CULTURE OF VIOLENCE: ANIMALS AS DOUBLE VICTIMS OF THE ‘ANIMAL
PRODUCTION’ INDUSTRY
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ABSTRACT
CULTURE OF VIOLENCE: ANIMALS AS DOUBLE VICTIMS OF THE ‘ANIMAL
PRODUCTION’ INDUSTRY
By
Cameron Thomas Whitley
Legal precedent and past scholarly research has clearly identified animal abuse as
a social problem. This work has linked violence against humans to past violence against
animals, but it has not looked at the determinants of animal abuse. Further, studies have
identified a positive relationship between legitimized violence in slaughterhouses and
community violence, but have not explored the effect of institutionalized
commoditization of animal life in the animal production industry on animal abuse. The
current study uses OLS regression to address both of these shortcomings, examining the
relationship between the animal production industry and animal abuse rates at the state
level and finding a significant positive relationship between the strength of the animal
production industry and reported animal abuse. Using the theories of institutional social
distance and moral dissonance, the paper suggests that this relationship exists because
institutional norms about the value and treatment of production animals are transferred to
society at large and result in elevated abuse rates.

Copyright by
Cameron Thomas Whitley
2011

Dedicated to Phyllis Whitley

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TABLE OF CONTENTS
LIST OF TABLES…………………………………………………………………………….…vi
LIST OF FIGURES……………………………………………………………………………..vii
INTRODUCTION………………………………………………………………………………...1
WORKS CITED.……………………………...…………………………….………………...…26

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LIST OF TABLES
Table 1 Descriptive Statistics…………………………………...…………………..……………15
Table 2 Bivariate Correlations………………………………...……………..……….……….…17
Table 3 OLS Predicting (Log) State Reported Animal Abuse with Standardized Beta
Coefficients and Robust Standard Errors………………………………………………...………21

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LIST OF FIGURES
Figure 1 Animal Production Employment and Animal Abuse……………...…………..………18

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Introduction
In 2007 Michael Dwayne Vick, a professional quarterback in the National Football
League pled guilty to federal felony charges for his involvement in an illegal interstate dog
fighting ring. He served twenty-one months in prison with two months of home confinement, lost
his position on the Atlanta Falcons American Football Team and subsequently filed for chapter
eleven bankruptcy. High profile perpetrators like Vick refocus public attention on animal cruelty
as a social problem, reminding us that it is both a crosscutting and ongoing issue. In addition to
this particular incident, 2007 brought with it nearly 2,000 reported cases of animal cruelty with
over 25,000 animals abused in the U.S. (petabuse.com).
The recognition of animal cruelty as a social problem is not a contemporary one. It first
gained recognition in the U.S. in the Massachusetts Bay Colony in 1641, when the first legal
code protecting domestic animals from cruelty was instituted (Francione 1996). The legal and
communal conceptions of animal cruelty have changed little over the last 370 years, focusing
almost exclusively on narrow acts of violence against domestic animals. Today, the Animal
Welfare Act is the foundation of animal cruelty legislation but excludes rats, mice and birds used
for laboratory experimentation, animals used for food and cold-blooded creatures. Though there
is a basic federal structure, inconsistencies in states’ laws and interpretations mean that an action
defined as animal abuse and aggressively prosecuted in one state may be entirely legal in another
(Gross 2006; Patterson-Kane & Piper 2009). For example, six states have enacted humane
farming laws that outlaw gestation and/or veal crates, while the remaining 44 have not legislated
on humane farming practices at all; in addition, each state identifies different species that are

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subject to protection. These inconsistencies are representative of varied attitudes towards the
value and utility of animal life.
The problem of animal cruelty is deeply embedded in how the animal “other” is
constructed; how we define the social problem is related to a number of social factors including
the “symptom” of collective group moral dissonance (Patterson-Kane & Piper 2009). As it
relates to animals, group moral dissonance refers to the process of creating a social structure that
encourages society to distance itself from animals when it faces a moral dilemma, opposing
animal cruelty but supporting animal commoditization. This process is particularly acute when
legal and commercial institutions reinforce moral dissonance by excluding particular animals
from welfare considerations, such as those in the Animal Welfare Act and the animal production
industry. Though essential to the U.S. economy and culture, the large-scale animal production
industry relies heavily on definitions of welfare and cruelty that are in conflict with those applied
to domestic animals.
With animal cruelty firmly established as a social problem, scholars have begun to
explore its social ramifications. This research has established the link between human and animal
violence, often focusing on well-cited studies connecting individual violence against humans to
previous violence against animals. A less well-known but equally important literature has begun
to explore the relationship between institutional norms of violence and community violence,
focusing specifically on the legitimated violence against animals in slaughterhouses and its
relationship to community violence against humans. This research suggests that institutionalized
and legitimized violence has a spillover effect that encourages criminal violence by influencing a
community’s culture of violence. What has not been explored is the possible spillover effect
from broader animal production, where violence may be less acute but where there is a

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pronounced commoditization of animal life. Further there has been no examination of the
relationship between industrial commoditization and animal abuse. The current study begins to
address this broad issue by asking: Is the strength of the animal production industry in a state
related to animal abuse levels? Further, is there reason to believe that the animal production
industry perpetuates communal moral dissonance and institutionalized social distance that alters
animal treatment norms in such a way as to influence rates of violence against animals?
In addition to examining the idea that commoditization influences communal norms that
affect the prevalence of animal abuse, this study explores the determinants of animal abuse,
something that is largely missing in extant work. This is a particularly important contribution
because animal abuse is a pervasive social problem that is linked to other forms of violence and
is both a reflection and potential indicator of pathologies in human society. Understanding what
drives this type of violence is thus essential.
To explore this question, I build on theories in Eco-Marxism and Green Criminology to
argue that in addition to the individual characteristics predicting animal cruelty, there are
systemic, institutionally driven norms that encourage social distance between the human and
animal other. Specifically, this paper relies on Patterson-Kane & Piper’s (2009) theory of
communal moral dissonance and Beirne’s (2004) idea of institutionalized social distance, which
suggests that institutions create norms about the treatment of animals that are transferred to
society at large and influence violent behavior. I use OLS regression to test the relationship
between the animal production industry, operationalized as animal production employment, and
animal abuse rates at the state level. I find a positive correlation between these variables and
argue that the animal production industry promotes a commoditization and objectification of
animals that transfers to broader communities and results in increased animal abuse. I use state

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level data from a number of sources and animal abuse data from petabuse.com to assess this
relationship.

Animal Production
Much attention has been paid to social problems generated by large-scale animal
production operations. However, many of these studies have centered on two primary concerns
that exclude human and animal interactions: environmental degradation (Bradford et al. 2008;
Fiala 2008; Koneswaran and Nierenberg 2008) and economic impacts, such as community costs
and the loss of small family farms (Kim, Goldsmith and Thomas 2010; Kim, Goldsmith and
Thomas 2009; Isakson and Ecker 2008). While useful, these studies do not address how the
animal production industry’s domination or construction of animals as commodities of
production may spill into the surrounding communities.
To the extent that existing work has addressed the human-animal relationship, it has done
so through case studies of the psychological effects of small-scale animal production on workers
(Arluke 1990; 1993; Birke 1994; Irvine 2004; Lynch 1988; Philips 1994). These studies have
demonstrated that workers attempt to manage their emotions by attributing limited
anthropomorphic qualities to the animals they are working with, decreasing their ability to
connect to their animals as a means of emotional self-preservation. Engaging in the required
work means that employees must emotionally disconnect from the animals they are working with
(Remy 2003; Smith 2002). Interestingly, this type of self-preservation has also been identified in
social organizations like 4-H, where children who are engaged in animal production will
eventually sell their animals for slaughter (Ellis and Irvine 2010). Arlie Russell Hochschild
(1983; 1979) defines this type of emotional remoteness in work as emotional labor. At all scales

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of production, animal production employees use emotional labor when they choose to stop
viewing animals as individuals, instead viewing them as commodities of production. This occurs
either as a form of self-preservation or in an effort to uphold work place norms. Building from
this concept, Arluke (1994b) identifies emotional management in animal production as the
caring-killing paradox, where workers are forced to care for and then kill, or recognize the
killing, of production animals. Wilkie (2005; 2010) identified the dialectic existence of caring for
and then killing (or being aware of the future slaughter) of the animal and the resulting
communication and emotional attachment in livestock production. Scholars have documented
similar emotional management processes in medical students using animals for experimentation
(Arluke & Hafferty 1996), grade school students dissecting animals (Solot & Arluke 1997) and
animal shelter workers euthanizing animals (Arluke 2006; Reeve, Rogelberg, Spitzmuller &
DiGiacomo 2006; Arluke 1994b). Kellert (1980) and Kellert and Berry (1980) argue that farmers
view animal production as commoditization.
The existing literature has made tremendous headway in identifying and understanding
the ways in which the animal production industry influences individual emotional processes;
what is missing, is a systemic, institutional approach that examines how the animal production
industry influences broader animal treatment patterns. This paper begins to fill this gap,
combining ideas from theories in Eco-Marxism and Green Criminology to argue that higher rates
of animal production employment increase reported animal abuse at the state level.

Eco-Marxism

Ecological Marxism unites the concepts of culture and nature with the traditional Marxist

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notions of labor and production and contends that capitalism separates nature and humanity,
where “the commoditization of land and labor, isolation of physical/biological objects from their
environment and…individual labor market, and the idea of individual workers as ‘factors of
production,’” (O’Connor 1998:22) takes shape. The inclusion of the natural environment in the
conceptual framework of production and commoditization allows a theoretical basis for
understanding how institutions cause environmental degradation, or in the case of animal
production, how they institute social norms that encourage people to commoditize animals,
whether within or external to the animal production industry. Eco-Marxists argue that within
capitalist societies social problems, particularly environmental ones, are only addressed when
there is an economic incentive to do so, either because the problem is so great that it creates
economic challenges or because addressing the issue will increase profit margins. New
technologies are often developed to address current issues, but are implemented without a full
understanding of potential long-term consequences. For example, in animal production the desire
for cheaper animal protein drove producers to decrease the amount of land used for production,
which in turn prompted confined animal feeding operations (CAFO). Although these facilities
decreased production costs and land use, they have generated a host of social problems such as
concentrated pollution and the collapse of small-scale farming. In addition to these social
problems, I contend that large-scale animal production has had an unforeseen systemic influence
on animal treatment patterns by promoting a culture of animal commoditization.
While traditional Marxism recognizes that production employees are concurrently
engaged in two relationships, it ignores the environmental component; Eco-Marxism addresses
this shortcoming in the following ways. First, Marxist thought argues that there is a technical
relationship between the individual and the means of production. Ecological Marxism adheres to

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this assumption, but proposes that this connection is based in the successful manipulation of
nature into a commodity of production. For animal production employees, this is the mechanized
engagement of caring for animals that they consider units of production. The psychological
dimensions of the human and animal production interaction discussed previously are nested
within this first concept; the institutional relationship proposed in this paper is nested within the
second. This second concept argues that production workers are engaged in a relationship with
institutions, it is the institutions that then regulate the technical relationship described above.
This is a multi-scale relationship where the individual is not only nested within the production
institution, but is also a member of a community within a state, nation and global network. As
production increases and the number of individuals influenced by the institution’s norms of
production swells, so too does the possibility that institutional commoditization norms will be
transferred to the surrounding community.
Fitzgerald, Kalof and Dietz (2009) provide scholarly evidence of this phenomenon in
their study of the correlation between slaughterhouses and community violence. Examining the
aggregate level, they find that as slaughterhouse employment increases so too do arrest rates,
violent crimes and sexual offences in the surrounding communities. They argue that this finding
is evidence that the institutionalized norms around violence developed within the slaughterhouse
industry are transferred to the community at large and result in violent crime. Although
slaughterhouses are considered animal manufacturing, not animal production, this study provides
foundational insight into how institutional values and norms transfer into local communities. I
build on the evidence that proximity to slaughterhouses increases human on human violence to
argue that the animal production industry promotes similar institutional norms that influence the
way that animals outside of the production industry, such as domestic animals, are treated.

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Green Criminology
The notion that animal production is correlated with animal abuse relies upon the idea
described above that the institutional norm of social distance between animals and humans can
be transmitted to society at large; but, this idea is insufficient because we must also understand
the ways in which institutional norms facilitate criminal behavior. To do this, we turn to work in
Green Criminology. Green Criminology (Lynch 1990) was established to address “crimes
committed against humanity through environmental destruction” (South and Beirne 2007:166).
This branch of criminology attempts to overcome the speciesist tendencies of mainstream
criminology by paying serious attention to harm against animals and recognizing the
interconnection of species (Beirne 1999; Cazaux 1999). Part of the interspecies research
examines the connection between human and animal violence; scholars doing this type of work
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argue that we should think of violence as “linked” , suggesting that “… most violence is linked,
and what is particular to these claimed links is that they encompass acts of violence toward
human and non-human animals” (Patterson-Kane & Piper 2009:590). For example, scholars have
identified abuse as a learned behavior, where exposure to family violence- including animal
abuse in the home- increases the likelihood that a child or adolescent will exhibit violent
behavior (e.g, Thomas and Gullone 2006; Baldry 2003; Flynn 1999; Raupp 1999; Ascione 1998;
Kellert & Felthous 1985; Ressler, Burgess & Douglas 1988). Additionally, numerous studies
have documented the connection between torturing and killing small animals and future violent
behavior (e.g., Peterson & Farrington 2007; Simmons & Lehmann 2007; Tallichet & Singer
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Growing theoretical work addressing animal abuse and family violence has been articulated as
“link(s)” (e.g., The American Human Society: Understanding The Link Between Animal Abuse
and Family Violence (Anonymous 2005))
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2006; Duncan, Thomas and Miller 2005; Charlisle-Frank, Frank & Nielsen 2004; Faver & Strand
2003; Wright & Hensley 2003; Flynn 2000a, 2000b; Flynn 1999; Arkow 1996; Felthous 1980)
(e.g., Gupta 2008; Fitzgerald 2005; Flynn 2000a, 2000b; Ascione 1998; Ascione et al. 1997).
A number of scholars have challenged the idea that it is simply violent behavior that is
linked, arguing that the behavior may actually result from socialized norms developed within
institutions and transferred to communities (Arluke 2006; Beirne 2004; Arluke 2002; Arluke,
Levin, Luke and Ascione 1999; Arluke and Lockwood; 1997). In the case of violence against
animals, Beirne (2004) explains that “whenever human-animal relationships are marked by
authority and power, and thus by institutionalized social distance, there is an aggravated
possibility of extra-institutional violence” (p.54). Because of this, Bierne and others argue that
institutions employing procedures or practices that harm animals for socially acceptable reasons
should be studied (Beirne 2002; 2004; 2007, Beirne & South 2007; Cazaux 1999; South &
Beirne 2006; Paterson-Kane and Piper 2009). The current study takes up this call by testing the
relationship between animal production and animal abuse. Although animal abuse is a growing
field of scholarly inquiry (e.g., Patterson-Kane & Piper 2009; Goodney-Lea 2008; Hackett &
Uprichard 2007; Piper 2003), there are gaps in the literature addressing how the norms of largescale animal production institutions reduce animals to commodities of production and how these
institutional norms may spill into the surrounding communities.

Data and Methods
Sample
The sample used to test the relationship between employment in the animal production
industry and reported animals abused includes 48 states with 56,001 reported animals abused.

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Data come from a combination of secondary sources, with all data gathered in 2009 except for
education, which was gathered in 2008, and the percent urban, which was gathered in 2000.
Variables come from the U.S. Census Bureau Decennial Census, U.S. Census Bureau American
Community Survey (ACS), Bureau of Labor Statistics and Pet.Abuse.com.

Dependent Variable
The dependent variable, reported animals abused based on court documentation or
verifiable media reference, from here on identified as reported animals abused, comes from PetAbuse.Com and represents animal abuse cases verified by the organization for each state in the
year 2009. Pet-Abuse.Com was founded in 2001 as an animal protection agency dedicated to the
research and tracking of criminal animal abuse and houses the largest known global animal abuse
database. The website allows anyone to submit an animal abuse case; however, court or media
documentation must accompany the file for verification before the case is included in the
database. Cases are identified in one of four ways: alleged, not charged, convicted, and open.
The first three categories are self-explanatory; the forth identifies a case as ‘open’ if an animal
has been abused but the responsible party cannot be identified or legally charged. Cases of abuse
include: beating, bestiality, burning, choking/strangulation/suffocation, drowning, fighting,
hanging, hoarding, kicking/stomping, mutilation/torture, neglect/abandonment, poisoning,
shooting, stabbing, theft, throwing, unlawful trade/smuggling, unlawful hunting/trapping, and
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vehicular . The site documents not only “pet” abuse, but also wild and agriculture animal
violations, though the majority of cases involve domestic animals. All cases on the database
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include identifiable information such as case documentation, animal type, abuse classification
and geographic location.
All reported animal abuse cases from 2009 were reviewed and coded to verify usability.
A total of 56,001 animals were reported abused in 2009. Reporting mechanisms and laws against
animal cruelty vary by state and are typically isolated to ‘domestic’ animals. However, this
analysis recognizes all reported animals abused, including both domestic and non-domestic
species. Including all species not only reduces bias due to state law differences, but it is also
essential in understanding how the animal production industry’s domination or construction of
animals as commodities of production may spill into the surrounding communities. Abuse cases
in this study include violence against: dogs, cats, birds, chickens, cows, deer, goats, horses,
marine animals, opossums, farm animals, pigs, rabbits, raccoons, reptiles, rodents, sheep and
squirrels. This data source has demonstrated reliability and has been used in other scholarly
studies (Gerbasi 2004).
The number of reported animals abused per 100,000 people was calculated using state
population statistics from the U.S. Census Bureau for each of the 48 states included in the
dataset. This variable is treated as continuous and is log transformed to satisfy OLS regression
assumptions.

Independent Variable
The primary independent variable is employment in animal production (per 100K), which
operationalizes the strength of the animal production industry in each state. Establishments are
classified based on the North American Industry Classification System (NAICS). The animal

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production industry is a subsector of sector 11-agriculture, forestry, fishing and hunting. This
subsector includes:
…establishments, such as ranches, farms and feedlots, primarily engaged in raising
animals, producing animal products and fattening animals. Industries have been created
taking into account input factors such as suitable grazing or pasture land, specialized
buildings, type of equipment, and the amount and type of labor required. An
establishment is classified to a NAICS industry or a national level industry in this
subsector provided that fifty percent or more of the establishment's agricultural
production consists of the products of that industry, (Bureau of Labor Statistics).
Employment in animal production (per 100,000 workers) was determined by taking the
total number of individuals employed in the animal production industry in a state and dividing it
by the number of persons employed in all industries (measured in 100,000s). To adhere to OLS
assumptions and reduce skew, employment in animal production (per 100,000) is logtransformed.
In addition to the primary independent variable, I include a number of theoretically
grounded controls, including community violence indicators. There is a sizable literature on
community violence that dates to the 1940s. In 1994 the National Research Council panel on
Understanding and Preventing Violence reviewed this literature to identify the robust causal
indicators of community violence. Many of the established indicators are reminiscent of Shaw
and McKay’s (1942; 1969) seminal work on the community characteristics associated with
delinquency. Factors connected to higher rates of violence fall into three main categories:
economic indicators like income (Boney-McCoy and Finklerher 1995; Shaw and McKay 1942),
unemployment and poverty (Smith and Jarjowa 1988; Cantor & Land 1985; Shaw and McKay
1969); social disorganization and population stability indicators including residential mobility
(Shaw and McKay 1942; 1969) and population density (Smith and Jarjowa 1988); and individual
demographic characteristics like age, gender, marital status and education (Bensing and Shroeder

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1960). What is largely missing from this analysis are institutional characteristics like industry
employment. Although some work has looked at the correlation between slaughterhouses and
meat packing facilities and community violence (Broadway 2000, 2007; Broadway & Stull 2006;
Eisnitz 1997; Markus 2005; Schlosser 2005; Stull & Broadway 2004), in general there is a dearth
of literature assessing the correlation between industry and community violence.
I include indicators from the above categories in my models, but it must be noted that
these indicators have been identified based on human violence; there has been limited study of
the determinants of violence against animals. As was discussed above, Fitzgerald, Kalof and
Dietz (2009) identified the connection between slaughterhouses and human violence, supporting
the institutional transmission argument; what is now needed is an examination of the animal
production industry and its potential influence on violence against animals.
Following the literature on predictors of community violence I include poverty rate,
median household income, education, unemployment, population change, and urban residence3
as controls. Assuming that the factors associated with community violence have similar causal
relationships with animal abuse, I expect that as the poverty rate, unemployment rate, population
change and urban residents increase, so will reported animals abused.
The 2009 poverty rate for each state was obtained from the U.S. Census Bureau (ACS).
2009 unemployment statistics were gathered from the Bureau of Labor Statistics. This is a
percentage rate based on the population eligible for employment. Population change comes from
the U.S. Census Bureau and is the change in population from 2000-2009. Percent of urban
residents is a 2000 statistic from the U.S. Census Bureau Decennial Census. In line with Green
Criminology, which asserts that the full social system must be taken into account, I also include
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variables that measure the criminal consequences of animal abuse. Maximum fine and maximum
jail time for animal abuse in 2009 are thus included as predictive indicators in this analysis. I
expect a negative relationship between animals abused and the maximum fines and jail time for
animal abuse. Each state’s maximum penalties were gathered from Pet-Abuse.Com, which
provides a number of legal statistics related to animal abuse.
Because the dependent variable is continuous, and for ease of presentation, I use ordinary
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least square regression . Data was analyzed using Stata. A Dfbeta test for outliers and influential
cases showed eleven states that could be influencing the data. Based on these influence levels,
states were removed one by one to assess their influence on the statistical significance of the
variables; all models excluding cases were then compared to the full model. No significant
changes were observed by excluding cases; because of this and because the larger dataset
provides a more complete picture of the U.S., the full dataset was used.

Results
Table 1 presents descriptive statistics for the sample. All statistics represent variables
prior to transformation. For the sake of brevity, I discuss only the four variables that have a
direct barring on state-level relationships with animals, reported animals abused, animal
production employment, maximum fine and maximum jail time. The independent variable,
reported animals abused has a large range from .15 animals to 129.10 animals abused per
100,000 people. Nevada has the lowest rate of reported animals abused, while Texas has the
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%!Because the dependent variable, reported animals abused, could also be considered a count

variable- a random variable indicating the number of times that an event has occurred, a negative
binomial model was also considered. However the negative binomial’s assumption of the
independence of events could not be satisfied theoretically.!
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highest. The primary independent variable, animal production employment, varies greatly,
ranging from a low of 10.13 to a high of 1,437.08 individuals employed in animal production per
100,000 workers. As mentioned previously and in line with Green Criminology, criminal
consequences are included because they highlight differences in how states view the utility and
value of animals, placing a different monetary and penal value on their harm. These differences
are highlighted in the range of maximum fines for animal abuse among states, which vary from a
low of $1,000 in Arkansas, Mississippi, North Carolina, and South Dakota to a high of $500,000
in Colorado; similarly maximum jail time varies from a low of three months in North Carolina
and Mississippi to a high of ten years in Louisiana and Alabama.

TABLE 1. Descriptive Statistics for the Sample (n=48)
Variable
Mean

SD

Range

Animals abused (per 100K)

12.29

22.09

.15-129.10

Employment in AP (per 100K)

252.71

261.68

10.13-1,437.08

Poverty rate (%)

13.91

3.04

8.5-21.90

Unemployment (%)

8.23

2.27

.85-13.35

Pop density change 2000-09(per sq. mi.)

9.01

7.31

.31-37.27

Urban (%)

71.42

14.93

38.18-94.44

Education (BA %)

26.87

4.84

17.1-38.1

Median household income ($)

49,507.17

7,511.61

35,078-64,851

Maximum fine($)

24,604.17

75,074.64

1,000-500,000

Maximum jail time (months)

44.625

28.90

3-120

AP, animal production
All descriptive statistics represent variables prior to transformations necessary to meet OLS
assumptions
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Table 2 presents bivariate correlation coefficients and their significance levels. The
correlation between animal production employment and reported animal abuse is .4 and
demonstrates that there is a positive significant correlation between animal production
employment and reported animals abused. Figure 1 shows this general pattern, highlighting the
positive relationship between employment in animal production and animals abused.

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TABLE 2. Bivariate Correlations (n=48)
Variables
1
2

3

4

5

6

7

8

9

1. Animals abused

1.00

2. Employment in AP

0.40* 1.00

3. Poverty rate

0.31* 0.17

4. Unemployment

-0.14 -0.23 0.21

1.00

5. Population change

0.08

0.08

6. Urban

-0.05 -0.38* -0.34* 0.26

7. Med. house Inc

-0.26 -0.32* -0.88* -0.10 0.00

8. Education

-0.19 -0.27 -0.74* -0.16 -0.03 0.49* 0.83* 1.00

9. Maximum jail

-0.16 -0.32* -0.13 0.12

-0.21 -0.01 0.21

0.10

1.00

7. Maximum fine
*p<0.05

0.00

0.25

0.18

0.39

10

0.14

0.00

1.00

0.07

-0.13 0.12

1.00
0.30* 1.00
0.55

0.38* 0.22

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1.00

Figure 1: Animal Production Employment and Animal Abuse

Table 3 reports the results of the OLS regression, which confirms that the positive
relationship between reported animals abused and animal production employment is significant
when controlling for other theoretically driven explanatory factors. The first column of each
model provides the unstandardized coefficients and robust standard errors, which were used to
correct for multicolinearity. The second column provides the standardized coefficients, which
allow us to assess the impact of each independent variable relative to the other independent
variables.
Model 1 includes the primary independent variable, employment in animal production, as
well as the indicators previously indentified as predictive of community violence. Using

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standardized coefficients, employment in animal production is positive and significant, with an
increase of one logged animal production employee per 100,000 workers resulting in an increase
of .51 logged reported animals abused per 100,000 people. Counter to expectations, the only
economic variable that is significant is the poverty rate, with a 1% increase in the state poverty
rate accounting for a .594 increase in reported animals abused.
Previous literature identifies a correlation between violence and population dynamics
with less population stability being correlated to higher rates of violent crime. In line with these
past studies, states that have less stable populations are more likely to have more reports of
animals abused. Urban environments, where there are more interpersonal interactions, have
higher rates of violence between humans, but not necessarily between humans and other species.
To assess these dynamics, the percent of population change from 2000 to 2009 and the percent
urban were added to the model. An increase in the percent of a state’s population residing in
urban areas also has a positive relationship with animals abused. This is consistent with
expectations. State unemployment rates and change in population were not significant in this
model. Including community violence indicators, the model accounts for 26.7% of variance in
reported animals abused.
Model 2 builds on Model 1 by controlling for the maximum state fines and maximum jail
time for reported animal abuse. Although these additional predictors do not have significance in
the model, theory in Green Criminology suggests that legal ramifications should be taken into
account. Even with the additional predictors, animal production employment remains positive
and significant in Model 2. Because the two additional predictors are non-significant, the
adjusted R-squared shows that Model 2 explains 23.9% of the variance in reported animals
abused. This non-finding could have greater state ramifications given the links between violence

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against animals and human on human violence. This additional predictor should be investigated
further.
Model 3 includes regional variation in the model. All previous indicators are included. To
account for regional variation all regions have been compared to the reference category
(Midwest). This model indicates that there is no difference between the Midwest and other
regions. Model 3 explains 22.3% of variance in reported animals abused.

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TABLE 3. OLS Regressions Predicting (Log) State Reported Animal Abuse with Standardized ! and Robust Standard Errors (n=48)
Model 1
Variables
Employment in AP (log)
Poverty rate
Unemployment
Population change
Urban
Median Household Inc.
Education

b/rse
.610**
(.180)
.256*
(.153)
-.101
(.080)
-.039
(.032)
.039*
(.000)
.001
(.069)
.007
(.069)

Maximum fine (log)
Maximum jail time

!
.510**
.594*
-.176
-.220
.444*
.146
.024

Model 2
b/rse
.729**
(.213)
.252
(.163)
-.103
(.083)
-.035
(.037)
.045*
(.019)
.000
.000
.011
(.070)
-.118
(.164)
.004
(.008)

South
West
Northeast
Constant
-8.303
2
R
0.377
Adjusted R2
0.267
*p<0.05; **p<0.01; ***p<0.001.
Midwest is the reference category for region
!

-7.89
0.385
0.239

"#!

!
.556**
.583
-.179
-.197
.508*
.107
.040
-.113
.096

Model 3
b/rse
.681*
(.299)
.186
(.164)
-.088
(.075)
-.061
(.047)
.042*
(.018)
.000
(.000)
.041
(.075)
-.124
(.187)
.005
(.009)
.482
(.720)
.634
(.654)
-.560
(.837)
-6.340
0.421
0.223

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.519*
.430
-.152
-.338
.472*
-.018
.150
-.119
.112
.175
.212
-.118

Discussion and Conclusions
Past literature has begun to establish the link between animal abuse and human social
systems. This study builds on extent work by identifying the relationship between the strength of
the animal production industry and animal abuse at the state level. These results support the
hypothesis that employment in the animal production industry has a significant, positive
relationship on the number of reported animals abused in a state, so that as state employment in
the animal production industry increases, so too do the number of reported animals abused.
Indeed, this relationship seems to suggest that there are systemic determinants of animal abuse
and offers indirect support for the theories of communal moral dissonance and institutionalized
social distance, though it does not test them directly.
The test clearly identifies a pattern in reported animal abuse that varies according to the
strength of the animal production industry; however, it cannot explain why this relationship
exists. For this, we turn to our theoretical foundations, which suggest that institutionalized
attitudes towards animals can transfer into societal behavior. In this case, the institutionalized
norms about the treatment of animals and the commoditization of animal life required by the
animal production industry is likely to spill into state culture and communal attitudes towards
animals more broadly, resulting in higher levels of animal abuse. The adoption of these attitudes
would be facilitated by moral dissonance, which allows people to embrace behaviors they
otherwise believe to be morally devoid- in this case behaviors that are considered abuse towards
domestic animals but are acceptable for livestock- because they see the utility of the action.
Though this study is an important initial step in testing the relationship between animal
production strength and animal abuse, it has a number of limitations. One of the primary
limitations is that data is available only on reported cases that do not provide a full picture of

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animal abuse in a state. Reporting is influenced by three factors identified in past work on human
on human violence as points of caution: (1) sampling bias (2) reliability of reporting and (3) the
definition of abuse (Patterson-Kane & Piper 2009).
Like other forms of abuse, animal cruelty is grossly underreported, a problem that is
amplified by animals’ inability to self-report. In addition, because of the Animal Welfare Act’s
species exclusions discussed previously, cruelty against many types of animals is not considered
illegal and thus is not subject to reporting. Given the magnitude of this exclusion, the animal
abuse numbers presented by Pet-Abuse.Com are conservative at best. Further, those cases that
are reported may be biased in a variety of untestable ways. For example, severe cases may be
reported more frequently because they may be more likely to be noticed; similarly, there may be
cultural differences that encourage some communities to be more vigilant in their reporting of
animal abuse. This latter point brings up a possible alternative explanation for the findings in this
paper: states with increased animal production may actually be more aware of animal welfare
and thus report animal cruelty at higher rates, though the actual occurrence of animal abuse may
not differ from that of other states. Although this is a possible explanation, past research on
slaughterhouses and community violence and the work done around moral dissonance and
institutional distance suggest that this is an unlikely explanation.
In addition to the legal ambiguities discussed previously, reporting relies on definitions of
animal abuse that vary across states. This variation may create a reporting bias. For example,
Maine recently enacted humane farming legislation that will outlaw veal crates beginning this
year. Because of this legislation, the use of veal crates becomes a form of animal cruelty in
Maine, though it is an acceptable practice without cruelty connotations in the 45 states that have
not passed the legislation. Because of these challenges- sampling bias, reporting accuracy and

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the definition of abuse- I report my findings with some caution. However, these limitations are
inherent in this type of research, since the only way to study animal abuse is through reported
cases. I thus report my findings because they speak to an important social problem that has
largely been ignored by the scholarly community. The data limitations suggest the need for
further inquiry and more detailed studies of the prevalence of animal abuse.
In addition to the data limitations, this study speaks only to aggregate level trends, it
cannot identify what is happening at the individual level. For example, I cannot identify whether
there is a direct correlation between working in the animal production industry and engaging in
animal abuse, nor can I identify the individual level cognitive processing that may transfer
institutional norms into individual behavior. Finally, the study is limited by the state-level
analysis in that it cannot identify spatial trends associated with proximity to animal production
facilities.
What the study does is provide evidence that the strength of the animal production
industry is related to reported animal abuse and provides insight into how institutional animal
norms may be transferred to society at large. Further, it provides an indirect test of the theories of
moral dissonance and institutional distance. Future research should more thoroughly examine the
moral dissonance and institutional distance created in animal production, paying particular
attention to the institutional norms developed in the industry and how they inform communal
attitudes about animals. In addition, it should further examine the social drivers of animal abuse
over time, and test public familiarity with animal cruelty laws as well as examining the attitudes
associated with these laws.

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