing
the impact of this expansion of our cities and the concomitant changes in social life for its
residents.

In the second chapter, Burgess proposed his inﬂuential concentric zone theory, in
which he argued that each successive concentric circle represented the extension or
growth of a city from the original circle, which represented the central business district
(the Loop in the case of Chicago). From these zones, one could predict the type of
physical structures, businesses, and demographic characteristics of the individuals who
had chosen to locate there. Basically, the poorest and least attractive housing and
neighborhoods were found directly outside the central business district, followed by more
and more attractive neighborhoods characterized by higher standards of living and
considerably fewer social problems (e. g., crime, prostitution, drugs). As each social
group gained more ﬁnancial resources and social status, there was an effort to move
outward to a better community. This resulted in expansion of the city, the natural
tendency for each inner zone to extend its area by invading the adjacent outer zone.

Thus, cities were in a constant state of change and expansion, and this was especially true
of late 19th and early 20th century America when transportation and communication
advances converted previous walking cities of ﬁve to eight miles to extended
metropolises more than quadrupling in size (Miller, 1973).

The old Chicago-school was concerned with how this growth process affected the
social organization of communities that were in a constant state of transformation. So,

the primary area of interest for researchers was to assess how neighborhood change and

transformation impacted both the residents and the neighborhood itself. Or, as Wirth
(1947) stated, “The central problem of the sociologist of the city is to discover the forms
of social action and organization that typically emerge in relatively permanent, compact
settlements of large numbers of heterogeneous individuals” (p.9). It was postulated that
as communities expanded and incorporated outer zones, neighborhoods would go through
massive changes due to population increase and turnover (invasion) and the commrmity
would be in a state of disorganization until, after some time, it stabilized into a new outer
zone (succession). Therefore, the present level of invasion and succession in a particular
neighborhood could predict the social organization of the community. According to this
ecological theory of urban dynamics, social problems could be found in their most acute
forms in communities undergoing these rapid population changes - in “disorganized”
communities.

Shaw and McKay (1942) extended this ecological approach to the speciﬁc area of
delinquency. These two sociologists are largely credited for popularizing a social
ecological theory of delinquency, social disorganization theory, which explained how
poor urban environments impacted adolescent development and delinquent behavior.
Their main ﬁnding was that the association between neighborhood residence and
delinquency decreased as the distance from the central city increased and that this
association remained despite the rapid changes in the ethnic and racial characteristics of
residents. Thus, variations in crime and delinquency rates reﬂected the structural and
social characteristics of local communities more than they reﬂected the personal

characteristics of residents who happened to live there. In general, social disorganization

theory has been deﬁned as the inability of local communities to realize the common
values of their residents or to solve commonly experienced problems (Komhauser, 1978).

In its severe form, social disorganization leaves residents isolated ﬁom one
another and from the social institutions that are supposed to provide basic services and a
reasonable quality of life. The lack of residential stability and presence of a
heterogeneous population make it extremely difﬁcult to establish a strong network of
relations or “weak ties” within the community that serve to establish norms and a
supportive context for child development. In terms of formal community structures, the
lack of neighborhood stability interacts with low socioeconomic composition and results
in a paucity of quality neighborhood institutions (e. g., schools, social service agencies)
which serve to bind residents together and provide essential services to them, particularly
youth. SD theory is a systemic model which incorporates formal associations as well as
the informal networks within a community that arise through friendship and kinship ties
(Kasarda & J anowitz, 1974).

SD theory posited that it was the level of community social organization that
mediated the relationship between a neighborhood’s compositional or structural
characteristics and delinquency rates. Thus, social disorganization and social
organization are on opposite ends of a continuum that describes a neighborhood’s
capacity to exert control over the behavior and activities of residents and non-residents
(Sampson, 1993a). This distinction is critical because confusion has arisen due to the
misuse of the theoretical framework in the past. For instance, social disorganization has
been used as a descriptor of disadvantaged environments (e. g., structural disadvantage),

the mediating social process (e. g., social organization/disorganization), and ultimate

10

outcomes (e.g., delinquency and crime; Bursik, 1988). Rather than simply describing the
structural characteristics of communities or community outcomes, social disorganization
theory should be viewed as an explanatory framework that describes the entire process of
how most neighborhoods are negatively impacted by adverse structural conditions.
Histogof the Inﬂuence of SD Theory on Sociological, Criminological, and
Psychological Incgiry: The Rise. Fa_ll,_and Re-emergence of SD Theory

While popular throughout the ﬁrst half of the 20th century, SD theory fell into
disfavor during the 1960s through the 1980s for several valid theoretical and empirical
reasons (Bursik, 1988). This section will review the various criticisms and limitations of
SD theory and address how updated systemic models of SD are adequately dealing with
these issues.

The central issue was that social disorganization lacked empirical data linking the
set of proposed structural variables to variations in community social organization and,
ultimately, differential youth outcomes (Bursik, 1988). While structural information such
as residential mobility and poverty rates could be easily obtained via census data,
collection of community social organization data was very costly and time consuming
because it required that interviews be conducted for a large number of neighborhoods
throughout an entire city (Heitgerd & Bursik, 1987; Sampson, 1993b). Moreover, a
macrosociological theory such as SD was inherently difﬁcult to validate empirically,
because both a strength and weakness of the theory is that it ties social structural
conditions to individual behavior. It is extremely difﬁcult to assess such macrolevel

constructs or contextual effects on individual behavior (Coulton et al., 1996; Sampson,

11

1991; Shin, 1996), and only recent advances in methodological and statistical tools have
allowed the ﬁeld to discern such effects in an empirically valid manner.

The second main limitation of SD theory was that the majority of data collected to
support this theory was cross-sectional. Thus, the ﬁeld was unable to truly model how
ecological change impacted human development and functioning in a manner that did
justice to the basic tenets of the ecology theory of urban dynamics. After all, the main
area of investigation for the old-Chicago school revolved around understanding how the
process of neighborhood change, through invasion and succession of different
populations, changed the physical, social, cultural, and economic landscape of local
communities. Understanding this process required longitudinal studies of local
communities rather than cross-sectional studies, which only have the ability to assess one
point in time. While there are obvious ﬁnancial and practical reasons for the lack of
longitudinal neighborhood projects, it was nonetheless surprising and problematic,
especially since change and adaptation are the central components to both ecological and
social disorganization theory.

Moreover, as discussed earlier, the landscape of urban America has dramatically
changed since SD theory was ﬁrst developed in the early part of the twentieth century.
This valid critique recognizes the lack of attention paid to extra-community dynamics
such as: public policy, discrimination and segregation, land-controlling elite, change from
a manufacturing to a service economy and the corresponding decrease in high-wage and
low-skill jobs, and the increasing concentration of poverty and other indicators of
disadvantage in urban areas (Coulton et al., 1995; Hirsch, 1998; Jargowsky, 1997;

Jargowsky & Bane, 1991; Logan & Molotch, 1987; Wilson, 1987, 1996).

12

Updated systemic models of social disorganization have consciously incorporated
these effects to a much greater degree. A good example of such recognition is seen in a
re-analysis of data that was originally collected by Shaw and McKay. On the South Side
of Chicago the African-American population was isolated by discriminatory housing
policies in a small area known as the Black Belt until 1948 when the Supreme Court
struck down race-restrictive covenants in housing policies. As African-Americans slowly
gained greater mobility and choice in housing, there was tremendous Opposition by the
surrounding ethnic white neighborhoods, which resulted in numerous racial conﬂicts, real
estate speculation, and white ﬂight to the suburbs (Bursik & Webb, 1982; Hirsch, 1998).
While this study and re-analysis comes from Chicago, this same sequence of events
occurred throughout the industrial cities of the Midwest and East coast (Sugrue, 1996).
Obviously, Burgess’s concentric zone theory and invasion/succession principles captured
in SD theory were unable to explain the inﬂuence of these ‘unnatural’ forces (e. g.,
racism, discrimination) in neighborhood change. The result was that Shaw and McKay’s
(1942) important theoretical ﬁnding that delinquency rates remained relatively stable
despite continuous changes in the racial and ethnic composition of the community proved
to no longer be valid.

However, as Bursik and Webb (1982) demonstrated in a re-analysis of the
original data, social disorganization still maintained validity if one looked at the nature
and pace of change in the racial and ethnic composition, which dramatically differed
from the past. Community change in racial composition in this era was characterized as
foothold change, turnover change, or entrenchment change. Foothold change indicated

an increase of families of color in a neighborhood by at least 10% over ten years but

13

where they remained in the minority, while turnover change represented an increase of at
least 10% but where families of color moved from minority to majority status.
Entrenchment change occurred when families of color increased their composition by
10% and were in the majority in the community for all ten years. The main ﬁnding of
this re-analysis was that delinquency rates signiﬁcantly increased for foothold and
turnover change but remained stable for entrenchment change: “The most established
nonwhite, changing communities [entrenchment areas] had delinquency rates not much
different than would have been expected from their previous patterns” (Bursik and Webb,
1982, p.39).

As these researchers concluded, the variation in delinquency patterns reﬂected the
nature and pace of racial change rather than the speciﬁc groups involved. The incredible
patterns of population turnover during this era excluded the development of an
institutional and social network base that was responsible for keeping delinquency rates
stable among Chicago neighborhoods up to 1950. Therefore, social disorganization
theory still retained validity if one analyzed the external social forces (e.g.,
discriminatory housing practices, racism, white ﬂight) that dramatically altered the
gradual process of invasion/succession for Chicago neighborhoods. In fact, this ﬁnding
should ﬁrrther support the underlying dimension of social disorganization theory, namely
that the rate of neighborhood change is more important than whoever is involved.
Another recent SD study that accounted for these external forces, as well as for the
confounding variables of concentrated poverty and race, found that White and African-
American youth had the same delinquency rates when neighborhood poverty was held

constant (Peeples & Loeber, 1994). These researchers also found that concentrated

l4

poverty was mainly concentrated in African-American neighborhoods. As these authors
concluded, “As Shaw and McKay noted, it is impossible to reproduce for whites the
conditions under which Aﬁican Americans live. This is just as true today: Urban whites
do not, to any appreciable degree, live in underclass neighborhoods” (p.144). Updated
social disorganization models need to be able to explain these important social, political,
and economic forces, both internal and external to the neighborhood, which alter
neighborhood composition, growth, and development as evidenced by these examples.

The third major limitation of SD theory was the widespread confusion regarding the
causes and effects of SD theory, which led to misunderstandings in articulating and
evaluating the model (Bursik, 1988). Many theoreticians criticized Shaw and McKay for
not clearly differentiating between the causes and effects of SD and utilizing the effects
of SD as evidence of disorganization itself in a circular argument. While this is not an
entirely valid argument, it certainly shows the complexity of their theory, which not only
spanned various levels of analysis (community, individual) but also encompassed aspects
of subcultural, strain, and control theories of crime and delinquency (Komhauser, 197 8).
Once again, recent conceptual and methodological advances have allowed proponents of
updated systemic models of SD to better model and measure key aspects of the theory
and to clarify causes and effects.

The fourth main issue regarding SD theory is that the outcome measures of many SD
studies have consisted of official recorded delinquency. There has been long-standing
debate in the ﬁeld of criminology as to whether ofﬁcial records are reliable and valid
indicators of delinquency participation. In general, ofﬁcial records have been criticized

as simply reﬂecting the biases in police practices and record keeping, while self-report

15

measures have been criticized for equating minor delinquency with the more serious
infractions that comprise the uniform crime reports (Hagan, Gillis, & Chan, 1978;
Sampson, 1986). Thus, it is important for current studies to include both self-report and
official records of delinquency.

Another major impediment to the development of the SD ﬁeld has been the lack of
agreement on the basic methods used to measure what is labeled community, contextual,
or neighborhood effects. Studies have generally utilized census tract demarcations as a
measure of the community, however this practice has been strongly criticized as not
ecologically valid by many theoreticians (Coulton et al., 1995; Crew, Kim, & Schweitzer,
1999; Sampson & Raudenbush, 1999). While this has always been a contentious issue, it
certainly has not decreased the number of studies on neighborhoods. Instead, it has led to
the development of many competing conceptualizations and measurements of
community, and may well explain the sometimes contradictory ﬁndings in neighborhood
studies.

Overall, while the aforementioned problems limited development of SD theory, or at
least were responsible for its decline in popularity during the 19605 through the 19808,
updated systemic SD models have dealt adequately with these problems. While these
issues have not been entirely reconciled, advances have allowed for a much better
understanding of how the structural and social conditions of neighborhoods inﬂuence
people. As a result of conceptual and methodological advances, SD theory has been
dusted off, reformulated, and utilized as one of the guiding frameworks to understand
neighborhood effects. Despite the numerous changes in the urban landscape over the past

century, it is a strong testament to the underlying assumptions of the ecological theory of

16

urban dynamics that social disorganization continues to be used as a theoretical and
conceptual ﬁamework for understanding the impact of the urban environment on youth
outcomes.

The current study combines an updated model of social disorganization theory with
community psychological theory to understand how social structural conditions impact
community social organization and, ultimately, individual youth behavior. Community
psychological theory, as discussed in the next section, bridges typical strict sociological
and psychological paradigms to better understand the connection between macrosocial
conditions and their link to the micro world of individual development and behavior.
Ecological Perspective of Human Development and Neighborhood Conceimtualization

While this manuscript has thus far mainly focused on sociology’s use of
ecological theory to explain macrolevel adaptation of human populations to urban
centers, the ﬁeld of psychology has contributed greatly to our understanding of more
microlevel phenomenon, such as the interaction between individuals and their
environments. Moreover, the ﬁeld of psychology has also signiﬁcantly contributed to
understanding how family and individual level-factors inﬂuence behavior, particularly in
the decades when SD theory fell in disfavor and more individual-level analyses of crime
and delinquency were the norm (Sampson, 1991, 1993b).

The utilization of ecology or ecological principles in psychological research is
also borrowed from environmental biology and employed as a metaphor to suggest the
need to go beyond the individual level and understand how the environment shapes
human behavior (Levine & Perkins, 1997). Psychology’s use of the ecological metaphor

can be mathematically represented by Lewin’s (1935) equation [B = f (P,E)], which

17

emphasizes that development or behavior is a ﬁrnction of the person, the environment,
and their interactions. Unlike sociological theory, rather than describing how
environmental characteristics impact groups of people, psychology brings the analysis
down to the individual person. This includes a focus on individual traits, motivations,
experiences, fears, and other characteristics that impact not only the individual, but those
around him or her and the greater environmental context.

Expanding on Lewin’s classic equation, Bronfrenbrenner (1979) argued that there
existed a number of ecologically nested environments that inﬂuenced individual
development, from those most immediate settings (e.g., family, home, and neighborhood)
to more distal or macrosocial environments (e.g., city, country, and culture).
Bronfrenbrenner’s ecological theory of human development differentiated important
developmental settings, which he labeled microsystems, and how they interacted to affect
human functioning and capacity. As he so eloquently argued, the majority of
psychological research is conducted out of context in that the focus is solely on the
person or on the person in one speciﬁc setting. Unfortunately, this limitation was also
further exacerbated by the fact that the setting was usually an artiﬁcial psychology lab
where external inﬂuences could be constrained and minimized for experimental purposes.

Thus, while speciﬁc behaviors could be viewed and isolated in a lab setting, the
natural inﬂuence of the various levels of the environment was purposely restricted.
Bronfrenbrenner argued for the need to view human behavior and development as
occurring in multiple ecological environments which produce independent effects, but
also interact to affect development in a complex and multifaceted manner. He

graphically represented these ecological contexts as a series of concentric circles nested

l8

within each other to Show the multiple layers of the environment, which he labeled
microsystem, mesosystem, exosystem, and macrosystem.

Thus, in a very similar fashion to Burgess’s concentric circle theory, which
emphasized the growth of urban areas and populations, Bronfrenbrenner also utilized an
embedded graphical display to illustrate how the various levels of community context
impact individual development. Consequently, the contribution of the ﬁeld of
psychology to this area of study was to assess how human thought and behavior played
out in the structural and social conditions of the urban environment. The ﬁeld of
psychology placed the emphasis on understanding how individual-level characteristics
and family dynamics may impact, and are impacted by, the environment. In
Bronfrenbrenner’s model, microsystems, represented by the innermost circle, are the
more proximate physical and social settings, such as the family unit or elementary school
for a child, while the mesosystem, the next distinct nested layer, represents the
interrelations or interaction of two microsystems in which the developing individual
actively participates. An example of the interaction between two microsystems would be
when parents discuss their children’s performance in school with the classroom teacher.
The exosystem includes settings that do not directly involve the developing individual per
se, but which nonetheless impact and are impacted by the setting in which the developing
person resides. In the case of a child, this would include his or her parents’ network of
associations in the local neighborhood or workplace. In the outermost concentric circle,
the macrosystern represents the broader economic, political, and social context of the

culture.

19

As a child grows and develops, he or she is presented with an increasing number
of microsystems, mesosystems, and exosystems, which must be navigated for successful
development. While the majority of neighborhood effects research and prior community
development programs have utilized census tract demarcations (Elliott et al., 1996;
Levanthal & Brooks-Gunn, 2000; Sampson, 1997), this focus on one setting severely
limits our understanding of the important transactions that occur as individuals navigate
the multiple and layered ecological contexts of their environment. Similar to the
laboratory setting, the artiﬁcial nature of census tracts imposes a constraint that does not
reﬂect the everyday experience of people in their neighborhoods. Residents may not only
think of their neighborhood differently, but they also are not limited to the boundaries
imposed by census tracts. Adults and youth travel in and outside of their neighborhood,
and areas outside the tract may have very important inﬂuences on them. For instance, in
the case of youth, their school and other friends may lie outside the census tract in which
their home is located. Thus, an ecological conceptualization of human development
warrants looking at multiple levels of neighborhood environments and how they
independently and conjointly affect individual youth.

One way to address this issue is to focus on a much smaller, objective, and
ecologically valid conceptualization of the urban landscape — the face-block. While
research has documented the subjectivity of what residents deﬁne as their neighborhood
(Coulton, Korbin, Chan, & Su, 2001), the face-block constrains residents to think of their
neighborhood in a consistent manner. The face-block consists of houses on both sides of
the street that are intersected or bounded by cross-streets or a similar geographic

demarcation such as dead-ends and railroad tracks (Unger & Wandersman, 1982). In

20

addition to readily identiﬁable objective boundaries, urban residents are more likely to
know each other, participate in block level organizations or associations, and monitor and
supervise activities at the block-level versus larger conceptualizations of neighborhood
(Perkins, Florin, Rich, Wandersman, & Chavis, 1990; Smith, Frazee, & Davison, 2000).
Research on this conceptualization of neighborhood has also established both its
reliability and validity as a measurement of the neighborhood environment (Appleyard,
1981; Brower, Dockett, & Taylor, 1983; Perkins & Taylor, 1996; Taylor, Gottfredson, &
Brower, 1984; Unger & Wandersman, 1983). Furthermore, another major strength of a
block conceptualization of neighborhood is that face-blocks can be easily aggregated up
to larger neighborhood units and thus the distinct layers of the urban environment can be
assessed independently or simultaneously.

While Bronﬁenbrenner’s ecological model is a useﬁrl heuristic to conceive of
human development, the numbers of systems (e. g., microsystems, mesosystems) quickly
accumulate and there is a need for a simpler, and in the case of neighborhood studies,
geographically based way to conceptualize the neighborhood’s inﬂuence on human
behavior. Hunter’s (1985) model of social orders presents a simpler yet elegant way to
conceive of the various levels of neighborhood context and how they inﬂuence human
behavior. Speciﬁcally, Hunter proposed three distinct levels of community which impact
neighborhood residents: private, parochial, and public social orders. An additional
strength of this model is that it already has been successfully incorporated into updated
systemic models of social disorganization (Bursik & Grasrnick, 1993; Taylor, 1997), and
it is also the guiding conceptual ﬁ'amework for neighborhood development programs

throughout the state of Illinois (Leverentz, 2001).

21

As displayed in Figure 1 (for comparative purposes, Bronfrenbrenner’s four
systems are listed in their corresponding social order), the three social orders are easily
distinguishable by their size and the various methods used to achieve social order and
control. The private social order represents the most immediate physical and social arena
around an individual’s home — the face-block or block. Although this interpretation is
congruent with Hunter’s, it must be acknowledged that the current formulation places
more emphasis on the importance of geographic proximity in the private social order.
The private social order contains the intimate and also informal relations that develop
over time with the neighbors directly surrounding a resident’s home. These are the type
of relationships that develop among neighbors who provide instrumental support, such as
the lending of tools or direct assistance, and the emotional attachment and support that
comes from day-to-day contact (U nger & Wandersman, 1982). In this conceptualization
of the neighborhood, shared norms exist about the appropriateness of public behavior
and, if broken, can result in direct criticism, ridicule or ostracism from fellow neighbors
(Black, 1989).

The parochial social order emanates outward from the area surrounding an
individual’s home to incorporate the larger and more typically conceived
“neighborhood”, which includes institutions and resources such as schools, places of
worship, and community-based organizations. The parochial level of community
captures the social attachments among close neighbors as well as the relationships that
are not so well established or relationships with those individuals whose geography
results in less daily or weekly contact. This level also represents the more formal aspect

of relationships dictated by community institutions, such as the local school or market

22

exchanges at the local grocery store. The public social order, the third and ﬁnal
conceptualization of community, addresses prior critiques of SD theories by representing
the larger social, economic, and political forces which strongly inﬂuence neighborhood
dynamics at the parochial and private levels of community. These are the external forces
that shape growth of cities in natural and unnatural (racism, land-controlling elite) ways,
as many social disorganization critics and urban scholars have noted (Hirsch, 1998;
Logan & Molotch, 1987). As has already been extensively documented and discussed,
these are the same macrosocial variables that disproportionately and negatively impact
poor minority neighborhoods in urban areas (Wilson, 1996).

Thus, the current study utilizes an updated model of social disorganization theory,
integrates psychological and sociological theory of ecology and hmnan development, and
conceptualizes neighborhood inﬂuence at three distinct levels or social orders to
understand how neighborhoods impact youth development. Since social disorganization
is the grounding theoretical framework for the current study, recent literature on
neighborhood effects via this paradigm will be reviewed and synthesized.

Current Nei borhood Effects Research

Since the late 19803, the importance of the local neighborhood environment has
been reacknowledged as statistics on concentrated poverty and its impact on children and
youth have reached beyond academia through popular books such as There are no
Children Here, The Truly Disadvantage_d,_and Savage Inequalities (Kotlowitz, 1991;
Kozol, 1991; Wilson, 1987). In the academic research community, neighborhood effects
research exploded during the 19908 and studies have quickly accumulated which

document the signiﬁcant role the neighborhood mesosystem plays in the outcomes of

23

residents, particularly in the development of children and youth (Brooks-Gunn et al.,
1997; Coulton et al., 1995; Gonzalez, Cauce, Friedman, & Mason, 1996). Most of the
research on poverty, or what is more generally labeled neighborhood disadvantage or
neighborhood effects, falls into one of ﬁve camps: neighborhood institutional resource
models, contagion or epidemic theories, collective socialization theories (SD theory),
competition theories, and relative deprivation theories (Jencks, 1990; Levanthal &
Brooks-Gunn, 2000).

While not mutually exclusive, each model stresses a particular pathway through
which disadvantaged neighborhoods impact their residents. For instance, neighborhood
institutional resource models stress the existence and quality of important youth
developmental settings such as schools, community centers, and social service
organizations, while contagion/epidemic models emphasize the importance of peer
networks and postulate that negative peer systems are more abundant in disadvantaged
neighborhoods. Collective socialization theories focus on the important role of
community social organization, which includes the development and enforcement of
community norms, supervisory capabilities of adults, and presence of adult role models.
Thus, those studies that utilize an updated systemic model of social disorganization
would be included in this camp. Competition theories emphasize how neighborhoods
compete for a ﬁnite amount of resources, while relative deprivation theories stress the
perceptions of residents’ own neighborhoods assets and problems within the context of

the surrounding neighborhoods and metropolitan area.

24

Updated Systemic Models of Social Disorganization or Collective Socialization

The current study utilizes a social disorganization or collective socialization
framework to investigate neighborhood effects, although it is important to note that
aspects of SD theory also correspond to institutional and contagion theories. As
discussed earlier, social disorganization impacts community social organization
informally by affecting residents’ relationships and ties to each other, and more formally
through the reduction of neighborhood organizational and institutional resources.
Aspects of SD theory also correspond to the contagion model in that Shaw and McKay
(1942) acknowledged the existence of multiple norms and values, which give rise to
networks of deviant peers and adults in these neighborhoods. Overall, while these
different theories about neighborhood effects emphasize different ways in which
neighborhood disadvantage affects individuals, there is some overlap, particularly among
collective socialization, institutional, and contagion models. Due to the recent
proliferation of neighborhood effects studies, only those investigations that utilize a SD
or collective socialization framework will be reviewed here. Additionally, since
delinquency is the main outcome variable of the current study, the subsequent literature
review will focus on studies which include crime, delinquency, or some measure of
violence as a main outcome variable.

As previously mentioned, one of the main criticisms of the social disorganization
model was the lack of empirical support for the proposed intervening relationship
between neighborhood disadvantage and delinquency (Byme & Sampson, 1986). A
number of recent studies have addressed this and other major problems outlined earlier,

thus resurrecting SD theory as one of the major conceptual frameworks through which to

25

 

 

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investigate the impact of neighborhood disadvantage on youth outcomes, particularly in
the ﬁeld of delinquency research (Bursik & Grasmick, 1993; Levanthal & Brooks-Gunn,
2000; Sampson, 1991, 1993b). Simcha-Fagan & Schwartz’s (1986) study marked the
return of social disorganization theory by empirically demonstrating that the level of
social organization in neighborhoods mediated much of the effects of disadvantaged
structural characteristics on self-reported and ofﬁcially recorded delinquency. Since the
publication of this seminal article, a number of studies utilizing SD theory have
conﬁrmed that the level of social organization in communities mediates a signiﬁcant
amount of the effects of structural characteristics on delinquency, victimization, and
general levels of violence (Elliott et al., 1996; Sampson & Groves, 1989; Sampson,
Raudenbush, & Earls, 1997). Unfortunately, as the hypothesized theoretical link between
neighborhood disadvantage and delinquency has continued to receive empirical support,
the ﬁeld’s sophistication in conceptualizing and operationalizing the mediating variable
of SD theory has been limited.

As Table 1 indicates, there have been a number of ways that the mediating
variable of community social organization has been operationalized and empirically
supported. Unfortunately, the lack of a consistent, standardized measure inhibits
comparisons across studies and thus limits the advancement of the ﬁeld’s understanding
of how ecological change impacts the social fabric and networks of communities, and
ultimately, youth outcomes. As illustrated by Table 1, there have been two major ways
of measuring community social organization that have been empirically demonstrated.
One method is to measure the level of ﬁiendship networks or contacts in the

neighborhood, which emerged from the theoretical tradition of emphasizing the

26

importance of social networks and weak ties (Crenson, 1978; Elliott et al., 1996;
Granovetter, 1973; Sampson & Groves, 1989; Warner & Rountree, 1997; Warren, 1978).
The second method is to assess the informal social control processes that operate at the
neighborhood level (Elliott et al., 1996; Sampson & Groves, 1989; Sampson et al., 1997).
Informal social control was usually measured by the likelihood that neighborhood
residents would intervene if children and teenagers were engaging in minor “delinquent”
behaviors or by the degree of organizational participation in informal and formal
community groups. Table 1 illustrates that informal social control has received more
empirical support, especially as of late, and is being utilized to a greater degree than
friendship networks to measure the level of community social organization. Logically,
informal social control taps into the ability of a community to realize its common values
and regulate behavior that would be harmful to the collective. Moreover, there has been
extensive discussion over the years on the important role of informal social control in
controlling crime and delinquency (Greenberg & Rohe, 1986; Sampson et al., 1997).
While these two methods may seem to tap into the same construct, upon closer
inspection, it is evident that one acts as a catalyst that necessarily precedes the other.
Speciﬁcally, the degree to which families, neighbors, and local institutions interact and
socialize youth is part of the process of a community realizing its common values and
developing shared norms. Once consensus is reached, it is communicated informally
ﬁ'om neighbor to neighbor and more formally through a community’s institutions. Only
when such shared norms exist are residents emboldened to intervene when these norms
are being violated. In other words, shared norms must obviously exist before one can

intervene when they are being violated. Thus, informal social control and related

27

intervention behaviors should be viewed as outcomes of community social organization
rather than as true measures of community social organization itself. Even though some
of the newer studies have incorporated items that measure informal social processes of
community cohesion in addition to intervention items (Sampson et al., 1997), there
continues to be an over-reliance on behavioral indicators of community social
organization. Moreover, the few studies that have assessed social processes such as weak
ties and neighboring have found inconsistent results, leading to questions about the
validity of the model, or at least how to best measure the social processes that lead to
informal social control (Macoby, Johnson, & Church, 1958; Sampson & Groves, 1989;
Warner & Rountree, 1997).
Sense of Comqu

A critical next step for the ﬁeld is to develop or agree upon a measure that
assesses the social processes that are required for informal social control and intervention
behaviors with youth in the community. Recent studies have noted this need and asked
researchers to incorporate measures that move beyond behavioral indices to measure the
various social processes that are inherently embedded in the complex and reciprocal
relationships among community social organization, informal social control, and crime
and delinquency (Bellair, 2000; Veysey & Messner, 1999). Sense of community may be
an effective and accurate measure of such social processes. SOC has been deﬁned as “a
feeling that members have of belonging, a feeling that members matter to one another and
to the group, and a shared faith that members’ needs will be met by their commitment to
be together” (italics added; as cited in McMillan & Chavis, 1986, p.9). As noted over

two decades ago (Sarason, 1974), “It [sense of community] is a phrase associated with a

28

kind of maudlin togetherness, a tear-soaked emotional drippiness that misguided do-
gooders seek to experience” (as cited in Chavis, Hogge, McMillan, & Wandersman,
1986, p.24). While Sarason sardonically pointed out its “non-scientiﬁc” nature, it is
precisely the shared emotional and communal quality of this variable that captures the
complex and subtle social processes necessary to form cohesive and supportive
communities.

In conjunction with the above deﬁnition, McMillan & Chavis (1986)
conceptualized four distinct aspects of SOC: membership, inﬂuence, sharing of values
with an integration and fulﬁllment of needs, and a shared emotional connection. Thus,
for SOC to exist in a residential neighborhood setting, residents must identify with the
community, feel that they matter to the community and that the community matters to
them, feel that the community shares their values and meets their needs, and experience
affective attachments with other community members. As the above deﬁnition indicates,
SOC measures the emotional and social processes that precede direct intervention and are
usually enforced through subtle behaviors such as the withdrawal of sentiment, respect
and esteem, and social and instrumental support (Black, 1989; Hunter, 1985).

In addition to the argument that SOC provides a more accurate and valid measure
of community social organization, another advantage is the applicability of the measure.
For example, an evaluation of a program which only utilizes the outcome variable of
informal social control may show no effect when, in reality, a considerable amount of
social change has occurred in the community. Or, as has been found in previous research
(Perkins, Wandersman, Rich, & Taylor, 1993), neighborhoods with higher levels of

informal social control may seem to have more crime because residents report more to

29

the police, whereas a neighborhood with more crime may seem to have fewer problems
because people are afraid to call the police out of fear of retaliation. In fact, this has been
extensively documented as one of the major reasons why residents in high-crime
neighborhoods do not “get involved” (Korbin & Coulton, 1997). Moreover, there are
many different ways of intervening with youth and most studies fail to distinguish
between informal intervening which includes speaking directly to the youth and/or his or
her parents, versus formal intervening, which involves calling the police or other formal
agencies. There is a vast difference between these two types of intervening and the fact
that in some communities problems can be solved by speaking directly with the involved
youth and/or parents while in other communities problems can only be solved by calling
the police. The former speaks to a community with extensive social networks,
established norms, and a lot of informal social control where problems are solved directly
and locally, while the latter speaks to a lack of informal social control and reliance on
formal community structures and agencies.

The development of SOC within a neighborhood is a continual and dynamic
process, which requires extensive and positive interactions with fellow community
members (McMillan & Chavis, 1986; Unger & Wandersman, 1982, 1983). In
neighborhoods with a high degree of SOC, social ties are strengthened and extended as
community members realize that they not only share a common identity and history, but
more importantly a common future. And, as the research is beginning to document, the
ﬁrture of the neighborhood is intricately tied to some of the most important outcomes

individuals and families, such as safety, access to quality neighborhood resources, quality

30

of life, and economic opportunity (Brooks-Gunn et al., 1997; Coulton et al., 1996;
Coulton et al., 1995).

Both SD theory and SOC stress the importance of neighborhood consensus on
goals and values for the community, particularly with issues that have the potential to
affect all residents in the community. Rather than a restrictive or invasive social control
process, both theories emphasize the development of norms and guidelines to ensure a
high quality of life in the residential environment. For instance, one basic need for all
communities, as previously noted, is the ability to form a safe environment where
residents are free from victimization. In this respect, neighborhoods that lack consensus
or the ability to realize such a basic community goal can be labeled as having little sense
of community, or alternatively, as being socially disorganized. In accordance with the
deﬁnition of social disorganization, SOC taps into the informal social processes and
connections that are necessary for a community to self-regulate and inhibit harmful
behaviors. Moreover, utilizing SOC as a measure of community social organization
improves upon the current mediating variables in social disorganization theory, which
tend to focus on behavioral indicators or outcomes of social organization rather than the
process itself.

Since SOC’s conceptualization, research has demonstrated its importance to both
neighborhood and individual-level outcomes. For instance, SOC has been found to relate
to the amount of emotional and instrumental support individuals provide to neighbors
(Unger & Wandersman, 1982) and also has a positive effect on psychological health in
adults (Davidson & Cotter, 1991). SOC has also been found to inﬂuence the degree to

which residents work on common public problems, as well as participate in the political

31

process (Chavis & Wandersman, 1990; Davidson & Cotter, 1989, 1993). For youth, SOC
has been found to signiﬁcantly reduce adolescent loneliness and to be more important in
this respect than levels of social support (Pretty, Conroy, Dugay, Fowler, & Williams,
1996). Most signiﬁcant in terms of using SOC as a mediating variable in SD theory,
prior research has documented SOC as a quantiﬁable neighborhood level construct which
can be targeted in designing intervention and rehabilitation programs for disadvantaged
urban neighborhoods (Buckner, 1988; Chavis, Hogge, McMillan, & Wandersman, 1986;
Glynn, 1986; Kingston, Mitchell, Florin, & Stevenson, 1999; Pretty, 1990).

In summary, there is a need within the social disorganization theoretical
framework for a more comprehensive, applicable, and valid construct of community
social organization than informal social control and related intervention behaviors. As a
measure of the mediating variables of SD theory, sense of community goes beyond
behaviors and would be able to quantify if shared norms and social networks are
developing within communities. Thus, this construct would be much more useful in
community assessments and could inform community revitalization and building
programs on how and where to proceed to eventually attain the goal of increased informal
social control and safety in the neighborhood.

Measuring SOC

While the four proposed dimensions of SOC, membership, inﬂuence, fulﬁllment
of needs, and a shared emotional connection, have long been discussed, empirical
evidence has not fully supported them, resulting in varying conceptualizations and
measures of SOC over the years (Chipuer & Pretty, 1999). Some scales ask about

neighboring and neighborhood participation while others do not, some measures refer to

32

the respondent’s block, some to the local neighborhood, and a couple even refer to the
respondent’s experiences throughout their entire city. There has also been considerable
disagreement over whether SOC is a unidirnensional or multidimensional construct (Hill,
1996). While evidence seems to be in favor of a multidimensional construct, the exact
factor structure of SOC has not been conﬁrmed. While the dimensions of this important
construct remain elusive, rather than deterring research, it should simply indicate the
diversity of the community experience (Please see Table 2 for a description of prior SOC
measures).

Simply put, like people, all communities are distinctive. Thus, it is unlikely that
any one measure of SOC is going to capture all the important dynamics across various
communities (e. g., urban/rural, poor/wealthy, stable/transitory, territorial/non-territorial).
Given the debate over what exactly constitutes the important elements of sense of
community, the conceptualization used for this study attempted to assess its most basic
and vital components — the shared emotional connection among neighborhood residents
and the feelings of inﬂuence and empowerment that lead conununity members to
establish shared norms and solve locally experienced problems.

Of course, it is also readily acknowledged that healthy communities ﬁrst require
an adequate level of physical security and safety, and unfortunately, most researchers
have neglected to include this dimension in their conceptualization and measurement of
SOC. Since the ﬁeld of neighborhood effects usually attempts to identify how poor
urban environments affect adolescent development, it seems ironic that more emphasis
has not been placed on basic physical safety issues, especially since many researchers

note how dangerous it is to live in some of these neighborhoods. One recent study

33

(McGuire, 1997) which included a safety measure sununed up its importance by stating,
“It appears in this community residents’ judgments about the neighborhood as a
worthwhile place to live may be most heavily inﬂuenced by immediate danger and crime,
because the ratings of quality of life loaded on to the street crime scale” (p.562).
Unfortunately, the current study did not have enough items about neighborhood safety to
include this important variable in the sense of community construct.

Healthy communities are also often described as areas where people know each
other and experience a feeling of togetherness. As articulated by Chavis and McMillan
(1986), the shared emotional connection among neighborhood residents “. .. seems to be
the deﬁnitive element for true community” (p.14). Thus, while safety is necessary for the
mere existence and development of SOC, its deﬁning element is the camaraderie and
connection neighborhood residents feel for each other. As extensively noted by
researchers, authors, and lay people, communities can be extremely safe and yet at the
same time also extremely alienating with little or no feelings of community togetherness.

In safe communities where there is a strong emotional attachment among
residents, this is usually witnessed by neighborhood celebrations such as block parties,
summer festivals, and other events where, whether consciously noted or not, community
itself is celebrated. It is in such communities that neighbors can come together to also
address public problems. In fact, it is argued that this empowering, action component, or
“neighborhood empowerment”, is vital for a healthy community. Even in neighborhoods
where there are relatively few problems that neighbors need to come together to address,
social gatherings and neighborhood celebrations are vitally important. It is this element

Of sense of community that most closely parallels the deﬁnition of social disorganization

34

as laid out by Komhauser (e. g., the inability of local communities to realize the common
values of their residents or solve commonly experienced problems).

The impact of neighborhood disadvantage has been primarily investigated via its
impact on community social organization. Due to the conceptual, methodological, and
statistical difﬁculty of partialling neighborhood effects, it is not surprising that the
multiple pathways through which disadvantaged neighborhoods impact youth outcomes,
particularly delinquency, have not been fully delineated. In the past several years
however, there has been a growing effort to understand how the neighborhood context
impacts youth outcomes via other pathways such as its inﬂuence on parenting and family
relations and processes (Barrera et al., 2002; Elder, Eccles, Ardelt, & Lord, 1995), peer
relationships (Gonzalez et al., 1996), school context (Kozol, 1991; Pretty, Andrewes, &
Collett, 1994), and the interactions among these important developmental contexts and
inﬂuences (Grifﬁn, Scheier, Botvin, Diaz, & Miller, 1999; Simons, Johnson, Beaman,
Conger, & Whitbeck, 1996). Since parenting and family processes are the most
important variables in terms of youth development, the current study incorporated this
proximal context. Moreover, recent research has not only focused on how neighborhood
disadvantage impacts parenting, but how families have utilized creative strategies to
Offset the insidious effects of growing up in neighborhood devastated by concentrated
poverty. Thus, parenting practices can both mediate and moderate the inﬂuence of

neighborhood disadvantage, as the following literature review will display.

35

The Impact of Nghborhood Disadvantage on Parenting,_F_amily Processes, and
Aﬂuion with Delinquent Peers

Overall, the most consistent ﬁnding in research on delinquency has been the
strong role family factors contribute to such behavior. In particular, all major meta-
analyses have found that parental involvement, monitoring, and discipline are the
strongest predictors of delinquency (Loeber & Dishion, 1983; Loeber & Stoutharner-
Loeber, 1986). While this has been the most consistent ﬁnding in the literature to date,
very few of these studies have looked at how parenting characteristics are inﬂuenced by
neighborhood factors, thus, these results may be overestimated or, at a minimum,
misinterpreted due to cross-level misspeciﬁcation. For instance, part of the variance
accounted for in delinquency by parenting variables may actually be due to the ways in
which disadvantaged neighborhoods impact or interact with parenting styles. By
omitting macrolevel variables such as neighborhood disadvantage, current estimates of
individual or parenting effects may be artiﬁcially or spuriously inﬂated (Simons et al.,
1996)

There are many hypothesized ways in which the neighborhood context impacts
parenting and family variables. One of the most obvious is the amount of stress incurred
by living in an economically and socially disenfranchised neighborhood. McLoyd (1990)
reviewed the literature and found that economic hardship and poverty can affect the
mental health of parents both directly and indirectly, and that this inﬂuence can impact
parenting abilities and thus their children. Neighborhood disadvantage can impact
parents directly by providing an inhospitable and dangerous environment for parents and

their children. Moreover, such a stressful environment can also create problems such as

36

chronic anxiety and depression, which can decrease parents’ energy, frustration level, and
ability to monitor and supervise their children’s daily lives. Indirectly, the stressors of
living in a disadvantaged neighborhood can exacerbate any pre-existing individual and
family issues or problems.

Returning to the basic tenets of social disorganization theory, communities
characterized by extreme levels of disadvantage also generally have the fewest
community and institutional resources which adults and families can access and utilize to
offset such hardships. The lack of adequate resources for such families produces a cruel
irony: those with the greatest need have the fewest community-based resources to assist
them in caring for their families. Moreover, as demonstrated by Coulton et al. (1996), the
resources that are available to these residents are perceived to be of inferior quality. For
instance, the most important resource for families in any neighborhood is the quality of
the local school system. The severe problems of schools in disadvantaged urban
neighborhoods has been well-documented and is considered a national crisis (Kozol,
1991; Simon & Burns, 1997).

Other studies have also suggested that the psychological and emotional distress
caused by poverty undermines parents’ beliefs in their ability to be good parents. Elder et
a1. (1995) found that both white and black parents under economic pressure had a lower
level of parental efﬁcacy'because of depressed feelings. Moreover, this ﬁnding was
especially true for single parents who did not have a partner to help reduce the daily
stress caused by ﬁnancial problems. A related study, which also assessed community and
parenting variables, found that mothers living in disadvantaged neighborhoods had a

poorer physical environment in, and directly outside, the home. This study also found

37

that these mothers also displayed less emotional warmth and responsiveness to their
children (Klebanov, Brooks-Gunn, & Duncan, 1994). Irnportantly, these ﬁndings were
substantial, even after controlling for family poverty and conditions. The authors
suggested that the poor physical environment might be due to the lack of incentives to
invest effort, time, and money in one’s house when the overall neighborhood housing is
in distressed condition. In terms of the ﬁnding that these mothers displayed less
emotional warmth to their children, this may be due to the reality of living and raising
children in poor urban neighborhoods, where this may be seen as an adaptive parenting
strategy - to prepare their children for the harsh neighborhood environment they will
encounter (McLoyd, 1990). It is also worthwhile to note the difference between current
poverty and the effects of long-term and persistent poverty, which is oﬁen neglected in
neighborhood effects research. McLeod & Shanahan (1990) found that persistent poverty
impacts children’s internalizing symptoms above and beyond current poverty. Due to the
fact that poverty has become more intense and concentrated within neighborhoods over
last several decades, its long-term effects cannot be overstated.

There have been a number of other studies which have found that parentng
characteristics and styles differ by neighborhood context, particularly that in lower SES
neighborhoods authoritative and harsh parenting styles are more common (Elder & Caspi,
1988; Simons, Lorenz, Wu, & Conger, 1993). As Furstenberg (1993) has documented,
parenting and family management strategies can be characterized as collective,
individualistic, or mixed and the strategy chosen is usually in direct response to the social
organization of local communities. Cohesive neighborhoods with adequate resources

allow parents to trust that their kids will be supervised and monitored by neighborhood

38

residents and that they will be informed when their child is misbehaving. Thus, they are
able to use “collective” parenting strategies. In contrast, extremely disadvantaged
neighborhoods often lack the common values, social ties, and neighborhood resources
that result in a “village-like” atmosphere where residents look out for children. In such
an environment, an individualistic parenting strategy is often utilized since parents cannot
trust that their children will be supervised and aided by neighborhood residents.

At the extreme end of this individualistic parenting style is the “lock-up” strategy,
where parents in severely disadvantaged and dangerous neighborhoods protect their
children by severely limiting their contact and association with others from the
neighborhood (Brodsky, 1996; Furstenberg, 1993). While this is an adaptive response to
harsh external neighborhood conditions, it further isolates families living in concentrated
poverty and limits any potential access and support from similar neighbors and
community members, as well as from local social service agencies and institutions that do
exist. Further, as children age, the role of peers and the general community will play a
greater role in their development no matter how successful parents are in protecting their
children from such an impact. Thus, the importance of consistent support and monitoring
can have much greater impact in disadvantaged neighborhoods. In a review of the
literature on successful methods parents use to offset poor neighborhood environments,
Jarret (1995) found that such a stringent parental monitoring strategy was one of ﬁve
major strategies. Together, these ﬁve strategies were termed “community-bridging” to
describe how parents use the limited resources in their community, limit the inﬂuences of
their neighborhood on their children and access resources in other communities to aid in

the positive development of their children.

39

In a related study on how neighborhood disadvantage inﬂuences parenting styles
and strategies, the role of restrictive discipline and low levels of parental monitoring and
involvement were hypothesized to mediate the relationship between neighborhood
disadvantage and childhood aggression. Rather than a direct mediating role, harsh and
restrictive parenting increased children’s belief and acceptance of aggression and this
resulted in greater externalizing problems for these children (Colder, Mott, Levy, & Flay,
2000). Since neighborhood disadvantage also directly increased children’s positive
beliefs about aggression, this study reveals the complexity of the multiple and varied
ways neighborhoods impact children.

Other studies have looked at the impact of the neighborhood context on children
by evaluating the interaction between neighborhood disadvantage and parenting practices
rather than just looking at its mediating role. For instance, Gonzalez et al. (1996) found
that the relationship between maternal restrictive control and youths’ (junior high) school
performance was moderated by neighborhood risk. Overall, maternal control was not
signiﬁcantly related to a child’s school performance. However, in high-risk
neighborhoods, high maternal control resulted in better grades while in low-risk
neighborhoods high maternal control resulted in worse grades. Although a cross-
sectional study, this result lends empirical support to the protective or adaptive parenting
practice of a more controlling or harsh parental style when families reside in
disadvantaged neighborhoods.

This long-held belief has been extensively documented in qualitative and
ethnographic studies of disadvantaged urban neighborhoods. After all, the results of not

knowing exactly where one’s child is at all hours of the day can have much more severe

40

consequences in dangerous neighborhoods than in neighborhoods that, for instance, do
not have a gang presence or an active open-air drug market. As one of the mothers from
Brodsky’s (1996) study states “Yeah, and then the drive-bys. It just- you know, you can’t
let the kids play outside anymore because you’re afraid someone is gonna come around
the corner shootin’ at the- the dealers and the kids will be outside and they’ll get hit”.
Ethnographic and qualitative studies have also documented the dissonance parents in
these neighborhoods experience when they weigh providing more autonomy to their
children or restricting this autonomy because of the endemic levels of violence and
related problems outside their front door. As one of the parents from Furstenberg’s
(1993) qualitative study stated, “Well, I know that I’m very protective of my son. I have
to give him more space so he can grow. Of course, in some neighborhoods the
prerequisite of basic safety levels are not met and this prevents parents ﬁom worrying
about higher-order needs of their children such as independence and autonomy.
Nevertheless, most researchers seem to continue take a static view of community context
and assume that the end goal should always be a tight and cohesive neighborhood, even
though it is sometimes advantageous for parents to isolate themselves from their
community, as the aforementioned quotes so poignantly illustrate.

In a related manner, Kupersmidt et al. (1995) found that the interaction between
neighborhood context and parenting styles and strategies depended on the type of
behavior under study. Similar to the aforementioned study, some parenting and family
variables work in certain environments while in other environments the same parenting
styles can produce deleterious effects. Utilizing cluster analysis, Gonnan-Smith, Tolan,

& Henry (2000) were also able to show that parenting practices and neighborhood type

41

interact in unforeseen ways to impact youth in these neighborhoods. For example, task-
oriented families work well in highly cohesive neighborhoods, but in neighborhoods with
low levels of cohesion this parenting style led to a signiﬁcant increase in serious and
chronic delinquency for teenage youth. This ﬁnding suggests that there is a relationship
or continuum between parenting and familial monitoring and control on one-hand and
neighborhood sources of supervision, monitoring and social control of youth on the other
(Sampson, 1986, 1997). As discussed at length earlier, research on the mediating role of
community social organization has shown that collective supervision of children and
enforcement of neighborhood norms (e.g., collective efﬁcacy) results in signiﬁcantly
lower levels of violence (Sampson et al., 1997).
N_eighborhood Selection Effects

A major and valid critique of all neighborhood effects studies has been the fact
that people are not randomly assigned to neighborhoods and that this selection bias may
explain the results rather than the ﬁndings being due to neighborhood-level structural or
social factors. In other words, some argue that the effect of neighborhood disadvantage
may operate at the family or individual-level and the relationship found at the
neighborhood-level is simply due to aggregation effects (Bronfenbrenner, 1979; Duncan
& Raudenbush, 1999; Korbin & Coulton, 1997; Levanthal & Brooks-Gunn, 2000).
While this argument cannot be entirely refuted because even random experiments like the
moving to opportunity program are not truly random, it seems a bit simplistic and victim
blaming to suggest that neighborhood context plays no role in youth outcomes and that
any negative effect found is Simply due to poor parenting and other characteristics

ascribed to poor people. In fact, this argument could be made for any social problem

42

found in disadvantaged urban neighborhoods and essentially blames the victim rather
than attempting to understand the detrimental impact of deleterious structural and social
conditions.

Gorman-Smith, Tolan, & Henry (2000) found not only great variability in
community social organization and family ﬁrnctioning in disadvantaged neighborhoods,
but also that “exceptional family functioning” comprised almost 30% of the sample. This
is a high percentage, especially since the study purposely over-sampled previously
identiﬁed “high-risk” youth from some of the worst neighborhood environments in the
city of Chicago. Thus, not only is there great variability among families in poor
environments, but many of these families somehow ﬁnd a way to help their children
tluive in some of the most disenfranchised developmental contexts. In fact, the vast
majority of children from disadvantaged neighborhoods grow up to lead successful and
productive lives like the majority of youth ﬁ'om more advantaged neighborhoods
(Seidman, 1991). Unfortunately, the ﬁeld of neighborhood studies has not concentrated
its efforts at understanding how families thrive in such harsh environments and has
neglected this more likely outcome and chosen to focus on those families and youth
experiencing serious difﬁculty, whether the ultimate negative outcome of interest is
school dropout, drug abuse, or delinquency. Thus, it is not only important to investigate
various pathways to delinquency, but also to extend analyses to examine positive youth
developmental outcomes such as success in school and participation in community and
school activities.

Overall, research has shown neighborhood effects account for only 5-10% of

variance in child and adolescent outcomes (Levanthal & Brooks-Gunn, 2000), thus,

43

family, peer, and individual factors are stronger determinants. While it is acknowledged
that these variables account for a greater percentage of variance in delinquency rates, the
role of the neighborhood context may increase as more sophisticated models include the
neighborhood’s impact and interaction with parental characteristics and individual youth
characteristics. It is especially important to examine whether neighborhood disadvantage
accounts for more variance in youth outcomes, particularly delinquency, when its
inﬂuence on parenting styles and strategies (e.g., parental monitoring and support) is
included. More important than this empirical rationale however, is that a greater
understanding of the interaction between family and neighborhood contexts can lead to
more successful interventions by targeting the multiple and varied contexts that inﬂuence
youth development.
Summary

While the role of neighborhood effects on youth outcomes has been re-
acknowledged, particularly in regard to the development of concentrated poverty, it is
essential not to overly romanticize the past and assume that the urban areas of our nation
are beyond repair. The fact remains that there never was a golden era of community and
urbanization does not necessarily eliminate the possibility of developing cohesive and
supportive neighborhood environments for residents and their families (Fischer, 1982;
Kasarda & Janowitz, 1974). However, at the same time, it is also true that certain
structural and social features of urban neighborhoods can be detrimental to residents,
particularly youth. Also, as Sirnons et a1. (1996) discovered, the same structural and
social characteristics that negatively impact families and youth are not solely limited to

urban areas.

While neighborhood-based studies have concentrated their efforts at
understanding how negative structural characteristics impact community social
organization, the assessment of how disadvantaged neighborhoods indirectly impact
youth outcomes via family and individual-level variables has been a more recent
development (Colder et al., 2000; Furstenberg, 1993; Gonzalez et al., 1996; Paschal] &
Hubbarb, 1998; Sampson, 1993a). This should not be too surprising as the impact of
disadvantaged neighborhoods on community social organization and youth outcomes was
only recently established, despite the fact that social disorganization theory emerged in
the early period of the last century. While the studies reviewed have shown empirical
support for various ways neighborhood disadvantage impacts parenting practices, the
current study focused on how disadvantaged urban contexts led to decreased parental
support and monitoring because of the increased stressors and difﬁculties associated with
rearing youth in such unstable and inhospitable environments. While this indirect or
mediating role Of parental support and monitoring will be evaluated, it was also
hypothesized family support and monitoring could act as a moderating variable in two
ways. First, it was hypothesized that family support and monitoring could interact with
informal social control to increase positive youth outcomes and decrease negative youth
outcomes. Second, it was argued that some parents would substantially increase support
and monitoring in an attempt to offset negative structural and social conditions found in
disadvantaged neighborhoods. In this case, high levels of family support and monitoring
would reduce the impact of low levels of sense of community and informal social control
on youth outcomes. Thus, family support and monitoring will be evaluated as both a

mediator and moderator of neighborhood disadvantage.

45

The Current Study

The literature reviewed in the introduction displayed the various and multiple
pathways neighborhood disadvantage is able to negatively impact families. The current
study will investigate these various pathways and how they interact to transmit the
inﬂuence of neighborhood disadvantage on youth outcomes. Please see Figure 2, which
displays the conceptual model that will be evaluated.

The current study merges sociological and community psychological
conceptualizations of ecological theory to better understand the impact of negative
structural conditions on individual youth development. Utilizing an updated model of
social disorganization or collective socialization framework, neighborhood is
conceptualized at three distinct levels, with the focus of this study on the most immediate
and objective conceptualization of neighborhood - the face-block. The current study
attempts to understand the impact of neighborhood disadvantage by assessing how
neighborhood structural conditions inﬂuence youth outcomes by simultaneously
impacting the social organization of local communities, parenting styles and strategies, as
well as affiliation with delinquent peers. The major research objectives and hypotheses
of the current study are:

l. The direct impact of neighborhood structural conditions (block stability and block
income) on youth outcomes will be assessed. It is hypothesized that higher rates of
block stability and block income will lead to more positive youth outcomes and less
negative youth outcomes.

a. Block income will also have an indirect impact on youth outcomes by increasing

the endogenous variable of family support and monitoring. It is hypothesized that

46

neighborhoods with higher incomes will have more community resources and
institutions, which help facilitate youth development and the ability of parents to
support and monitor their children.

b. Block stability will also indirectly inﬂuence youth outcomes via its impact on
sense of community, informal social control, and family support and monitoring.
It is hypothesized that neighborhood stability helps facilitate the development of
social networks and norms, which subsequently reinforces positive youth
development and parental involvement and support.

2. The endogenous construct of family support and monitoring will also be analyzed as
a moderating variable between sense of community, informal social control, and
youth outcomes.

a. Speciﬁcally, it is hypothesized that this may happen in two different ways. First,
family support and monitoring may interact with high levels of informal social
control to signiﬁcantly increase positive youth outcomes and signiﬁcantly
decrease negative youth outcomes.

b. It is also hypothesized that families in severely disadvantaged neighborhoods may
utilize extremely intense parental support and monitoring strategies to offset the

negative inﬂuence of the negative structural and social characteristics.

47

 

 

 

 

 

 

 

 

 

 

 

 

 

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48

Table 1

Signiﬁcant Findings From Recent Social Disorganization Studies

 

 

 

 

 

 

 

 

 

Study Mediating Variables Outcome Variables

Simcha-Fagan & 0 Organizational participation 0 Self-reported delinquency

SChWﬁﬂZ, 1986 0 Community disorder-criminal 0 Severe self-reported
subculture delinquency

o Ofﬁcially recorded
delinquency

$338011 & Groves, 0 Organizational participation 0 Criminal offending rates
0 Local ﬁ'iendship networks (personal violence &
0 Control of street corner youth " PYOPCTW/ vandalism)

0 Criminal victimization
rates (mugging/robbery,
stranger violence, total
crime, etc.)

Elliott, Wilson, 0 Social integration 0 Prosocial competence
Huizinga, Sampson, o Informal networks 0 Conventional ﬁiends
5150“, & Rankin, 1995 o Informal control b 0 Problem behavior
Sampson, Raudenbush, o Collective efﬁcacy ° 0 Violence
& Earls, 1997 0 Household victimization
o Homicide rates

Bellair, 2000 o Informal surveillance 0 Burglary

o Informal control 0 Stranger Assault/Robbery

 

Note. The reviewed studies all utilized a social disorganization framework with similar independent
variables. Only the mediating variables which proved signiﬁcant with at least one of the outcome

variables are listed.

' Control of street comer youth was the most consistent signiﬁcant mediating variable.
b Informal control was the only signiﬁcant mediating variable with all three outcome variables.
° Collective efﬁcacy combined ﬁve items on social cohesiveness and trust and ﬁve items on informal

social control.

49

 

Table 2

Sense of Communig & Related Measures for Geogaphic Communities

 

 

 

 

 

 

 

 

 

 

 

Study Quick Description Basic Results
Doolittle & PCA found support for 6 6 components: Supportive
Macdonald (1978) separate factors. climate, Family life cycle,
Localism, Safety, Informal
interaction, & Neighborly
interaction.
Percent of variance
accounted for by each
component: 15%, 12%,
8%, 7%, 6%, 6%.
Krupat & Guild Surveyed a number of 6 commnents: Warmth and
(1980) different sized closeness (CL = .83),
communities and created Activity/entertainment (a =
a community social .78), Alienation/isolation
climate scale with 30 (a = .68), Good life (a =
items and 6 components. .66), Privacy (a = .54), &
Uncaring (a = .53).
Riger & Lavrakas Found 2 important 2 components: Physical
(1981) components in patterns rootedness (a =. 59) &
0f attachment and Socially bonded (on = .56).
interaction 0f Rooted accounted for 38%
neighborhood residents. of variance and bonded for
Created a typology of 17% of variance.
neighborhood attachment
for residents: young
mobiles, young
participants, isolates, and
established participants.
Glynn (1981) Assessed ideal and actual Unidimensional —
levels of SOC in 3 psychological sense of
different communities community.
through a 17 8-item scale. Actual SOC a = .97.
Decreased instrument to Ideal SOC a = .92.
60 items through
analyses.
Chavis, Hogge, Created the Sense of 4 commnents:
McMillan, & Community Index (SCI), Membership, Inﬂuence,
Wandersman (1986) which had 4 components. Integration and fulﬁllment
Shortened version of of needs, and Shared
scale (SCI — short form) emotional connection.

 

50

 

 

 

 

 

sample comparing SOC

contains 12 items and is Overall alpha has been
the one most often used found to be around .71.
in measuring SOC
despite reliability
problems.
Davidson & Cotter Created Sense of Unidimensional.
(1986) Community scale (SCS) a = .85 in one community
which originally had 17 and .81 in the other.
items.
Referred to level of city
vs. neighborhood.
Buckner (1988) Created Neighborhood Unidimensional.
Cohesion Instrument 17 item scale entitled
(NCI). Originally Neighborhood Cohesion
thought to be 3 separate Instrument.
scales (attraction to a = .95,
neighborhood,
neighboring, &
psychological sense of
community) but analyses
indicated it could be one
overall construct.
Pretty (1990) Used short form of SCI Unidimensional.
in a University residence PCA found that it was

inappropriate to look at the

 

 

 

 

 

 

 

 

with the University short form as 4 separate
Residence Environment components.

Scale (URES) (Moos &

Gerst, 1974).

Davidson & cotter Used a shortened version Unidimensional.

(1993) of their SCS. This Alpha = .84.
version was reduced to 5
items.

Pretty, Andrews, & Used shortened version Unidimensional.

Collet (1994) of SCI to calculate school
sense of community and
neighborhood sense of
community.

Hill (1996) Reviewed various Found less than 30
measures of SOC and published measures of
discussed implications SOC and factor analysis
for the ﬁeld. has yielded both

unidimensional and
multidimensional
| interpretations.
iwifoot (1996) Reviews measures of o M- Presents

 

 

 

51

 

SOC, community
satisfaction and identity,
etc.

Argues for more

an argument for 14
dimensions of community
identity.

 

 

 

 

multidisciplinary
research and focus on
qualitative measures.
Skaeveland, Garling, Created the MMN, 4 Components: Supportive
& Maeland (1996) multidimensional acts of neighboring,
measure of neighboring Neighbor annoyance,
scale. This scale Neighborhood attachment,
contains 14 items and Weak social ties.
one of few to measure Percent of variance
negative neighbor accounted for by each
relations. component: 32%, 16%, 8%
& 8%.
Alpha ranged from .70-.86
for the four subscales.
Barnes & McGuire Adapted questionnaire 4 Components: Perception
(1997) from Simcha-Fagan & of street crime and life
Schwartz (1986) to use quality (on = .85), Social

with families with young
children.

relationships and networks
among neighbors (or = .82),

 

 

 

 

 

Named Neighborhood Attachment to
Characteristics neighborhood (on = .81),
Questionnaire (N CQ)- and Neighborhood disorder
Shows similarity of (a = .77),
community social
organization in SD
theory and measures of
SOC.

Brodsky, O’Campo, Used a revised form of Unidimensional.

& Aronson (1999) Chavis, Florin, Rich and PCA found support for 2
Wandersman’s scale dimensions although one
(1987; as cited in Linney was too small so only kept
and Wandersman, 1991). one dimension for study.
10 items. a = 84,

Kingston, Mitchell, The SOC scale utilized in 4 Components:

Florin, & Stevenson this study assessed many Neighborhood-related

(1999) of the same elements as attitude scale (a = .83),
previous scales although Neighborhood inﬂuence
some components were scale (a = ,89),
developed for this study. Neighborhood related

 

 

behavior (a = .80),
Participation in community

 

52

 

 

organizations (N 0 alpha,
one item).

 

 

 

 

 

 

 

Chavis & Pretty Reviews theoretical and One major theme of this
(1999) measurement articles on article was the continued
SOC and serves as an search for measures.
introduction to a special
issue.
Chipuer & Pretty Reviews the short-form Found that components of
(1999) of SCI and its proposed SCI were unreliable
4 dimensions. (Alphas ranged from .16 to
a high of .72).
Suggest using long form of
SCI as foundation to create
a new measure
Chipuer, Pretty, Created a SOC scale for 4 components: Support,
Delorey, Miller, youth called the Safety, Activity, &
Powers, Rurnstein, Neighborth Youth friendships. Alphas ranged
Barnes, Cordasic, & Inventory. 22 item from .64 to .94.
Laurent (1999) measure which had 4
components.
Used Buckner’s NCI and
short form of SCI to
create inventory with
input from youth.
Crew, Kim, & 4 items measuring SOC Unidimensional.
Schweitzer (1999) at block-level. Alpha = .81
Schweitzer, Kim, & SOC measure was Alpha not reported but
Mackin (1999) comprised of 16 items assessed as a
related to connection, mm construct.
belonging, and support.
Prezza, Amici, Translated Davidson & Unidimensional.
Roberti, & Tedeschi Cotter’s SCS into Italian. While 5 factors had

(2001)

18 items.

eigenvalues over 1, all

 

 

 

 

Found support for 5 items loaded > .36 on the
components but also ﬁrst factor so interpreted
found that it could be unidimensionally. Overall
looked at as one alpha = .82.
dimension.

Zani, Cicognani, & Translated Davidson & 4 Components:

Albanesi (2001) Cotter’s SCS into Italian Opportunity for
and measured participation and
adolescent’s SOC. fulﬁllment of needs,
Items loaded differently Pleasantness of living area,
from adults. So, concept Social climate, &
of SOC plays out Membership.

 

53

 

 

differently for youth.

Percent of variance
explained by each
component: 15%, 14%,
12%, & 12%.

a = .85.

 

 

 

 

Bardo, 1983; Buckner,
1988; Glynn, 1981; Lalli,
1992; Nasar & Julian,
1995; Skaeveland et al.,
1996)

Performed a PCA on all
95 items from these
scales and found support
for 5 components of SOC

 

Martinez, Black, & Created Perceived - 4 commnents: Social
Starr (2002) Neighborhood Scale embeddedness, Sense of
(PNS), a scale with items community, Satisfaction
from previous published with neighborhood, Fear of
items on SOC, crime.
neighborhood
satisfaction, etc.
Intended for parents of
young children. Total 34
items and a CF A found 4
components.
Obst, Smith, & Looks at numerous scales 0 5 commnents: Ties and
Zinkiewicz (2002) over the years (Bardo & friendship, Inﬂuence,

Support, Belonging, and
adds construct of conscious
identiﬁcation.

Percent of variance
accounted for by each
component: 24%, 13%,
10%, 7%, & 4%.

 

m. An attempt was made to review the vast majority of published empirical studies

on sense of community and related variables. Since the concept spans many disciplines
and is labeled differently across these content areas, some studies may have been omitted.
Also, studies which investigated non-territorial communities (e.g., Bishop, Chertok, &
Jason, 1997) were excluded ﬁom presentation.

54

 

Figure 2

Congptual Model

 
   
   
  

Sense of
Community

    
 
 
 

Informal Social

  
   
 
   
    

Block
Stability

 

Outcomes

 

 

 

Delinquent
Peers

   
  

   

Fam Support
& Monitor

55

CHAPTER 2
METHOD
Procedures

Sm

This research study was conducted in the city of Lansing, Michigan. Lansing is
the state capital and an industrial city with a population of approximately 127,000. The
Sense of Community in Lansing Neighborhoods Project ofﬁce is located at Michigan
State University in East Lansing. All interviews were conducted in either the homes or
on the front porches of the respondents.
Participants

Participants were referred from the local school district. There were 103 tenth-
grade males who participated in the study along with one of their parents and one of their
neighbors. Therefore, for each student there was a total of three interviews (student,
parent, and neighbor) for a combined total of 309 interviews. Of the 103 youth, 41%
were White, 40% were African American, 11% were Hispanic, 6% Asian, and 3% mixed
race. As can be seen in Table 3, student respondents closely matched the racial/ethnic
percentages of Lansing High School students.

Primary caretakers and neighbors had to be over the age of 18. Only one adult
was surveyed at each household to avoid the potential bias or inﬂuence of others.
Of the 206 participating adults, 67% were female and 67% owned their own homes. The
average length of time on the block was approximately 10 years and covered a range

from three months to 39 years. An interpreter was utilized to increase Asian respondents

56

since a large percentage were of Hmong descent and many of these youth’s parents spoke
little or no English.
Recruitment Procedures

This research project was conducted with assistance from the Lansing school
district ofﬁce of research and evaluation services. First, the Lansing school district
provided a random sample of 300 tenth-grade male students who attended public high
schools throughout the city. To ensure that no parent, youth, or neighbor felt coerced to
participate, a three-step consent procedure was employed. First, the school district
required that the initial mailing to the 300 families were sent out from the school
district’s own ofﬁce. The SOC research team mailed an initial letter to these 300 parents,
which explained the rationale and goals of the study and contained a request for
participants. A self-addressed, stamped postcard was included and parents were
instructed to return this postcard if they did not want their youth to be included in a pool
of possible research participants. The phone number to the SOC project ofﬁce was also
included and parents were encouraged to call if they had any questions, comments, or
concerns. Once an adequate time had passed from this initial mailing, the Lansing school
district ofﬁce of research and evaluation services provided the SOC project team with the
names and addresses of all those parents who did not return the postcard indicating that
they did not want to participate. This resulted in a 22% refusal rate for a sample size of
235. This passive consent procedure complied with local school district policy, and
again, was only the ﬁrst of a three-step procedure.

For the second component of the recruitment procedure, trained interviewers

traveled to the youth’s home to explain the study to the youth’s primary caretaker and ask

57

if they would like to participate. A follow-up letter with the interviewer’s name was leﬁ
if the primary caregiver was not home or too busy to discuss the study at that time. If a
primary caregiver was home and agreed to participate, the interviewer reviewed the
consent form, obtained a signature, and interviewed the parent either at that time or set up
an appointment for an interview in the future. At this point of the consent procedure, an
additional 41 students (17%) were dropped because their parents reﬁrsed to participate.
Also, 49 students (21%) were dropped for various reasons including incorrect addresses,
if a family moved, or if they did not live on a street where a face-block could be
adequately approximated.

In the third component of the consent procedure, each youth was contacted during
the initial parent visit, or at a follow-up visit, and asked if they would like to participate.
If so, the interviewer reviewed the project assent form, obtained a signature, and either
interviewed the youth then or set up a time for a future interview. So, even if parents
signed written consent, only those youths that also assented on their own were included
in the study. Of all youth that were approached, only one refused to participate and was
dropped ﬁ‘om the study. Neighbors were approached via a random sampling procedure
and in the same manner as the primary caretaker although only verbal consent was
needed for their participation. There were three requirements for a neighbor’s
participation. They had to be at least 18, agree to participate, and live on the same face-
block as the youth.

Interviewer Training and Supervision
Upper-level, undergraduate psychology students received college credits for

participating as part of an independent study course at the University. Initial interviewers

58

were trained for one and a half months prior to the data collection process in a class
format which was similar in nature to that of a graduate level seminar. First, interviewers
were introduced to seminal works in the area of Sense of Community and delinquency.
Second, interviewers were responsible for reading and discussing the recent research on
neighborhood studies that incorporated social disorganization theory. Third, interviewers
were exposed to methodological issues in community research with an emphasis on
interview techniques. Finally, and most importantly, interviewers reviewed the various
survey instruments and practiced role-playing interviews until there was adequate
consistency in their administration of the survey. Particular attention was paid to the
youth interviews and how to build rapport, trust, and explain, in terms that the youths
could understand, the meaning of conﬁdentiality. Interviewers that were recruited after
this training period received an abbreviated version of this training course.

In order to increase consistency across interviewers, a project staff member
accompanied the interviewer for the ﬁrst two interviews and provided support and
feedback. Also, the project team developed an extensive interviewer training manual,
which detailed the multiple issues that interviewers may conﬁont, and strategies to
overcome these potential pitfalls. During the data collection phase, interviewers
attempted to conduct eight hours of interviews per week. Interviewers were required to
go out on different days and times but were instructed to focus their time during the early
evening hours and on weekends. Interviewers also kept a logbook that consisted of the
dates, days, and times of attempted contacts in order to facilitate face-to-face contact of
all households. Most importantly, no household was excluded because it was difﬁcult to

establish contact, regardless of the number of times an interviewer had to return.

59

Households with an invalid address (e.g., abandoned, family moved) were returned to the
Lansing school district for the correct or updated address. Interviewers also met one time
per week for a two-hour supervisory group meeting during the ﬁrst month and a half of
data collection. After this, interviewers met individually for 30-minute sessions with the
Sense of Community in Lansing Neighborhoods project coordinator. Project staff was
also always available to interviewers for help or feedback as often as needed. Finally, to
assess interrater reliability, two interviewers coded approximately 6% of all interviews.
Of a total of 868 items, only six were inconsistently marked, for an overall agreement
rate greater than 99%.
Interview Procedure

Trained interviewers traveled to the youth’s homes to conduct the interviews for
the study. First, interviewers introduced themselves to a primary caretaker as a project
member on the Sense of Community in Lansing Neighborhoods Project team. Each
interviewer had a Michigan State University ID card displayed along with the SOC
project logo. Interviewers provided a brief scripted introduction and description of the
study prior to obtaining consent. Again, written consent was obtained ﬁom the primary
caretaker, written assent from the youth, and verbal consent was obtained from the
neighbor prior to interviews.

Face-Block Measures

This study differed from the majority of previous neighborhood effects studies
based on social disorganization theory by conceptualizing and measuring neighborhood
at the block-level and by directly measuring the proposed independent variables of

neighborhood income and residential stability. The vast majority of previous studies

60

have utilized some combination of census indicators or other administrative data to derive
these measures. In general, income or SES has been measured in numerous ways that are
representative of social science research. Most prior studies have summed and
standardized a number of measures within a census tract such as: percentage of families
below the poverty line, percentage of residents employed in professional or managerial
positions, percentage of college educated residents, average income or housing value, etc.
Residential stability has most often been calculated as the proportion of families that have
moved in the last ﬁve years in a census tract.

Another major difference in the current study was the way in which the
independent variables were operationalized. The independent variables were
conceptualized and measured on a level of advantage versus the traditional method of
focusing on levels of disadvantage. It is argued that this modiﬁcation was more than just
a matter of semantics. Researchers need to be more sensitive to the communities under
study as what is being investigated surround issues of safety, quality of life, and possible
life outcomes of youth in these communities. By conceptualizing and measuring these
neighborhoods in a positive manner, the dialogue can change from one focused on
deﬁcits to one focused on investigating and explaining the various strengths of these
neighborhoods and the people who live within them.

Blocg Income

Income was individually calculated by dividing monthly income by the number of

residents in the house. To obtain a block income measure, the parent and neighbor’s

income were simply averaged.

61

Block Stability

Individual scale scores (e. g., parent, neighbor) were calculated by summing four
likert items such as: People move in and out of this block a lot — reverse coded. Block
scores were obtained by averaging the parent and neighbor’s total scale score.
Respondents were asked to rate from 5 (strongly agree) to 1 (strongly disagree) their
endorsement of the four items. Parent and neighbor responses were assessed together to
obtain block-level reliability. Alpha was .84.

Sense of Community

This scale was created to measure the sense of community that exists on
residential face-blocks within an urban community. The measure was created after an
existing literature search on all of the sense of community measures in the literature, thus,
many of the items were previously published in other scales. There were six items for
this measure and respondents were asked to rate from 5 (strongly agree) to 1 (strongly
disagree) their endorsement of the item. Examples include: People who live on this
block feel connected to each other, (2) A feeling of community spirit exists among the
residents on this block, and (3) People on this block have a voice regarding important
community issues. Parents and neighbors of the targeted youth were asked to respond to
this measure and their scores were averaged to construct a SOC score for the face-block
of each youth. All negatively worded items were reverse coded prior to analyses. Alpha
was .77 at the block-level.
m1 Social Control

Parent and neighbor’s scores were averaged to obtain a block measure of informal

social control. There were four items, which asked about the likelihood that

62

neighborhood residents would intervene, and respondents answered on a 5-point scale
from 5 (very likely) to 1 (very unlikely). Each item was preceded by the following
question “How likely are people on this face-block to intervene if . . .”: Children are
ﬁghting in front of your house and A child is taking something from a neighbor’s house.
Intervene was deﬁned as actions taken to address the misbehavior such as confronting the
youth directly, discussing the situation with their parents, or calling the police. Alpha
was .81 at the block-level.

Ofﬁcial Crime & Delinquency

Ofﬁcially reported crime and delinquency data was collected from the Lansing
Police department. Using ArcView 3.2, the sums of speciﬁc delinquency violations were
calculated to correspond to the minor delinquency, severe delinquency, and alcohol and
drug use self-report measures from the youth outcome survey. To correct for moderate
skew and kurtosis problems, all of these outcome variables were log transformed
[LN(sum + 1)].

The crime dataset included all crimes which occurred in Lansing and resulted in
arrest between 1995 and 1998. Prior crime and delinquency research has found that
using a number of years increases the reliability of ofﬁcial police data (Peterson, Krivo,
& Harris, 2000). Also, to approximate the size of typical face-blocks in the Lansing area,
a 600-foot “buffer” was constructed around each youth’s address. To create this buffer,
GIS utilized each youth’s address and drew a circle 600 foot in every direction around
their home.

Thus, in addition to the block that the youth lived on, the buffer also included 600

feet perpendicular to the home and could include blocks behind and across from the

63

youth’s home. While this extended the neighborhood beyond the youth’s block, it was
necessary for two reasons. First, there needed to be enough variance across the youth’s
blocks, and with such a small area, this was likely not to be the case. Second, many
crimes occur at or very close to a street corner and are either coded that way or one block
is randomly chosen. Thus, these incidents needed to be included for both blocks and the
creation of buffers in this manner handled this potential problem. In cases where parts of
these buffers or neighborhoods overlapped, incidents were summed for both

neighborhoods.

Family Measures

Family Support and Monitoring

 

Five items were summed to create this scale. Higher scale scores indicate a
greater level of support and monitoring by the youth’s primary caregiver. Three
questions asked about helping and supporting their son in school and 2 items asked
whether or not they knew their son’s ﬁiends and parents of those ﬁiends. Alpha was .69.

Individual Youth Measures
Afﬁliation with Delinquent Peers
There were three items which assessed each youth’s afﬁliation with delinquent
peers. Each item was preceded by the following question “How many of your ﬁ'iends
”: rob or bully others into giving them something; sell drugs. Youth answered on a 5-
point scale from 5 (all of them) to 1 (none of them). Alpha was .69.
Youth Outcome Measures

There were three major elements to the youth outcome survey: conventional

activity, self-reported delinquency, and alcohol and drug use. To correct for severe skew

64

and kurtosis, all of the self-reported delinquency outcome variables were log transformed
[LN(scale + 1)]. The vast majority of these items were taken ﬁ'om the youth survey
utilized in Elliot et al.’s (1996) study on neighborhood effects in Chicago and Denver,
although there were some modiﬁcations to the delinquency and drug use sections.
Minor Delinquency — self-report

This component contained four items, all of which related to stealing. Three
items related to stealing various amount of money (e.g., $50 or less, $100 or less) and one
item asked about stealing something from a car. Alpha was .69.
Severe Delignquencv — self-report

Two items constituted this component of self-reported delinquency. These two
items were on the severe end of the scale and asked the participant if they had attacked
someone in the past year, while the other item asked if they used force (may have
included a weapon) to take money or things from someone else.
Alcohol and Drug Use

There were two items for the survey measure of alcohol and drug use. Each youth
was asked the number of times in the past year that they consumed alcohol until they
were intoxicated and the number of times in the past year they used marijuana.
Conventional Activity

This outcome variable was measured by three items that asked about the number
of activities the youth participated in school, in the community, and youth religious

activities. Alpha was .39.

65

Data Analyses

Since there were multiple indicators for the main constructs, and because the
intent of the current study was to explore the various pathways by which disadvantaged
neighborhoods impact youth, latent covariance analysis was utilized in a two-stage
process to assess the main research questions of the study. The ﬁrst phase of analysis
required the theoretical formulation of a measurement model while the second phase
consisted of assessing the relationships among the latent variables from the conceptual
model as displayed in Figure 2 (Schumacker & Lomax, 1996).

The measurement model was evaluated by the overall ﬁt or chi-square test, which
should be nonsigniﬁcant to indicate adequate model ﬁt. Since the chi-square is overly
inﬂuenced by sample size (Gerbing & Anderson, 1992; Schumacker & Lomax, 1996),
and since other ﬁt indices produce a downward bias with small samples (Fan, Thompson,
& Wang, 1999; Gerbing & Anderson, 1992), a number of additional ﬁt indices were
utilized to assess model ﬁt. For both the measurement and structural models, the chi-
square statistic will be presented along with the standardized RMR, RMSEA, and IFI. To
indicate good model ﬁt, the standardized RMR should be close to .08, RMSEA should be
close to .06, and IFI should be around .95 (Hu & Bentler, 1998, 1999). Maximum
likelihood estimation was used because it is the most common estimation method in
structural equation modeling and performs well under poor conditions such as small
sample size and excessive kurtosis, both of which characterize this study (Hoyle &
Panter, 1995). Finally, to achieve best ﬁt, modiﬁcation indices and standardized
residuals were also analyzed and changes were made to the model only if they

corresponded to underlying substantive theory.

66

The second phase of data analysis consisted of applying the measurement model
to a path model. The exogenous manifest variable of block income and latent exogenous
variable block stability are hypothesized to have both direct and indirect effects on youth
outcomes. Speciﬁcally, block stability will indirectly inﬂuence youth outcomes by
facilitating greater levels of sense of community and informal social control as well as via
its inﬂuence on family support and monitoring. Block income will indirectly inﬂuence
youth outcomes by facilitating the ability of parents to supervise and support their
children. Finally, family support and monitoring will also be evaluated as moderating the
relationship between block stability, sense of community, and informal social control on
youth outcomes. Due to the difﬁculty of assessing moderating relationships in structural
equation modeling, these hypotheses will be evaluated by conducting regression analyses.

Analysis of the proposed structural models also employed the overall model of ﬁt
index or chi-square test and the indices described previously. The current analysis used a
deductive approach in evaluating structural models by starting with a ﬁrll conceptual
model and testing alternative models using the chi-square difference test (Hoyle &
Panter, 1995). However, only three paths were potentially removed from the conceptual
model. Since the intent of the current study was to evaluate the direct and indirect effects
of neighborhood advantage on youth outcomes, all indirect pathways were kept in the
ﬁnal structural model to facilitate comparisons of the model across the various youth
outcomes. Thus, only the direct paths from block stability and block income to youth
outcomes were removed ﬁom the conceptual model if they were insigniﬁcant and
resulted in a non-signiﬁcant chi-square difference test. To assess the hypothesis

proposed by the contagion theory of neighborhood effects, a path from block stability to

67

afﬁliation with delinquent peers was added to the conceptual model. If this path was not
signiﬁcant and resulted in a non-signiﬁcant chi-square difference, it was deleted from the

model.

68

Table 3

Race/Ethnic Baﬁground of City’s High School Students & Research Participants

 

 

Race/Ethnic High School Research
Category Students Particﬂants
White 45% 41%
Aﬁican-American 36% 40%
Hispanic 12% 11%
Asian 7% 6%
Mixed Race NA.“ 3%
Native American 1% 0%

 

Note. Race/Ethnic background of the students was obtained from the city’s school district oﬂice
of research and evaluation services. Percentages are rounded so can sum to over 100%.
NA. = Not available. Mixed race/ethnicity is not an option on school demographic forms.

69

CHAPTER 3
RESULTS
Measurement Model

The ﬁrst step in covariance structure analysis is the speciﬁcation of a
measurement model to assess both convergent and discriminant validity prior to assessing
any structural relationships among the variables. Thus, a conﬁrmatory factor analysis
was conducted on all variables in the conceptual model to insure that indicators loaded on
their respective latent variables. Since there were multiple outcome variables, only the
measurement model for conventional activity will be presented although a conﬁrmatory
factor analysis was performed on each separate outcome variable.

The initial measurement model provided adequate ﬁt statistics, minus the chi-
square value [x2(260, N = 103) = 364, p = .000, standardized RMR = .072, RMSEA =
.063, IFI = .900.]. Utilizing the cutoﬁ values previously discussed, the standardized
RMR and RMSEA suggested adequate ﬁt although the IFI was low and should be closer
to a value of .95. By reviewing the standardized residual covariance matrix and
modiﬁcation indices, it was apparent that there were a couple of adjustments that could
be made to improve model ﬁt. Speciﬁcally, the modiﬁcation indices suggested that
correlating the error between two indicators of the same underlying construct would
substantially reduce chi-square and improve ﬁt.

For the second measurement model, the error of two of the indicators for family
support and monitoring (F84 and F85) were correlated and this improved model ﬁt
[x2(259, N = 103) = 331, p = .002, standardized RMR = .073, RMSEA = .052, IF I =

.931]. These questions are distinctly related in that one asks about knowing their child’s

70

friends while the other asks about knowing the parents of their child’s ﬁiends. Thus, it
made conceptual that these items would share error variance. While the ﬁt indices
showed improvement, the IFI was still a bit low and a review of the standardized
residuals and modiﬁcation indices suggested a further possible correlation among the
errors of the indicators in another construct.

For sense of community, the modiﬁcation indices suggested that the error for two
of the action items could be correlated, action 2 and action 3. Again, there was both
conceptual and empirical support for correlating the errors of these items. One of these
items asked about people on the block feeling they have a voice in important community
issues and the other asks about participation in block groups such as neighborhood
watches and block clubs. These are the type of local informal and formal neighborhood
groups created to address important community issues and provide residents with a voice
and collective action in community affairs. Thus, in a theoretical sense, it again made
sense that the errors of these two items would share variance. Empirically, the goodness
of ﬁt statistics improved and suggested good model ﬁt when these errors were correlated
in the third measurement model [12(258, N = 103) = 319, p = .005, standardized RMR =
.073, RMSEA = .048, IFI = .942]. Please see Figure 3, which displays the ﬁnal
measurement model while the factor loadings for the measurement model are presented
in Table 4. The factor loadings for the additional outcome variables are also included at

the bottom of the table.

71

Structural Models
Conventﬂral Activity

A two-stage process was utilized to derive the ﬁnal structural model for all
outcome variables. First, a structural equation model was conducted on the conceptual
model as presented in Figure 2. In this ﬁrst stage, a path from block stability to
delinquent peers was also included to assess the contagion model of neighborhood
effects, which suggests that delinquent peers are more abundant in disadvantaged
neighborhoods. The second stage consisted of evaluating whether or not the direct
effects of the exogenous variables (block stability and block income) and the contagion
path should be retained for the ﬁnal model. Thus, if any of the exogenous variables did
not exert a signiﬁcant direct path, or if the path ﬁom block stability to delinquent peers
was not signiﬁcant, these paths were set to 0 and a chi-square difference test was
conducted to assess if these paths should stay in the ﬁnal model. If the chi-square was
not signiﬁcant, these paths were removed for the ﬁnal model. In order to facilitate
comparison across the various youth outcome variables, all of the indirect paths were
included in the ﬁnal model.

The initial model for the outcome of conventional activity produced adequate ﬁt
indices (Please see Table 5) although ﬁve of the proposed paths were not signiﬁcant.
Regarding the paths that could be removed, the direct path from block stability to
conventional activity was insigniﬁcant (.14) and the path ﬁom block stability to
delinquent peers (-.07) was also insigniﬁcant. These paths were set to 0 and a chi-square

difference test was conducted to evaluate if model ﬁt worsened with their removal. The

72

chi-square difference test was insigniﬁcant, thus, these paths were deleted for the ﬁnal
model.

The ﬁnal structural model for conventional activity is presented in Figure 4
[x2(288, N = 103) = 359, p = .003, standardized RMR = .085, RMSEA = .05, IFI = .933].
Block income exerted a signiﬁcant direct effect (.27 *) with higher income neighborhoods
leading to increased rates of conventional activity, which was measured as the number of
school, community, and religious activities. Again, the direct impact of block stability
was insigniﬁcant and removed ﬁom the model.

Indirectly, block stability exerts a signiﬁcant positive inﬂuence on sense of
community (.42*) and family support and monitoring (35*). Sense of community
signiﬁcantly increases informal social control (.40*) but this indirect pathway does not
have an impact on conventional activity (.20). The pathway ﬁom block stability to
family support and monitoring signiﬁcantly decreases afﬁliation with delinquent peers
(-.4l *) but again does not signiﬁcantly impact rates of conventional activity (-.10).
However, block stability does exert an indirect effect by increasing family support and
monitoring, which directly increases conventional activity (.35*).

Overall, it was found that the residential stability of neighborhoods indirectly
increased youth’s participation in conventional activity through its inﬂuence on family
support and monitoring. The income level of the neighborhood was also found to have a
direct positive impact on conventional activity while its proposed indirect impact via
family support and monitoring was not supported by the data. Finally, the path ﬁom
block stability to afﬁliation with delinquent peers was not signiﬁcant and removed from

the model.

73

Minor Delinquency — self-rpmrt

The initial model for the outcome variable of self-report minor delinquency
produced marginally adequate ﬁt indices (Please see Table 6). The IF I was low,
standardized RMR a bit high, although the RMSEA statistic suggested adequate ﬁt.
Regarding the direct effects of the exogenous and manifest variables, both block stability
and income had little impact on minor delinquency. These direct paths were removed,
along with the path ﬁ'om block stability to delinquent peers, due to an insigniﬁcant chi-
square difference for the ﬁnal model.

The ﬁnal structural model for self-report minor delinquency is presented in Figure
5 [38014, N = 103) = 403, p = .000, standardized RMR = .09, RMSEA = .05, IFI =
.920]. As can be seen from the ﬁnal model, the hypothesized direct impact of block
income and stability did not hold for this outcome variable. Thus, both of these direct
paths were removed. Indirectly, block stability has a substantial impact on both sense of
community (.42*) and family support and monitoring (.33*) and ultimately inﬂuences
minor delinquency through the latter pathway. As before, block stability facilitates the
development of sense of community and this variable leads to higher levels of informal
social control in the neighborhood. However, block stability’s impact on minor
delinquency is negligible as there is no relationship between informal social control and
minor delinquency (.01). As in the case of conventional activity, block stability
facilitates family support and monitoring which subsequently reduced youth’s afﬁliation
with delinquent peers (-.40*). Afﬁliation with delinquent peers is signiﬁcantly positively

associated with higher rates of minor delinquency (46*); thus, block stability exerts a

74

strong indirect effect on this outcome via this pathway. The results also show that the
direct path from family support and monitoring is not related to minor delinquency (.15).
Minor Delinquency — ofﬁcial

The initial model for the outcome variable of ofﬁcial minor delinquency produced
marginally adequate ﬁt indices (Please see Table 7) although there were still three
insigniﬁcant pathways. For the ﬁnal model, the direct path from block income was
removed as well as the path from block stability to delinquent peers. The ﬁnal structural
model for ofﬁcial minor delinquency is presented in Figure 6 [x2(242, N = 103) = 306, p
= .003, standardized RMR = .088, RMSEA = .052, IF I = .938]. As can be seen ﬁom the
ﬁnal model, the direct path of block stability to minor delinquency was quite large and
remained in the ﬁnal model (-.46*) while block income was unrelated to ofﬁcial minor
delinquency (-.09) and this path was removed from the model.

Indirectly, block stability increased sense of community and informal social
control, which was associated with lower rates of official minor delinquency (-. 14),
although this path is not statistically signiﬁcant. Block stability also substantially
increased family support and monitoring levels but this path was not signiﬁcantly
associated with minor delinquency (-.03). Family support and monitoring did
signiﬁcantly decrease afﬁliation with delinquent peers (-.39*) but the pathway from
delinquent peers to ofﬁcial minor delinquency was also insigniﬁcant (-.17). Finally,
block income also does not exert an indirect effect on this outcome variable through its
inﬂuence on family support and monitoring (.01 ). Thus, all of the indirect pathways from
block stability and block income are ultimately not signiﬁcantly related to ofﬁcial rates of

minor delinquency.

75

Severe Delinquency: self-report

The ﬁnal structural model for severe delinquency is presented in Figure 7, while
the goodness of ﬁt indices for all the structural runs are displayed in Table 8. The ﬁnal
model produced adequate goodness of ﬁt statistics although the [F I is still a bit low
[x2(263, N = 103) = 363, p = .000, standardized RMR = .089, RMSEA = .061, IF I =
.910]. The ﬁnal structural model for severe self-reported delinquency includes direct
paths from the exogenous variables of block stability and income and an indirect effect of
block stability via its impact on family support and monitoring and association with
delinquent peers. Similar to ofﬁcial minor delinquency, the direct impact of block
stability remains and is quite large (-.45*). Thus, in the case of self-reported severe
delinquency, the residential stability of a neighborhood signiﬁcantly decreases this
serious type of offending pattern. Equally strong, but a rather surprising ﬁnding, is the
positive path coefﬁcient between block income and severe delinquency (.43*), suggesting
that higher income neighborhoods lead to higher rates of severe delinquency.

Block stability also indirectly decreased self-reported severe delinquency by
promoting family support and monitoring, which in turn, decreased afﬁliation with
delinquent peers (-.40*). Since afﬁliation with delinquent peers is positively associated
with severe delinquency (.35*), block stability indirectly decreased severe delinquency.
The pathway ﬁom block stability to sense of community and informal social control was
signiﬁcant, however, the paths from these variables did not signiﬁcantly impact rates of
severe delinquency (.04). Block income was also not signiﬁcantly associated with family
support and monitoring (.02), and thus, did not exert an indirect effect on self-reported

severe delinquency.

76

Severe Delinquencv - ofﬁcia_l

The ﬁnal structural model for ofﬁcial severe delinquency is presented in Figure 8,
while the goodness of ﬁt indices for the structural runs are displayed in Table 9. The
ﬁnal model produced excellent goodness of ﬁt statistics [x2(242, N = 100) = 293, p =
.013, standardized RMR = .087, RMSEA = .046, IFI = .950]. In regard to the direct
effects of the exogenous variables, block stability retains a large and signiﬁcant impact
on ofﬁcially reported severe delinquency (-.41 *) while block income had no relationship
to severe delinquency (-.04) and this path was dropped from the model. The path from
block stability to afﬁliation with delinquent peers was also not signiﬁcant and dropped
from the ﬁnal model.

Indirectly, the path from block income to family support and monitoring was also
not signiﬁcant and did not exert any indirect impact on ofﬁcial severe delinquency.
Block stability has a substantial effect on severe delinquency via sense of community and
informal social control as well as its impact on fanrily support and monitoring and
affiliation with delinquent peers. Block stability increases both sense of community and
informal social control, which is negatively associated with ofﬁcial rates of severe
delinquency (-.16*). Block stability also facilitates family support and monitoring and
this variable signiﬁcantly reduces afﬁliation with delinquent peers (-.39*). With ofﬁcial
severe delinquency, however, the path from delinquent peers to severe delinquency is
insigniﬁcant (-.17).

Alcohol and Drug Use — self-report
The ﬁnal structural model is presented in Figure 9 and the goodness of ﬁt indices

are displayed in Table 10. The ﬁnal model produced adequate goodness of ﬁt statistics

77

[38065, N = 103) = 335, p = .002, standardized RMR = .086, RMSEA = .051, IF I =
.936]. The direct paths from block stability to self-reported alcohol and drug use (-.08)
and block income to self-reported alcohol and drug use (.03) were both insigniﬁcant and
removed from the ﬁnal model. The path from block stability to delinquent peers (-.07)
was also insigniﬁcant and removed because the chi-square difference was not signiﬁcant
when all three of these paths were set to 0.

Block stability did exert an indirect effect on alcohol and drug use via its impact
on family support and monitoring. Speciﬁcally, block stability increased family support
and monitoring (33*), which signiﬁcantly decreased youth’s afﬁliation with delinquent
peers (-.37*). In the case of self-reported alcohol and drug use, the path coefﬁcient from
affiliation with delinquent peers to alcohol and drug use was .72*, suggesting a very
strong relationship between these two variables. Since family support and monitoring
signiﬁcantly reduces afﬁliation with delinquent peers, it has the potential to offset this
strong relationship. While block stability also displayed a signiﬁcant relationship with
sense of community (.42*), this pathway did not have a signiﬁcant impact on alcohol and
drug use as informal social control was not signiﬁcantly related to this outcome variable
(-.08).

Alcoholﬁand Drung — ofﬁcﬂ

The ﬁnal structural model for ofﬁcial alcohol and drug use is presented in Figure
10 while the goodness of ﬁt indices are displayed in Table 11. The ﬁnal model produced
adequate goodness of ﬁt indices [x2(242, N = 100) = 302, p = .006, standardized RMR =
.086, RMSEA = .050, IFI = .941]. In terms of direct effects of the exogenous variables,

block stability was signiﬁcant and retained in the ﬁnal model (-.38*) while block income

78

was not signiﬁcant and deleted from the ﬁnal model (-.12). The path from block stability
to delinquent peers was not signiﬁcant and also deleted from the ﬁnal model.

Indirectly, block income’s impact on family support and monitoring was not
signiﬁcant consequently this manifest variable did not exert any indirect effects on
ofﬁcial youth alcohol and drug use. While block stability continued to have signiﬁcant
relationships with sense of community and family support and monitoring, these indirect

pathways did not signiﬁcantly impact ofﬁcial alcohol and drug use violations.

. “r
l

Speciﬁcally, the path from informal social control to this outcome variable was .05 and

ri-

P‘

the path from afﬁliation with delinquent peers was -.01.
The Moderating Effect of Family Support and Monitoring on Youth Outcomes

Family support and monitoring was also assessed as a potential moderating
variable between informal social control and youth outcomes. However, for all outcome

variables, family support and monitoring did not signiﬁcantly moderate this relationship

(Please see Table 12).

79

Figure 3

Measuremen____t__ Model

67 68 Q Q3 6191
T
FMlFemoTlewll aanl acts ll acts 1

1

-1 Conventional
Sense of Activity

Community (I ‘

’9:

e an

@1 E
Stability

@1 a,

Family Support.
8: Monitoring

 

;.

.2:
3PM
::

lnforrnal Sod.l
°trol

 

80

 

Table 4

Egg] Mea_surement Model ﬁctor Loadings (N = 103)

 

 

Latent Construct Indicators Factor Loadings
Block Stability (BS) B81 .777
BSZ .751
B83 .827
BS4 .626
Sense of Community (SOC) EMO3 .776
EMO4 .728
EMOl 0 .882
ACT2 .674
ACT3 .737
ACTS .741
Informal Social Control (ISC) ISC4 .809
ISCS .732
ISC6 .904
ISC7 .832
Family Support and Monitoring PSI .505
(FSM)
FSZ .745
F S3 .697
FS4 .590
FSS .270
Delinquent Peers (DP) DP2 .624
DP3 .685
DP4 .765
Conventional Activity (CA) CA1 .655
CA3 .441
CA4 .349
Self-Reported Minor SRD5 .560
Delinquency
SRD6 .853
SRD7 .460
SRDll .692
Self-Reported Severe SRD16 .914
Delinquency
SRD17 .534

 

81

Table 5

Goodness of Fit Indices & Chi-Square Difference Results for Conventional Activity

 

 

p Std. x2
Model X2 df value RMR RMSEA IFI Difference
Initial 359 286 .002 .085 .050 .932
.906, 2
Final 359 288 .003 .085 .050 .933 p = .636

 

82

Figure 4

Final Structural Model for Conventional Activity

 
   
   
    
    
 
 

Sense of
Community

   

lnforrnal Social

.42*
Control

  
   
 
   
   
      
  

Block
Stability

'32 Conventional

Activity

 

Block
Income

 

 

 

Delinquent

Fam Support Peers

& Monitor

      

83

Table 6

Goodness of Fit Indices & Chi-Square Difference Results for Minor Delinquency

 

 

self-r§p_ort
Std. x2
Model X2 (If p RMR RMSEA IFI Difference
value
Initial 403 311 .000 .090 .054 .921

Final

403 314 .000 .090 .05 .92 .401,3=
.940

 

84

Figure 5

Final Structural Model for Minor Delinquency - self-rqport

 
        
    
  
    
      

Sense of
Community

   

lnforrnal Social
Control

.42*

.32*

  

Minor
Delinquency

 

Block
Income \

 

 

 

Delinquent
Peers

 

Fam Support
8: Monitor

      

85

Table 7

Goodness of Fit Indices & Chi-Square Difference Results for Minor Delingreng -
Official

 

 

Std. x2
Model X2 df p value RMR RMSEA IFI Difference
Initial 305 240 .003 .088 .052 .938
Final 306 242 .003 .088 .052 .938 1.008, 2 =
.604

 

86

Figure 6

Final Structural Model for Minor Delingprency - ofﬁcia_l

 
   
   
  

Sense of
Community

    
    
 
 

Informal Social

.40*
Control

     
 
  
    
    
    

Block
Stability

.32"

  

Minor
Delinquency

 

Block
Income

 

 

 

Delinquent
Peers

   

   

Fam Support
& Monitor

87

 

Table 8

Goodness of Fit Indices & Chi-Square Difference Results for Severe Delinquency
- self-rpmrt

 

 

p Std. x2
Model x2 df value RMR RMSEA IFI Difference
Initial 363 262 .000 .089 .062 .909
Final 363 263 .000 .089 .061 .910 .379, 1 =
.538

 

 

88

Figure 7

Final Structural Model for Severe Delinquency - self-report

 
   
   
  

Sense of
Community

     
    
      

Informal Social

.33*

 

Delinquency

Block
Income

 

 

 

Delinquent

Fam Support Peers

& Monitor

      

89

 

Table 9

Goodness of Fit Indices & Chi-Square Difference Results for Severe Delinquency -
ofﬁcial

 

 

Std. x2
Model x2 df p RMR RMSEA IFI Difference
value
Initial 293 240 .011 .088 .047 .949
Final 293 242 .013 .087 .046 .950 .346,2=
.841

 

90

Figure 8

Ei_n_al Structural Model for Severe Delipquencv - ofﬁcial

 

’ \\

/ \\\

1”
;

/
/

Sense of “_.\_\.39*
39* ,3 Community // ‘

, \J/ Informal Social )
”‘"“ '/ \ Control

1,, \
_,/ \ ,Il’ \
,// \»\ // 4’

( Block \ -.16*
‘ . . //'i \N'mn pp“ - * \\

‘\

 

 

  

/ V ’ \ a x ‘‘‘‘‘‘‘‘ \ A
N\KHH\—‘-_“ \\\
31 * ( \\ \ ‘19/ \\
\ \\ Severe
\ * \ Delinquency /
Block \32 ,/
\ ///// //
Income i \\ _.1 2 , .
\‘\\ .02 \\\ / , ///
\ \ / i],
\\\ \ / ,/

Fam Support \p__:.39'( Delinquent
& Monitor /,/ +ikpee_rs/’/
\V‘

91

Table 10

Goodness of Fit Indices & Chi-Square Difference Results for AlcohoLand DrugUse —
self-r§p_ort)

 

 

Std. it2
Model x2 df p RMR RMSEA IFI Difference
value
Initial 334 262 .002 .086 .052 .934
final 335 265 .002 .086 .051 .936 900,3:
.825

 

 

92

Figure 9

Final Structural Run for Alcohol and DruLUse - self-report

 
   
   
  

Sense of
Community

    
    
 
 

lnforrnal Social

.42*
Control

      
      
  

Block
Stability

.32*

 

 

 

 

Delinquent

Fam Support Peers

& Monitor

      

93

Table 11

Goodness of Fit Indices & Chi-Square Difference Results for Alcohol and Drugyse —
ofﬁcial

 

 

Std. XT
Model x2 df p value RMR RMSEA IFI Difference
Initial 300 240 .005 .087 .051 .941
Final 302 242 .006 .086 .050 .941 1.565, 2 =
.457

 

94

Figure 10

Final Structural Run for Alcohol and Drug Use - ofﬁcial

.40*

Block
Stability

.32”

 

Block
Income

 

 

 

Sense of .39*
Community Informal Social
Control
.05
-.38*
Alcohol &
33,, Drug Use
-.08
_02 -.01

81 Monitor Peers

95

Table 12

Moderating Effect of Family Support and Monitoringon Youth Outcomes

 

Outcome Variable

Conventional Activity

Beta

.62

FSM x ISC

Minor Self-Reported
Delinquency .1 8

FSM x ISC

Minor Ofﬁcial
Delinquency .14
F SM x ISC

Severe Self-Reported
Delinquenqv .00

FSM x ISC

Severe Ofﬁcial
Delinquency .21
FSM x ISC

Self-Reported Alcohol
was .12
FSM x ISC

Ofﬁcial Alcohol and
D_ru.g§ -.00

FSM x ISC

l

2

O

 

Unstandardized

96

T-Value

1.49

.89

.66

.40

1.76

.32

-.86

P-Value

.14

.38

.51

.69

.08

.75

.39

te. F SM = Family Support and Monitoring and ISC = Informal Social Control.

CHAPTER 4

DISCUSSION

The Role of Neighborhood Stability

Overall, the most consistent ﬁnding ﬁom the current study was the strong role of
neighborhood stability in the majority of the structural equation models - from
conventional activities to minor and severe delinquency. Returning to the old-Chicago
school and the original formulation of an ecological theory of urban dynamics from
which social disorganization emerged, it was theorized that residential stability was the
strongest predictor for the overall health of a community (Park et al., 1967). While most
researchers ignored this structural feature and solely focused on the role of poverty
(Byme & Sampson, 1986; Komhauser, 1978), there have been several important studies
over the years that have documented how it is the compilation of negative structural
characteristics, particularly residential turnover, that negatively impact communities and
those who live there.

For instance, as discussed earlier, Bursik and Webb (1982) demonstrated that
although data ﬁom 1940 to 1970 in Chicago seemed to disconﬁrrn the basic tenets of
social disorganization theory, it was only because the nature and pace of residential
turnover changed dramatically during those decades. Once the federal government
outlawed discriminatory housing practices in the late forties, residential turnover around
the traditional black belt exploded. Real estate speculation, white ﬂight to the suburbs,
and intense and sometimes violent battles occurred throughout the South side of Chicago

as African-Americans gained greater access to housing, despite the intense efforts of

97

many white ethnic neighborhoods (Hirsch, 1998). Once Bursik and Webb accounted for
these factors, they found that delinquency patterns essentially stayed the same as they had
in the past. In essence, rather than disconﬁrming social disorganization theory, this study
validates its fundamental hypotheses by demonstrating the vital importance of
neighborhood structural characteristics, particularly residential stability, on the youth
outcome of delinquency.

Another seminal article that directed attention on the importance of the residential
stability of a neighborhood comes from Kasarda and Janowitz’s (1974) study on
community attachment. In this study, they compared a model based on the work of Wirth
and Toennies, which blamed increasing size and density - essentially the process of
urbanization - as the causes of community dislocation to the ecological model of the old-
Chicago school, which argued that residential stability was the key factor. The results
supported the hypothesized importance of residential stability in community attachment
and satisfaction. As these authors stated,

First, location in communities of increased size and density does not weaken bonds of

kinship and ﬁiendship. Instead, length of residence is a central and crucial factor in

the development of these social bonds. Second, location in communities of increased
size and density does not result in substitution of secondary for primary and informal
contacts Third, increased population size and density does not signiﬁcantly
weaken local community sentiments. But community sentiments are compatible with

desire to avoid the negative features of local community life” (p. 339).

Thus, the ﬁnding of the primary importance of block stability from the current study

supports previous research and has many implications for community-based programs

98

and initiatives designed to decrease negative youth outcomes. In fact, the results from the
current study suggest that efforts to assist children and youth in disadvantaged
neighborhoods will have little success if they do not address neighborhood structural
factors, which have both strong direct and indirect effects on youth outcomes.
Official Delinquency vs. Self-qu_orted Delinquency

Social disorganization developed in the early to middle part of the twentieth century,
thus, this model was extensively utilized in explaining ofﬁcial records of crime and
delinquency since self-report data was not collected during this time period (Bursik,
1988; Shaw & McKay, 1942). Since the development of victimization surveys, there has
been perpetual debate in the ﬁeld of criminology as to what self-report and ofﬁcial crime
and delinquency data actually measure since research has found conﬂicting results
depending which source of data is utilized. Self-report data has been criticized as
equating minor delinquency with severe delinquency (Hindelang et al., 1979), while
many studies have shown a strong correlation between ofﬁcial data and individual and
neighborhood socioeconomic status suggesting that there is substantial bias in those
individuals who are apprehended and enter the criminal justice system (Hagan, Gillis, &
Chan, 1978; Hindelang et al., 1979; Menard, 1987; Sampson, 1986a). In fact, some
research has even found a negative correlation between self-report and ofﬁcial measures
of the same crime (O’Brien, 1983).

The results from this study showed that there was no relationship between self-report
and ofﬁcial minor delinquency (-.08). In the case of ofﬁcial and self-report alcohol and
drug use, there was also an insigniﬁcant relationship (.04) while a signiﬁcant positive

relationship was found in the case of severe delinquency (.19*). Thus, as delinquency

99

moves from relatively minor infractions such as stealing to more serious delinquency, the
relationship between self-report and ofﬁcial data increases and becomes signiﬁcant.
While this is a good ﬁnding in that it suggests the measures are signiﬁcantly related in the
case of less ﬁequent and more severe delinquency, nevertheless, the correlation was
small suggesting that there is still a wide discrepancy between the two measures.
Furthermore, similar to recent updated systemic models of social disorganization
(Simcha-Fagan & Schwartz, 1986), the current study found that the social disorganization
model “ﬁt” the data better when ofﬁcial verses self-report data was analyzed. For
instance, in the case of self-reported severe delinquency, the path from neighborhood
stability to sense of commrmity, informal social control, and this outcome variable was
not signiﬁcant. But, in the case of ofﬁcial severe delinquency this indirect pathway was
signiﬁcant.

Since self-report measures have been utilized in delinquency research, there have
been many competing theories proposed to explain the different ﬁndings between self-
report and ofﬁcial data. First, the disparity could suggest that police target
neighborhoods with higher levels of residential instability and lower incomes under the
assumption that poorer and less stable neighborhoods contain more “delinquents”. Thus,
by increasing their presence and time in these neighborhoods they subsequently witness
and arrest more people for crime and delinquency. Second, it could suggest that more
stable neighborhoods with higher incomes facilitate the development of social networks,
sense of community, and neighborhood norms, which result in increased informal social

control in the neighborhood. In other words, in neighborhoods where people know each

100

other and each other’s kids, it is more likely that they will directly intervene when they
see misbehavior, or at least, inform the parents of the youth involved.

Thus, there is less need for formal institutions such as the police to intervene since the
community is able to reduce behavior that can lead to serious injury or victimization.
Whereas, in neighborhoods with people constantly moving in and out, people do not have
the time or the incentive to get to know each other, reach consensus on what is and what
is not acceptable behavior in the community, and then act to stop behavior that violates
community norms. Thus, these neighborhoods rely heavily on institutions such as the
police department to institute and maintain minimal levels of social control and safety in
the neighborhood. While elements of both theories are probably valid, it is argued that
the latter scenario provides a better explanation for the signiﬁcant negative impact of
informal social control on ofﬁcial severe delinquency and lack of impact on self-report
severe delinquency found in the current study.

Therefore, while police departments are often heavily criticized for bias and
discriminatory enforcement, they may simply be responsible for enforcing laws that
deuimentally impact residents of disadvantaged communities. Nevertheless, whether
intended or not, since residents living in these disadvantaged neighborhoods are
overwhelmingly minorities, the net result is discriminatory in nature (Bishop & Frazier,
1996; Donziger, 1996; Miller, 1996; Wordes, Bynum, & Corley, 1994). For example,
even though the rates of drug use are essentially equivalent among racial and ethnic
groups, and Whites constitute the majority of the US. population, ninety percent of the
adult prison admissions in 1993 for drug offenses were either Black or Hispanic

(Donziger, 1996).

101

As concentrated levels of poverty increased throughout the eighties and nineties along
with it came concomitant social problems such as crime and delinquency, drug abuse,
and child maltreatment (Coulton et al., 1995). At the same time, funding for all
components of the criminal justice system increased dramatically throughout the eighties
and nineties. For instance, throughout the 1980s, police expenditures increased by 416%,
court system by 585%, prosecution and legal services by 1,109%, and corrections by
990% and by the mid-1990s the United States budget for the crime control industry
exceeded $200 billion (Miller, 1996). In fact, the United States now has the highest rate
of incarceration per capita among the Western democracies. Thus, rather than dealing
directly with the structural and economic antecedents of crime and drug use, the United
States instead has utilized the criminal justice system to deal with its social problems.

The result of such a policy has been disastrous for minorities. While Aﬁican-
American juvenile comprise 15% of the juvenile population, they account for 26% of
arrests, 45% of delinquency cases involving detention, and predominate among youth
sent to adult prison (Snyder & Sickrnund, 1999). Moreover, the substantial increase in
funding for the prison industrial complex meant less funding was available for
progressive polices and programs such as drug prevention and treatment and community
development initiatives.

Overall, rather than simply blaming the police or those who live in disadvantaged
communities, the results of the current study and past research suggest the need for
alternatives to aggressive police enforcement in disadvantaged neighborhoods. In fact,

the act of removing such a large percentage of the male population in disadvantaged

102

neighborhoods most likely increases the instability and disorder in the community,
thereby, ultimately increasing crime and delinquency.
Measuring Communig Social Organization

As discussed in the introduction, there have been many different types of measures
used to assess the “village-like” potential for communities. Some studies have looked at
the number of contacts or weak ties in the community or the number of residents
participating in neighborhood organizations, while others have looked at the level of
informal social control. Perhaps the most comprehensive measure utilized to date has
been the construct of collective efﬁcacy employed by Sampson, Raudenbush, & Earls
(1997). This measure combined both items on social connection among residents and
willingness to intervene to stop youth misbehavior in the neighborhood and was deﬁned
as “. .. a task-speciﬁc construct that relates to the shared expectation and mutual
engagement by adults in the active support and social control of children” (as cited in
Sampson, Morenoff, & Earls, 1999, p.635).

However, it has been argued and modeled in this study that the mediating variable of
SD theory, community social organization, and informal social control are distinct
variables. In order to correctly measure the process of community organization and
disorganization that Shaw and McKay described, it is necessary to model and measure all
of the social and behavioral processes involved. One contribution of the current study is
that it further delineates the indirect path from neighborhood structural disadvantage to
community social organization, informal social control, and youth outcomes. Recent
research has also demonstrated that the relationship between neighborhood structural

characteristics, neighborhood social characteristics, informal social control, and crime is

103

much more complex than traditionally modeled. To appropriately represent this
relationship, a nonrecursive model seems necessary since crime and delinquency
certainly impact neighborhood social and structural characteristics as well as the
willingness of residents to intervene (Bellair, 2000; Brower et al., 1983; Warner &
Rountree, 1997).

For instance, crimes such as burglary and other property offenses may increase
neighborhood surveillance and intervention while more violent crime such as assault and
battery may reduce intervention out of a fear of retaliation (Korbin & Coulton, 1997).
Thus, there are several valid reasons to replace, or, at least augment the current measures
of updated systemic social disorganization models, which have relied too heavily on
behavioral measures such as informal social control. Moreover, the relationship among
neighborhood structural characteristics, social characteristics, and willingness to
intervene is complex and often depends on the context of communities under study.
Thus, all of the important structural, social, and behavioral variables proposed by social
disorganization theory must be included in order to completely understand the complex
and reciprocal relationship among these variables which ultimately result in differential
community and youth outcomes such as delinquency.

The Indirect Effect of Neighborhood Stabilig; via Family Support & Monitoring

While the majority of neighborhood effect studies have concentrated their efforts at
understanding the relationship between community social organization and youth
outcomes, there are several additional pathways through which neighborhood
disadvantage can have a deleterious impact on youth outcomes. In terms of the lower

part of the conceptual model (See Figure 2), the indirect path from neighborhood stability

104

to family support and monitoring was consistently signiﬁcant and usually in the mid-
thirties (e.g., .35* in the case of conventional activity). For this outcome variable, the
direct path from family support and monitoring to conventional activity was also
signiﬁcant (.39*). More often though, there was not a direct and signiﬁcant relationship
between family support and monitoring and the outcome variables. Usually, the
relationship between neighborhood stability, family support and monitoring, and youth
outcomes was much more complicated. With the delinquency outcomes, neighborhood

stability signiﬁcantly increased family support and monitoring, which subsequently E

 

signiﬁcantly decreased afﬁliation with delinquent peers. This is an important relationship
because afﬁliation with delinquent peers signiﬁcantly increased negative youth outcomes,
particularly with self-report data. For example, in the case of self-reported alcohol and
drug use the path ﬁom delinquent peers to this outcome variable was extremely strong
(71*)

Thus, stable neighborhoods facilitated positive parenting strategies, which were able
to reduce afﬁliation with delinquent peers, and consequently, the strong role of this
variable on negative outcomes like self-reported alcohol and drug use. Previous
neighborhood effects studies which also incorporated parental monitoring and support
measures found that neighborhood disadvantage signiﬁcantly disrupted parenting and
resulted in increased negative youth outcomes (Brodsky, 1996; Larzelere & Patterson,
1990; Patterson & Dishion, 1985; Sampson & Laub, 1994; Simons et al., 1996). There
also have been a number of studies that found neighborhood disadvantage negatively
impacted parenting through other indirect pathways such as increasing family stress and

conﬂict (Paschall & Hubbarb, 1998), increasing erratic and harsh discipline (Grifﬁn et

105

al., 1999; Sampson & Laub, 1994), decreasing maternal warmth and responsiveness
(Klebanov et al., 1994), and decreasing parents’ sense of efﬁcacy (Elder et al., 1995).
Taken together, these studies support the multiple indirect pathways neighborhood
disadvantage detrimentally impact parents and ultimately their children. As models of
neighborhood disadvantage become more complex and are not simply limited to one or
two parenting variables in a narrow methodological approach (Florsheim, Tolan, &
Gorman-Smith, 1998; Steinberg, Mounts, Lambom, & Dombusch, 1991), the ﬁndings
can inform the development of prevention and intervention programs which account for
the complex ways disadvantaged neighborhoods directly and indirectly impact parents
and parenting practices.

The role of Neighborhood Income

Another consistent ﬁnding throughout most of the youth outcome variables was the
rather negligible role of neighborhood income. Contrary to the proposed hypothesis,
block income did not indirectly impact any assessed outcome variable through its
inﬂuence on family support and monitoring. It was hypothesize that more advantaged
neighborhoods would have more youth sponsored activities and institutions and that this
would facilitate parents in supporting and monitoring their adolescent’s activities.
However, this path was insigniﬁcant in every structural model.

As far as a direct impact, neighborhood income only produced a signiﬁcant path for
the outcome variable of conventional activity (29*) and self-reported severe delinquency
(43*). As discussed in the limitations section, this may be the result of using block
income instead of the more traditional and comprehensive measure of socioeconomic

status. However, given the paucity of ﬁndings for income and large role of neighborhood

106

stability, it seems that this explanation cannot totally justify the results of the current
study. Another possible reason for the lack of direct and indirect eﬁects for block income
may lie in the structural composition of the sampled city. Unlike the majority of
neighborhood effects studies, the current study was conducted in a mid-size, Midwestern
city that does not have large pockets of either extreme wealth or extreme poverty. Given
that many neighborhood effect studies purposely oversarnple residents on opposite ends
of neighborhood structural characteristics such as income to increase and capitalize on
variance (Sampson, 1993a), the lack of disparity throughout the city of Lansing may be a
major reason for the lack of ﬁnding many of the hypothesized direct and indirect effects
for block income. As a recent comprehensive literature review on neighborhood effects
found (Levanthal & Brooks-Gunn, 2000), national and multisite studies have much
greater sampling variability and the higher intercorrelations among neighborhood
dimensions in city-based studies such as this one lead to higher probability of a null
ﬁnding. Or, as other studies have hypothesized, there may be also be a tipping point that
structural factors must exceed to exert an impact on youth outcomes (Simons et al.,
1996). Nevertheless, there were many signiﬁcant ﬁndings and the neighborhood
structural and social characteristics ﬁom the current study are certainly more
representative of medium-sized cities than the majority of neighborhood effects studies,
which are usually completed in the largest U. S. cities.
Moderating Role of Family Support and Monitoring

The current study hypothesized that family support and monitoring would act as
both a mediator and moderator. The results showed that neighborhood advantage

facilitated parental support and monitoring, which decreased afﬁliation with delinquent

107

 

peers and resulted in less negative youth outcomes. In this manner, family support and
monitoring transmitted much of the inﬂuence of neighborhood advantage on youth
outcomes. However, it was hypothesized that family support and monitoring could act as
a moderating variable in two different ways.

First, as discussed in previous research (Furstenberg, 1993; Sampson, 1993a;
Sampson et al., 1999), parental supervision, monitoring, and other practices are strongly
inﬂuenced by the level of community social organization. In neighborhoods
characterized by consensual norms and a sense of community, parents can count on
fellow residents to supervise and intervene when their youth are misbehaving in the
neighborhood. Thus, their own level of supervision and monitoring is supported when
they are not with their child. In this manner, it was hypothesized that the synergistic
effect of the interaction between these two sources of supervision and social control,
neighborhood-level and parental-level, could signiﬁcantly increase positive and decrease
negative youth outcomes.

Second, it was also hypothesized that parents in neighborhoods with a lack of
norms and supportive adults often utilize extremely individualistic parenting strategies
where they constantly monitor and supervise their youth and purposely restrict their
child’s interaction with others in the local community. By utilizing such community-
bridging strategies (Brodsky, 1996; Furstenberg, 1993; Furstenberg & Hughes, 1997;
Jarret, 1995; Jarret, 1997) family and parenting practices can be utilized to offset the
negative impact of neighborhood structural and social disadvantage. However, the
results indicated that family support and monitoring did not moderate the relationship

between informal social control and youth outcomes in any of the outcome variables.

108

 

Limitations

There were several limitations to this study that warrant caution in interpreting the
results. First and foremost, this was a cross-sectional study with a relatively small sample
Size for structural equation analysis. Thus, this study needs to be replicated with a larger
longitudinal sample to truly understand the impact of neighborhood effects on youth
outcomes. Second, some of the outcome variables suffered from moderate to severe
skewness and kurtosis problems. While those variables which were problematic were log

transformed prior to conducting analyses, it must be acknowledged that such

P,

distributional properties have the potential to bias SEM results. To reduce the potential 3
for errors, maximum likelihood estimation was utilized since this estimation method is
robust to skew and kurtosis problems. Third, income was utilized as an independent
variable instead of socioeconomic status, thus interpretation of the lack of impact of
neighborhood income on youth outcomes must be interpreted with caution. Finally, this
study included individual-level, family-level, and neighborhood-level variables. Since
only two households per block were utilized to create many of the neighborhood-level
variables, multilevel modeling procedures such as hierarchical linear modeling could not
be utilized for data analysis. Thus, individual and family-level variables could not be
partialled from neighborhood variables and the strong ﬁnding of the neighborhood
variables with ofﬁcial data may be confounded by the fact that both were measured at the

neighborhood-level.

109

CHAPTER 5

IMPLICATIONS FOR FUTURE RESEARCH

The current study demonstrated the strong direct and multiple indirect ways
neighborhood context impacts youth outcomes. As neighborhood effects models become
more sophisticated, these pathways will be further delineated and have important
implications for intervention programs. Empirical research can be used to guide

multilevel prevention and intervention programs to target the most important and

 

inﬂuential individual, family, and community-level variables. As the current study
showed, programs will not be successful if they do not incorporate the multiple
inﬂuences in adolescent’s lives. For instance, it was demonstrated that peers play a very
strong role in the self-reported use of alcohol and drugs. In practice, typical delinquency
and drug use prevention programs usually simply target youth and implement educational
curriculums at school or attempt to provide supervised after-school activities, a mentor,
etc. and neglect other important contextual variables such as family support and
monitoring, sense of community and informal social control, as well as the importance of
safe and stable neighborhoods. The results of the current study showed that while peers
play a strong role in alcohol and drug use, increased parental monitoring and support can
signiﬁcantly decrease this effect. Furthermore, it was found that family support and
monitoring could be signiﬁcantly increased by fostering the development of safe and
stable neighborhoods, which would then further reduce alcohol and drug use. Thus, there

are many different foci for prevention and intervention programs to target and the strong

llO

 

link between neighborhood structural and social characteristics, and ultimately youth
outcomes, suggests the need to go beyond the individual and family-level.

By working with local residents, neighborhood-level intervention programs that
are culturally and contextually valid can be developed and implemented to create safe
and supportive neighborhoods. Moreover, it is argued that programs which target the
multiple ecological transactions among and between individuals, families, and their
communities will be better able to create and sustain positive social change by
inﬂuencing the multiple factors responsible for youth outcomes.

Another implication from the current study is that the ﬁeld of neighborhood
effects should no longer be constrained to administratively deﬁned neighborhoods such
as census tracts and census block groups. In fact, a block-level conceptualization of
neighborhood offers many advantages, the greatest of which are the identiﬁable and
objective boundaries of urban blocks. However, while the current study found support
for a block-level conceptualization of neighborhood, it is readily acknowledged that not
all researchers will want to or should focus on such a small conceptualization of
neighborhood effects. For instance, block-level dynamics may be more salient for young
children than for adolescents, who are no longer restricted to the immediate
neighborhood and have friends and participate in activities throughout a much larger
geographic area. Or, block-level dynamics may be more important for some outcomes
than others. However, the main point is that individual blocks can be aggregated together
to create larger neighborhoods while the reverse is not true. Thus, by incorporating
spatial analysis software such as geographic information systems, the ﬁeld is no longer

limited to a number of pre-deﬁned and extremely large neighborhood conceptualizations

lll

 

(e. g., census tract). In the current study, a 600-foot buffer was created around each
youth’s home to approximate a block-level conceptualization of neighborhood but there
is no reason that this buffer could not have been extended to a quarter mile to represent a
larger neighborhood conceptualization. Perhaps this would have made a difference in the
strength of the various pathways for certain outcome variables such as drinking and drug
use, which are more likely to happen a greater distance from home than the other
outcome variables. In sum, the ﬂexibility offered by software programs such as GIS will
help the ﬁeld of neighborhood effects better understand the various levels or
conceptualizations of community and how they may differentially impact youth and

community outcomes.

112

 

 

Appendices

113

 

Appendix A

Indicators of Latent Constructs

114

 

 

 

Construct

Indicator

 

Block Stabilig
BS1

BS2

BS3
BS4

Sense of Community
Em3

Em4
Eml 0

A2

A3

A5

Informal Social
Control

I4

15

16

17

Family Support &
Monitoring

FS 1

FS 2

FS 3

FS 4

FS 5

Afﬁliation with
Deliqqpent Peers
DP2
DP3
DP4

The majority of residents on this block rent their houses.
When people come to live on this block, they tend not to stay
here long.

People move in and out of this block a lot.

I would like to live on this block for at least another ﬁve years.

 

People who live on this block think of themselves as a
community.

People on this block feel connected to each other.

A feeling of community spirit exists among the residents on this
block.

People on this block have a voice regarding important
community issues.

People on this block participate in neighborhood organizations
like block groups, neighborhood watches, neighborhood
associations, etc.

People on this block never do things to improve the block.

 

How likely are people on this face-block to intervene if

Children are f ﬁghting in front of your house.

A child is taking something ﬁ'om a neighbor’s house.
A child is throwing stones at another child or pet.

A child has a weapon.

I help with his homework every night.

I help my child with problems they are having at school.

I attend meetings concerning my child’s school and education.
I know ’s ﬁiends.

I know the parents of my child’s ﬁ'iends.

How many of your ﬁ'iends

Break into buildings.
Sell drugs
Use marijuana

 

115

 

Appendix B

Correlation Matrix

116

 

 

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117

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