Views Are Instilled Into Media Consumers

Home , Cultivation theory

JARED SCOTT ROSENBERGER

CRIME, MEDIA, AND THE AMERICAN DREAM: THE ROLE OF MEDIA

CONSUMPTION IN INSTITUTIONAL ANOMIE THEORY

A Dissertation

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Philosophy

Jared S. Rosenberger

May, 2013

CRIME, MEDIA, AND THE AMERICAN DREAM: THE ROLE OF MEDIA

CONSUMPTION IN INSTITUTIONAL ANOMIE THEORY

Jared Scott Rosenberger

Dissertation

Approved: Accepted:

______Advisor Department Chair Dr. Valerie J. Callanan Dr. Matthew T. Lee

______Committee Member Dean of the College Dr. Matthew T. Lee Dr. Chand Midha

______Committee Member Dean of the Graduate School Dr. Stacey Nofziger Dr. George R. Newkome

______Committee Member Date Dr. Richard Rosenfeld

______Committee Member Dr. Richard E. Adams

______Committee Member Dr. William T. Lyons Jr.

ABSTRACT

Messner and Rosenfeld’s Institutional Anomie Theory (IAT) is based on the assumption that the “American Dream” produces a society that is obsessed with the pursuit of success and dominated by the economy. Thus, crime is prevalent in the United States because individuals are willing to cut corners in order to attain the “dream” for themselves. This dissertation expands the work of Messner and Rosenfeld (1994), contending that the

“American Dream” is transmitted directly to citizens through the consumption of media representations, using over 6000 cases from the public use portion of the National

Longitudinal Study of Adolescent Health (ADD Health). A series of logistic regressions were conducted to determine the influence of television consumption on committing multiple forms of serious criminal behavior. As hypothesized, television consumption directly increases the odds of committing three types of serious criminal behavior

(economic based, violent, and general). In addition, the results suggest that compared to light television consumers, heavy consumers are less influenced by crime-curbing noneconomic institutions like education and the family.

iii

TABLE OF CONTENTS Page

LIST OF TABLES……………………………………………………………………….xv

LIST OF FIGURES……………………………………………………………………..xvi

CHAPTER

I. INTRODUCTION………………………………………………………………….…..1

II. INSTITUTIONAL ANOMIE THEORY…...... …………………………………...…..8

The Development of Institutional Anomie Theory…………….……………….....8

Empirical Tests of IAT……………………………………………………....…..15

The institutional dynamics of IAT……..…………………..……….……16

The cultural dynamics of IAT………...………………………….………21

IAT at the individual level.……………...………………………..…..….24

Critiques, limitation, and unanswered questions.…..…….….……..…....26

III. MEDIA, CRIME, AND THE “AMERICAN DREAM”………………….………...30

The Transmission of the “American Dream”……….……………………..….....30

Cultivation Theory.………………………………………………………32

Media representations and the “American Dream”..……………..…...…36

Contribution to IAT and hypotheses...…………………………….…...... 41

IV. DATA AND METHODS……………………………………………………….…..45

The National Longitudinal Study of Adolescent Health……………….……...... 45

Dependent variables………………………….………………….…...... 48

Independent variables..……………………………………..………...... 50

Institutional variables………………………………………...….…...... 51

Media variable…………………………….…………………….…....….53

Criminal predisposition………..……………………..…………....……..54

Control variables………..………………………….....…………...……..55

Analytical Plan………………………………………….…………..…………....55

Mediation and moderation…………………………………………….…58

Summary…………………………………………………..………...…...59

V. ANALSIS AND DISCUSSION………………………………………………..……61

Descriptive and Bivariate Results………………………………………………..61

Media Effects Models………………………………………………....…...…….67

Media effects models: discussion……………...…...…….……....…...…74

Moderating Effects Models……..………………………..………....….…….….81

Comparison of Coefficients Test..…………..………..………………….87

Moderating effects models: discussion.…….………...………………….88

Summary of Hypotheses…………………………..……………………………..93

VI. CONCLUSION………………………………………………...……………………96

Summary of Findings…………………………...………………………………..98

Media effects…………………………………………………...…..…….99

Moderating effects………..……...………………...………………...…100

Limitations……………..…………………………………..………...……....…102

Future Research……………….…………………..…………………………....105

Implications for the Field of Criminology…..…………….………...………….107

Summary……………………………………..…………………..………….….108

REFERENCES…………………………………………………………………………110

APPENDICES………..………………………………………………….…….……….118

APPENDIX A: DATA SOURCES…………..…………………..………….….119

APPENDIX B: MEASURMENT..…………..…………………..………….….120

APPENDIX C: MEASURMENT.. ……….....…………………..………….….121

APPENDIX D: MEASURMENT.. ……….....…………………..………….….122

LIST OF TABLES

Table Page

1 Descriptive Characteristics of the Sample…………………………………….………63

2 Pearson Correlations…………………………..………………..………….…….……66

3 Odds Ratios of the Influence of Television on Committing Crimes of Economic Attainment ……………………….……………..…..…….69

4 Odds Ratios of the Influence of Television on Committing Violent Crimes ………………………………..……………………….…..…….71

5 Odds Ratios of the Influence of Television on Committing General Criminal Behavior ……………………..…………………….…...…….73

6 Odds Ratios of the Influence of Institutional Factors on Committing Crimes of Economic Attainment by Levels of Television Consumption..…...….82

7 Odds Ratios of the Influence of Institutional Factors on Committing Crimes of Violence by Levels of Television Consumption.....…………….…….84

8 Odds Ratios of the Influence of Institutional Factors on Committing General Criminal Behavior by Levels of Television Consumption .……...….….86

9 Tests for Equality of the Influence of Institutional Factors on Criminal Behavior across High and Low Television Consumption ....……..……….…….87

vii

LIST OF FIGURES

Figure Page

1.1 Analytical Model of Social Organization and Crime in IAT……....……………….11

viii

CHAPTER I

INTRODUCTION

America incarcerates more of its populace than any other nation in the world.

Over 2.2 million citizens are currently behind bars, with an additional 1 in every 100 citizens under supervision by state, federal, and local correctional authorities (Bureau of

Justice Statistics 2010). While much of the high incarceration rate can be explained by the United States’ sentencing laws (Tonry 1999), rates of murder, rape, and other violent crimes are consistently amongst the highest when compared to other industrialized nations (Interpol 2007). In 2009, the United States had a murder rate of 5.1 per 100,000

(Federal Bureau of Investigation 2009), which was highest amongst comparable post- industrial nations, despite being the lowest in recent U.S. history (United Nations Office on Drugs and Crime 2011). The high rates of crime and violence even hold true when compared to countries with far less affluence than that of the United States, even in places with much political and social unrest. For example, in a survey of 73 countries with comparable crime data collected by the United Nations, the United States had the

10th highest mean robbery rate (United Nations Office on Drugs and Crime 2002). One would expect the world’s wealthiest nation, which has enjoyed long periods of political and economic stability, to have much lower levels of violent or property crime. It seems that there is something different about American culture, something that influences individuals to turn to serious and violent crime far more often than in other countries.

As one of the first attempts to address the question of why certain nations or societies have high rates of crime, Robert Merton (1938) used insights from Durkheim, coupled with observations about cultural goals, to formulate the anomie theory of crime.

Merton proposed that the cause of national-level differences in crime is the result of an imbalance between cultural goals and the institutional means for attaining them. He argued that societies become preoccupied with their culturally prescribed goals, while the institutionally acceptable means of attaining those goals hold little value. In America, cultural goals surround one primary mode of success: the pursuit of money. It is argued that the goal of economic attainment seems to trump all other measures of success

(Schoepfer and Piquero 2006) so that the goods associated with economic success have become the markers of happiness. The means to attain these goals seem to be of little concern, an idea that is highlighted by the high rates of corporate and property crime observed in the United States (Messner and Rosenfeld 2001). For Merton, the emphasis put on the goal of financial success in the United States leads to a separation from the norms and values associated with pursuing these goals. Thus, America is highly anomic as individuals find themselves in a state of normlessness.

To demonstrate how a culture can become preoccupied with cultural goals while being unconcerned with the institutionally appropriate means of attaining these goals,

Merton (1938) uses the example of sports. In competitive sports the goal of winning often outweighs the importance of how winning is achieved. There are multiple examples in the sporting world where coaches, players, and owners cut corners in order to win at their particular sport. Perhaps no example is more famous than that of Major

League Baseball’s Gaylord Perry; a successful baseball player who stopped halfway

2 through his 20 year baseball career to write a now infamous book: “Me and the Spitter.”

In his book, Mr. Perry describes the way in which he uses the illegal spitter pitch (which involves wetting your fingers with saliva or other slick substances) to produce more effective movement on his pitches. Put simply, Mr. Perry wrote a book about cheating in baseball before he had even finished his major league career. Gaylord Perry played another ten seasons after the release of his book before retiring and later he was elected into the National Baseball Hall of Fame. There are of course, many other contemporary examples in the world of sports where individuals are willing to cut corners in order to win.

In 1994 Messner and Rosenfeld applied anomie theory, giving it a renewed relevance, in their work Crime and the American Dream. For Messner and Rosenfeld

(1994), high rates of violent and property crime in the United States are caused by two interacting and equally important factors: cultural and institutional dynamics. American culture values economic attainment above all else and it socializes all its members to value “achievement orientation, individualism, universalism, and a peculiar form of materialism that has been described as the ‘fetishism of money’” (68). Moreover, the economy dominates other institutions like the family, the community, and education, which makes economic pursuit more important and economic pressures more apparent.

The pursuit of economic success is the most important cultural goal and the economic institution dominates all others. The result is a society obsessed with economic success

“by any means necessary,” or to go back to Merton’s sports analogy, “It’s not how you play the game; its whether you win or lose.” As Merton (1938) proposed, the means of attaining success begin to have little importance. In the quest to attain financial success,

3 individuals resort to the use of crime and violence in their pursuit of the “American

Dream.”

Messner and Rosenfeld (1994) assume that the “American Dream” is something that is built into the very foundation of society and is accepted and promoted by social institutions, groups, and individuals. While they caution not to oversimplify American culture, they believe the core values are socialized into members “with few exceptions.”

This poses an important question: How are these beliefs transmitted universally to members of society? Messner and Rosenfeld (2001:70) briefly mention that the consumption of media “play a pivotal role” in transmitting these values, especially in relationship to the “fetishism of money,” perhaps the key and underlying component of the “American Dream.” The extent to which the media influences these cultural goals, promotes the economy’s dominance, and inhibits institutions such as polity, family, education, and religion, has not been examined in IAT.

The possible influence that cultural values, such as materialism, have in promoting the economy’s dominance over other institutions warrants further investigation into how these values are transmitted to all members of American society.

American media is full of materialistic messages and representations that suggest success is the result of financial gain and the accumulation of possessions. Literature on media messages suggests that materialism, consumerism, and pro-capitalist ideals are all transmitted via media consumption (Churchill and Moschis 1979; Carlson 1993; Buijzen and Valkenburg 2003). This suggests that capitalism benefits a great deal from media messages. While the economy influences individuals, often times negatively, the values associated with capitalism and pro-capitalist views are instilled into media consumers.

These values, better known for encompassing the “American Dream,” are as Carlson

(1993:245) says “the engine that sustains the system.” Messner and Rosenfeld (1994) maintain that the power and influence of the economy in American society leads to its domination over all of the other institutions. If media representations are a source of socialization that transmit the “American Dream” to society’s members, than differences in the amount of certain media consumed may determine the extent to which the economy dominates the influence of noneconomic institutions in the lives of its viewers.

This dissertation research extends the work of Messner and Rosenfeld (1994) in a number of important ways. First, it explores the possible relationship between media consumption and the tenets of IAT. For a macro-level theory such as IAT to be successful they must be able to determine how all subcultures, groups, and individuals are exposed to similar messages about what constitutes success. I contend that this is done through the media, which acts as a major socializing agent in the transmission of values associated with the “American Dream.” If this is true, individuals who are exposed to high amounts of television (a medium that is saturated with materialistic depictions) should be less affected by noneconomic institutions and more likely to commit crime.

Second, this research is one of only a few to apply the components of IAT at the individual-level of analysis. While primarily a macro-level theory, IAT makes testable assumptions about processes that take place at the micro-level. Finally, the research offers further testing of the assumptions of IAT, a theory that has yet to be fully explored.

This dissertation is separated into five chapters, with the first consisting of the general introduction above. Chapter II discusses Messner and Rosenfeld’s (1994) IAT and reviews relevant literature that has empirically tested its assumptions. Since the

5 theory draws heavily from Merton (1938), I begin by reviewing anomie theory which provides the framework for IAT and ultimately my dissertation research. In this section, empirical tests are described in detail as they represent a limited body of work. Further, the institutional and cultural dynamics have usually been tested separately, primarily due to data limitations. Each one of these lines of research is outlined and described below.

Since this dissertation looks to test IAT at the micro-level, I also explore the limited empirical work that has attempted this type of application. Since micro-level applications of IAT are rare, I include a theoretical argument justifying my approach.

Chapter III reviews existing literature that suggests media representations transmit the values associated with the “American Dream.” In addition, this section addresses critiques of the theory identified through empirical testing and theorizes about the possible role the mass media may play in IAT. Finally, hypotheses testing the relationship between media consumption and the tenets of IAT are laid out.

Chapter IV provides an outline of the data and methods I use to test my hypotheses. By utilizing the National Longitudinal Study of Adolescent Health (ADD

Health) data set, I am able to test my hypotheses with cumulative data on crime and media consumption across adolescence and into adulthood, which allows me to control for prior delinquent behavior, and media consumption across the life of the study.

Detailed descriptions of the measurement and coding of variables, the sampling, and data collection are also included in this section.

Chapter V interprets the findings and discusses the results of the study. It is separated into three major sections, the first discussing the results of the tests assessing the possibility of a direct relationship between television consumption and criminal

6 behavior. The next section focuses on differences in the predictors of crime across high and low television consumers. Next, the implications of the results in testing my three major hypotheses are discussed. Chapter VI concludes the dissertation by situating the findings in the literature and arguing that the findings have implications for future studies of IAT and criminological research in general. Finally, limitations and direction for future research are discussed.

CHAPTER II

INSTITUTIONAL ANOMIE THEORY

The Development of Institutional Anomie Theory

In one of the most influential articles in the field of sociology, “Social Structure and Anomie,” Merton (1938) rejected popular biological explanations of crime and argued that two distinct yet related factors influence criminal offending: strain and anomie. Anomie and strain theory represent both a macro and a micro-level explanation of why certain societies, groups, and individuals may be driven to crime and deviance.

While the ideas from both theories can never be fully separated, strain theory was a dominant force in criminal research during the 1950s and the 1960s, largely tested separately from anomie theory (Cullen and Agnew 2006). Strain theory focuses on how the pressure to commit crime disproportionately affects certain individuals and groups.

Cultural goals are shared by everyone, but certain individuals and groups of individuals lack, or are disproportionally denied, access to the institutional means to attain them. The desire to attain success causes a tremendous amount of strain and stress in these individuals. In order to alleviate these pressures, individuals “adapt” to the strain in multiple ways, often resulting in an individual using deviant means to make up for their lack of legitimate ones.

Anomie theory focuses on macro-level causes of crime and asks why certain societies or nations have higher levels of crime, violence, and deviance than others. For

Merton, the cause of these macro-level differences is the result of an imbalance between cultural goals and institutional means for attaining the goals. Merton (1938:673) states,

“There may develop a disproportionate, at times, a virtually exclusive, stress upon the value of specific goals, involving relatively slight concern with the institutionally appropriate modes of attaining these goals.” He argued that when a society fails to place appropriate checks on goal seeking behavior it is said to be in a state of normlessness or anomie. An anomic society, much as an anomic individual, loses concern with the appropriate means to achieve cultural goals and is left fixated only on the attainment of the goal itself.

In 1994 Stephen Messner and Richard Rosenfeld (1994) published Crime and the

American Dream, representing a substantial advancement of Merton’s anomie theory.

They argue that crime is the result of the cultural and the institutional dynamics of

American society. Where the cultural dynamics represent values that are specific to

American society, the institutional dynamics describe the corruption of the balance of power between the institutions. They posit that in the United States, the dominance of one particular institution—the economy—over all of the other institutions creates an imbalance. The resulting “institutional structure diminishes the capacity of other institutions, such as the family, education, and the political system, to curb crime- fostering cultural pressures and to impose controls over and provide support for the members of society” (Messner and Rosenfeld 2001:xi). The result of the imbalance of power between the economy and the noneconomic institutions is both weak social controls and a lack of institution support (see Figure 1.1).

The prevailing force of the economy contributes to a culture that has a strong preference for values that translate into economic success. These values all play a role in the creation of the “American Dream,” and contribute to a mindset that involves happiness through the achievement of financial and material gain. To restate, Messner and Rosenfeld identify four specific values associated with the “American Dream:” achievement orientation, individualism, universalism, and the fetishism of money.

Achievement orientation refers to the cultural goal of making something out of yourself, essentially “pulling yourself up by your bootstraps,” to attain success through hard work and determination. Messner and Rosenfeld (2001) argue that the focus on achievement results in relatively slight concern for who someone is as a person, but rather on what they have achieved in life. In America, it is essential that your achievements are completed independently, and people who are perceived to have things handed to them are devalued. Individualism is thus necessary to truly attain success. However, the act of succeeding independently in the face of opposition means little in American society if it does not translate into monetary success. The fetishism of money refers to the cultural obsession with the accumulation of wealth. In American society, the amount of money that an individual has is the primary determinate of that of whether or not they are successful.

Figure 1.1: Messner and Rosenfeld’s (2010) Analytical Model of Social Organization and

Crime in IAT

Achievement Individualism ECONOMY POLITY Orientation

Universalism Pecuniary FAMILY SCHOOLS Materialism Weak Meager ANOMIE Institutional Institutional Controls Support

CRIME

It is as Merton (1968:190) states “Money is literally, in this context, a currency for measuring achievement.” The relationship between success and money is of vital importance to explaining crime, especially white-collar crime, because it implies that success is, as Messner and Rosenfeld (2001:70) state, “open-ended.” Even the already rich, powerful and successful in society are motivated and encouraged to pursue further monetary gain. While the strain from being blocked opportunities to success may be felt disproportionately by minorities and lower-class citizens, all segments of society feel the pressure to achieve and acquire more.

Finally, achievement attained independently through monetary gain would hold less value if it was only the measuring rod of success for some segments of our society.

Thus, universalism, or the idea that the same standards of success are applied to all members of society, is necessary for economic success to be the dominant goal in society.

In America, everyone is encouraged to pursue economic success and to move up the

11 stratification ladder. This contributes to a society where competition to succeed is great and there is tremendous pressure to reach the goals of financial and material success.

The cultural characteristics described above result in a high degree of anomie amongst U.S. citizens. Norms and values that once bonded societies together are replaced with the belief that success and happiness are best achieved through financial gains and the accumulation of material possessions. The cultural goal of economic success above all else, what Merton (1938) and Messner and Rosenfeld (1994) consider to be a determining mechanism of criminal behavior, is argued to not only be present in

American culture, but is considered by its citizens as perhaps the nation’s most important and noble ideal (Hochschild 1996). This ideal is better known as the “American Dream.”

The “American Dream” is not only accepted by members of society, but there is an assumption that every individual has an equal shot of attaining it. For Merton (1938) the lack of legitimate opportunities leads to criminal offending, but Messner and

Rosenfeld (1994) recognize that even individuals who lack these opportunities refrain from crime if other institutions have a strong influence. Naturally these institutions have a negative relationship with criminal offending, as they represent institutions that keep individuals bonded to the norms and values of society. However, the strength and acceptance of the “American Dream” and the dominance of the economy cause the other institutions to have a limited effect. They identify the institutions of the family, education, and polity as being particularly important in this relationship.

Messner and Rosenfeld (1994) see the relationship between individuals and noneconomic institutions as being perverted by the economy’s dominance over society.

Thus, individuals who adhere to the “American Dream” are driven by economic success

12 above all else, and noneconomic institutions that inhibit criminal offending are only important if they assist in economic attainment. In an anomic society such as the U.S., the family becomes an institution of economic support, education becomes a means to attain a higher paying job, and politics is a way to gain the power to regulate economic success. The result is a society of individuals attached to the goal of success but not to the legitimate institutional means to attain it. It is evident in this discription that Messner and Rosenfeld’s application of anomie varies from Durkhiem’s orginal conceptualization and the application of the term by Merton (1938). While Messner and Rosenfeld do argue that anomie is due to the lack of norms and values associated with noneconomic insitituions, it is also caused by a saturation of the norms and values associated with the economy. Thus, individuals may be highly bonded with the cultural dynamics of society and the economic institution, but their seperation from noneconomic insitutions, and the norms and values associated with the legitimate means to pursue success, that causes

America’s anomic state.

It seems that IAT is well equipped to explain the motivations in American society to pursue economic advancement “by any means necessary.” However, Messner and

Rosenfeld (1994) believe the same mechanisms that drive individuals to commit financially motivated crimes contribute to high rates of violence, fear of crime, and high levels of incarceration, all prevalent in American society. They state, “Although property and violent crimes might appear on the surface to be quite different, many violent street crimes are similar in an important respect to the “suite” crimes of high finance. They involve a willingness to innovate, that is, to use technically efficient but illegitimate means to solve conventional problems” (Messner and Rosenfeld 2001:3). This may

13 explain the prevalence of violence in the United States. Take the example of settling a disagreement; the use of violence is often easier, quicker, and more satisfying to an individual, but more importantly, it solves the problem. Perhaps legal action or the involvement of law enforcement agencies would also solve the problem, but they are much more difficult, expensive, and time consuming. Further, Messner and Rosenfeld

(2001) recognize that many violent disputes arise from economic problems, often involving illegal activities (drugs, prostitution) that make the appropriate means to settle the dispute (the police or community officials) unavailable. We should then expect that the “American Dream” contributes to the use of violence in addition to non-violent crimes of economic attainment.

Beyond the influence it has on motivating criminal behavior, Messner and

Rosenfeld (2001) argue the “American Dream” leads to other important and related societal characteristics. The first of which is a society with an increased level of fear of criminal activity. Increased levels of property and violent crime associated with

American culture contribute to an increase in fear of crime amongst the public. Fear of crime results in two important types of reactions among the public. First, “Fear of crime has been shown to reduce residents’ satisfaction with their neighborhood and to instill a desire to abandon the neighborhood for safer surroundings” (Messner and Rosenfeld

2001:5). Being dissatisfied with your neighborhood weakens any positive control the community may have on the individual that would prevent crime. Individuals who are not bonded to their communities may be willing to commit crime against neighbors in their pursuit of success.

Second, fear of crime leads to punitive attitudes amongst its citizens (Surette

1998; Dowler 2003; Callanan 2005). These attitudes translate into high levels of incarceration, which are higher in the United States than any other country in the world.

Despite this, crime and violence remain high demonstrating that correctional institutions and punitive sentencing laws fail to deter citizens from offending (Andrews and Bonta

2010). Recognizing the interconnectedness of high levels of crime, fear, and punitiveness, Messner and Rosenfeld (2001) ask whether or not something has “gone wrong” in the United States. Perhaps there has been a failure to implement the appropriate punishment or rehabilitative programs within the criminal justice system?

They think not. Instead IAT posits that the “American Dream” generates “distinctive forms and levels of crime that remain remarkably resistant to social reform and social control” (Messner and Rosenfeld 2001:5).

Empirical Tests of IAT

Since the theory’s creation numerous tests of IAT have been undertaken. Messner and Rosenfeld (1994) first presented a strictly theoretical explanation of criminal offending, so it was initially unclear how they intended tests of IAT to be modeled. As discussed above, the theory contains two important parts; the institutional dynamics and the cultural dynamics. The institutional dynamics of IAT focus on the effect of noneconomic institutions on the relationship between the economy and crime. There are questions as to how noneconomic institutions influence this relationship. However, it is clear that the values associated with economic success contradict those historically promoted by noneconomic institutions. As an example, religious institutions often

15 support altruistic behavior, which some suggest represents the opposite of the economy and the “American Dream” (Chamlin and Cochran 1997).

The institutional dynamics of IAT

The first empirical test of IAT comes from the work of Chamlin and Cochran

(1995); in fact, it was they who first coined Messner and Rosenfeld’s (1994) arguments as institutional anomie theory. Chamlin and Cochran (1995) identify the following basic hypothesis from the work of Messner and Rosenfeld (1994):

The effect of economic conditions on instrumental crime rates will depend on the vitality of noneconomic institutions. That is to say, we would expect an improvement in economic conditions to result in a reduction of instrumental crime only when there is a simultaneous strengthening of noneconomic institutions (415).

This suggests that crime is only reduced when there is both an improvement in both economic and noneconomic institutions (Messner and Rosenfeld 2010). Thus, Chamlin and Cochran (1995) test for a relationship between poverty rates and the vitality of noneconomic institutions, on property crime rates for all 50 states. The percentage of individuals living below the poverty line was their measure of economic deprivation.

Noneconomic institutions were measured with church membership, family structure, and voting percentage. The study concludes that the influence of living below the poverty line on property crime depends on the strength of all three noneconomic institutions.

Thus, if church membership, the strength of the family, and voting percentages are high, then the percentage of property crime in that area would be lowered. This study opened the gate for further empirical testing of IAT.

Messner and Rosenfeld (1997) tested the tenets of IAT, with particular focus on what is known as the “decommodification of labor,” which occurs when any institution,

16 including policies or laws from a given institution, help to weaken the impact the economy has on individuals (1394). They hypothesize that countries that decommodify the effects of the market by providing more welfare assistance to their citizens should see a decrease in homicide rates. Messner and Rosenfeld (1997) were the first to test the theory cross-nationally, which researchers seem to agree is most appropriate. Using a cross-national sample of 45 nations, they found support for the idea that decommodification is negatively related to homicide rates. In other words, policies that aim to reduce vulnerability to market forces seem to reduce criminal offending. The study introduces the idea of decommodification to the study of IAT, provides support for

IAT using a cross-national data set, and demonstrates the theory’s relevance to serious violent offending (homicide).

Drawing insight from both Chamlin and Cochran (1995) and Messner and

Rosenfeld’s (1997) initial tests of IAT’s institutional dynamics, Savolainen (2000) offers further support for the decommodification of labor. Using the same cross-national data set as Messner and Rosenfeld (1997), Savolainen (2000) attempts to combine what he sees as the strengths of Chamlin and Cochran (1995) and Messner and Rosenfeld (1997) into one empirical test of IAT. Using homicide rates as the outcome measure, Savolainen

(2000) found that the relationship between economic inequality and lethal violence is dependent upon the “strength of the welfare state” (1036) (measured with an index that includes national characteristics like health care, welfare, and political corporatism). He concludes that “the effect of economic inequality on lethal violence appears to be limited to nations characterized by low levels of decommodification and welfare spending”

(1036). This suggests that the fewer buffers to market forces a country provides to its citizens the higher the lethal violence that country should expect.

Similar to Messner and Rosenfeld’s (1997) approach, Hannon and Defronzo

(1998) used the components of IAT on a sample of metropolitan counties to determine if welfare assistance reduces the influence of resource deprivation on crime. While still a macro-level application of IAT, the study looks for variation within the United States in line with Chamlin and Cochran’s (1995) original test of IAT. The results supported this idea, which led them to conclude that lowering economic distress is an effective way to lower rates of both property and violent crime. This supports Messner and Rosenfeld’s

(1994) IAT as it suggests “welfare frees people from total reliance on market forces, thus limiting anomie and enhancing the social control functions on noneconomic institutions”

(389). The research suggests that if a society can reduce economic burdens on its citizens, then institutions identified by IAT that reduce crime and bond individuals to society’s norms and values (i.e. polity, education, religion, the family) can have a greater influence on lowering crime rates.

Pratt and Godsey (2002) expanded the research by testing whether or not social support affects the relationship between inequality and homicide rates. Using a 46 nation sample, social support is measured with an index of multiple variables including the proportion of a nations GDP spent on health care and education (Pratt and Godsey

2002:592). In this way, their measure of social support represents a more robust measure of decommodification, as providing healthcare and education should buffer citizens from the individual economic hardship related to these expenditures. They conclude that their measure of social support does indeed have an inverse relationship with homicide rates.

In addition, social support was found to interact with economic inequality which further increased homicide rates. This suggests that areas with low social support and high economic inequality should expect increased homicide rates. These findings were consistent with Messner and Rosenfeld’s (1997) study and the assumption of IAT that investment into institutions or programs that may reduce economic burden decreases violent crime cross-nationally. Pratt and Godsey (2003) conducted a follow up study on these assumptions which further supported their original ideas, finding the social support reduces the effect of the economy on rates of homicide.

Maume and Lee (2003) offer further testing of whether or not noneconomic institutions buffer or “decomodify” the effect of the economy on crime. Using homicide reports from U.S. counties with populations over 100,000, Maume and Lee (2003) attempted to test IAT on both expressive and instrumental homicide. They suggest that the relationship between noneconomic institutions and the homicide rate is both direct and indirect (mediating the relationship between the economy and homicide). They found that noneconomic institutions mediate the relationship between the economy and both expressive and instrumental homicide. This suggests that when noneconomic institutions are strong the effects of the economy are reduced.

Further comparing groups within the U.S. using IAT, Stucky (2003) was interested in determining if local political structures influence crime rates. The data included information on the political structure of over 950 U.S. cities. There were three major types of local government identified; Mayor/council governments where the heads of government are elected, council/city manager governments where the head of the government is an appointed professional, and commission governments where a group of

19 elected officials collectively govern an area. He found that in areas that have a

Mayor/Council form of elected government, crime was reduced. Specifically relevant to the IAT, Stucky (2003) found that “the effects of structural indicators on deprivation, such as poverty and family disruption, on violent crime were lower in cities with mayor- council forms of government and as the number of traditional local structures increased”

(1123). This suggests that when citizens have an active hand in electing government leaders, they may be more bonded to the political institution in their community and thus less likely to commit crime.

One of the difficulties with empirically testing the institutional dynamics of IAT is that the relationship between the economy, noneconomic institutions, and crime is unclear. Originally Chamblin and Cochran (1995) believed that IAT suggests a moderating relationship between noneconomic institutions and the relationship between the economy and crime. Other researchers followed their approach, and subsequently the vast majority of support for IAT comes from the “moderating effects” model (Chamlin and Cochran 1995; Hannon and DeFronzo 1998; Piquero and Piquero 1998; Savolainen

2000; Pratt and Godsey 2003; Stucky 2003). However, multiple studies have suggested that the relationship between the economy and crime is mediated by noneconomic institutions (Maume and Lee 2003; Bjerregaard and Cochran 2008).

For example, Bjerregaard and Cochran (2008) used a cross-national data set of 49 nations to determine if noneconomic institutions mediated or moderated the relationship between the economy and crime. Noneconomic institutions included the family, education, and polity, while the economy was measured by economic freedom, social security expenditures, and household income. The results showed some support for IAT.

IAT seemed to explain homicide rates more than it did theft, which were both included as dependent variables. This was contingent on the measure of the economy used and on the strength of noneconomic institutions. They concluded that the relationship between noneconomic institutions and the effects of the economy on crime remains unclear and that further testing and clarification of the measurement of key variables in IAT is needed to draw any definitive conclusions.

In sum, existing research has found support for the theory. Moreover, it suggests that noneconomic institutions affect the relationship between the economy and crime in multiple ways; mediation and moderation. It is likely that the relationship both mediates and moderates. What is more important is that the existing literature testing the institutional dynamics of IAT largely supports the tenets put forward by Messner and

Rosenfeld. The vast majority of empirical tests of IAT do support the theory. While tests of the institutional dynamics are important, they represent only one part of Messner and

Rosenfeld’s theory. The relationship between the institutional dynamics and crime cannot be fully tested or understood without addressing the role of culture in promoting criminal behavior.

The cultural dynamics of IAT

The literature reviewed above tests the institutional dynamics of IAT. These studies were concerned with how the strength or weakness of the relationship between the economy and crime is contingent on noneconomic institutions. However, Messner and Rosenfeld believe that crime is the result of both culture and the institutional structure (see Figure 1). Nevertheless, empirical tests of the cultural values identified by

IAT are less common. It is likely that “this reflects the difficulties in obtaining valid and

21 reliable measures of cultural orientations for quantitative analysis” (Messner and

Rosenfeld 2010:134). However, a few studies have tested the cultural dynamics of IAT.

Chamlin and Cochran (1997) were the first to test the cultural dynamics of IAT, just as they were the first to test the institutional dynamics of the theory. They argued that if the components of IAT were correct, and the “American Dream” leads to individualistic pursuits of economic gain causing an anomic crime-inducing state, then it is reasonable to assume that groups with a high degree of charitable donations (altruism) would be less anomic. Using a sample of over 400 U.S. cities, Chamlin and Cochran

(1997) found that cities exhibiting altruism have lower rates of both violent and property crime. They conclude, “that these findings are not simply an artifact of the research design, they strongly suggest that communities that effectively teach their members to respect and engage in behaviors that promote the welfare of others enjoy relatively lower rates of crime” (220).

Baumer and Gustafson (2007) offer perhaps the most complete test of the cultural dynamics of IAT. Using data from multiple sources that include the Uniform Crime

Reports (UCR), the General Social Survey (GSS), and the Census Bureau, they gathered information relevant to IAT on 77 of the 87 geographical sampling areas across the

United States included in the GSS. Their goal was to determine if instrumental crime rates are higher in geographical areas that have a strong commitment to monetary success and a weak commitment to the legitimate means of success. The degree to which individuals are committed to material success comes from a General Social Survey question asking respondents if they agree with the following questions; “next to health, money is the most important thing.” Also from the GSS, Baumer and Gustafson (2007)

22 use the statement “there are no right or wrong ways to make money, only hard and easy ways” to determine individual’s attachment to legitimate means of success. The results support IAT as they found that the influence of the cultural dynamics on crime is greater in areas where education (measured with an index of 6 items related to poor educational quality) and economic attainment are low. Further, in areas with high attachment to monetary success and low attachment to legitimate means of attainment, crime is reduced when high levels of welfare assistance are present. The findings not only support the idea of Messner and Rosenfeld (2001), that institutional vitality inhibits the effects of anomic culture, but they are in line with studies looking at the institutional dynamics of IAT that suggest reducing citizens’ vulnerability to economic harms reduce crime (Messner and

Rosenfeld 1997; Savolainen 2000).

Not all tests of the cultural dynamics of IAT have been supportive. Cullen,

Parboteeah, and Hoegl (2004) tested if adherence to the cultural goals of achievement, individualism, universalism, and materialism led to criminal behavior. Using data on 43 nations collected by the World Values Survey (2000), they used the outcome variable of business manager’s willingness to justify ethically suspect behavior, like cheating on your taxes, taking bribes, and claiming benefits that you did not earn. They hypothesized that the stronger each cultural goal described by IAT (achievement oriented, individualism, universalism, materialism) was in a given nation, the more likely managers would be to justify unethical behavior. Cullen et al. (2004) utilized hierarchical linear modeling which allowed them to provide the first multi-level test of the tenets of IAT. Their results support 5 of their 8 hypotheses that are in line with the theory, including that the cultural values of universalism and materialism lead to the

23 justification of ethically suspect behavior. However, business managers in nations with high degrees of individualism and achievement orientation were less likely to support unethical behavior. Cullen et al. (2004) argue that this may be due to the fact that managers do not often face blocked opportunities to legitimate means of attaining economic success. This supports Merton’s (1938) original anomie theory, as he argued that individualism and achievement orientation only lead to deviance when legitimate means are blocked.

IAT at the individual level

There is a limited body of research attempting to apply IAT at the micro-level.

Applications of IAT at the individual level are not common, and only one study has attempted micro-level applications of the theory. These have supported the notion that

IAT can be applied at the micro-level. In addition, Messner, Thome, and Rosenfeld

(2008) argue that not only is IAT applicable at the micro-level, but it should be encouraged. The following section reviews the existing literature testing IAT at the micro-level.

In an extensive and innovative test of IAT, Muftic (2006) tested both the institutional and cultural components on cheating in college at the micro-level. The survey of 122 U.S. born and 48 international students includes data on cheating habits, adherence to cultural goals, and the influence of institutions like the family, polity, education, and employment. Adherence to the cultural goals described by the “American

Dream” was measured using scale variables that captured achievement, individualism, universalism, and the fetishism of money. The study found partial support for IAT applied to individual-level cheating. Using the foreign born students as the comparison

24 group, Muftic (2006) finds that U.S. born students “have an increased adherence to economic goal orientations that increase cheating behaviors” (630). Those students who adhered to the values of universalism and the fetishism of money, were more likely to cheat. In addition, “students who were more committed to their families or more involved in the polity had a lower likelihood of cheating” (Muftic 2006:648). The study represents one of the few studies of IAT at the micro-level, and the results appear to indicate the theory partially explains individuals’ behaviors.

Messner et al. (2008) offer their recommendations as to where micro-level tests of

IAT should go into the future. While they “encourage further efforts” of micro-level IAT testing, they recommend expanding the types of deviance being explained in previous micro-level tests. Since IAT assumes “insensitivity to the moral status of the means is likely to be a generalized phenomenon,” (Messner et al. 2008:177) we can extend micro- level explanations to serious criminal behavior. Further, there are a few necessary requirements to consider in designing and interpreting studies within the framework of

IAT. Perhaps the most important factor to remember in applying IAT at the individual level is that “individual attributes and repertoires that lead toward or away from criminal behavior arise and, in turn, reinforce the defining cultural and structural features of the whole society” (Messner et al. 2008:178). Unlike its close theoretical relative, general strain theory, “IAT should not be interpreted as signs or symptoms of abnormality, pathology, or other individual deficiencies or defects” (Messner et al. 2008:178). We must then be careful to recognize the structural implications of micro-level tests of IAT.

While it is important to remember that IAT assumes that crime is the result of macro-level characteristics, the effect of these characteristics is felt on the individual

25 level. Simply argued, institutions and cultures do not commit crimes, people do.

Individual tests of IAT must be interpreted in the context of macro-level processes.

Previous studies on the micro-level have been promising; however, these have focused on lesser forms of offending. Messner et al. (2008) suggest that researchers expand applications of IAT to serious forms of criminal behavior.

Critiques, limitations, and unanswered questions

Whether testing the institutional or cultural dynamics of IAT, studies have raised concerns about the assumptions set forth by this relatively new theory. The following section highlights a few studies that have failed to find support for IAT and some of the limitations of the theory. Further, one study in particular (Jensen 2002) identifies two unanswered questions related to the theory, one of which represents the focus of this research.

In a study that resulted in mixed support for the theory, Batton and Jensen (2002) took a unique approach to testing IAT, using time-series data to examine the role of decommodification on homicide rates in cities across the United States. While Batton and Jensen (2002) found support for decommodification in the early half of the time- series data (before the end of WWII), they found no relationship between changes in the level of decommodification and homicide after WWII. However, it may be that the inconsistent findings are due to measurement issues with decommodification, which only includes expenditures on welfare. Further, previous tests of decommodification have looked at differences between nations, while this analysis examined time-series variation within the United States. Changes that occur in the rate of decommodification from year to year within a country are likely more subtle, and thus less noticeable statistically.

Jensen (2002) offers some of the strongest challenges and critiques of IAT. He takes issue with the fact that Messner and Rosenfeld offer no empirical support for the goals and values that are said to contribute to criminal offending. Further, Jensen (2002) offers what may be the most relevant critique of IAT: “How can the institutions that are supposed to be undermined by economic dominance do such a thorough job of socializing people into the hierarchy of values that undermine them?” (Jensen 2002:56).

There seems to be a fundamental flaw in the logic of IAT. That is if noneconomic institutions are dominated by the economy, than how can they actually buffer the link between the market and criminal offending? This is a paradox that needs to be addressed.

The contradiction above represents a specific challenge to IAT that Messner and

Rosenfeld do not directly discuss. However, I posit that their research addresses and solves this problem, albeit indirectly. Messner and Rosenfeld (1997) first test their assumptions by looking at factors that decommodify, or empower “the citizenry against the forces of the market” (1394). They find support for the idea that if a country decommodifies the market by investing in a welfare program, it reduces crime rates. This relationship implies that reducing the dominance of the economy over noneconomic institutions will result in a reduction of crime. So for countries and individuals who adhere to norms of economic success, only when the dominance of the economy is reduced can the noneconomic institutions be free to buffer crime. When the impact of the economy is not weakened it dominates noneconomic institutions, which fail to positively impact citizens by reducing the motivations and need to commit crime. In short, the economy seems to dominate noneconomic institutions in the sense that its influence

27 trumps the influence of the other institutions. If a country can dilute the strength of this influence, noneconomic institutions will reduce crime.

Related to Jensen’s (2002) critique of IAT there is another question that must be addressed: How do individuals and societies come to universally attain the values of achievement, individualism, universalism, and the fetishism of money? IAT argues that societies that hold these values are more likely to be anomic which may lead to criminal offending. However, in Messner and Rosenfeld’s (1994) description of IAT they offer no empirical support for this claim, and as reviewed above, tests of the cultural dynamic of

IAT have been few. Researchers should continue to test the cultural dynamics of IAT, as research conducted thus far appears mixed. However, there are related lines of research attempting to determine the prevalence and the impact of the “American Dream” on society.

The very notion of the “American Dream” is vastly supported by the American public (Hochschild 1996). For example, Hochschild and Scovronick’s (2004) research on the “American Dream” and public schools demonstrates that while most Americans believe in the dream and believe it is attainable by all members of society, few resources are invested in institutions (like education) that can make this reality. The public believes the “American Dream” represents the idea that all individuals can attain success, which refers to financial success and the accumulation of possessions, through hard work and resolve. However, the public ignores, or is unaware of the fact, that opportunities for success are blocked for various groups, including racial minorities, the poor, and women, amongst others. This reinforces the idea that we live in an anomic society just as Merton and Messner and Rosenfeld suggest. If American’s were equally concerned with the

28 goals and the means of attaining them, it stands to reason that there would be a greater emphasis on equal competition.

The popularity and the acceptance of the “American Dream” supports the claim that we live in a society dominated by its ideals. However, this does not fully address the critique related to Jensen (2002), as it is hard to imagine a way in which the values associated with the dream could spread to all individuals, groups, and subcultures without some common institution transcending the boundaries that separate American citizens. I argue that such an institution not only exists, but it pervades the lives of individuals, sending identical messages to all within its reach. Within these messages are lessens about what makes life exciting, what makes an individual successful, and what an individual needs to be happy. These messages are accepted by viewers as news, information, and more importantly as reflections of reality. Thus, it could be argued that one cannot talk about American values without discussing the role and the power of this institution, the institution of media.

CHAPTER III

CRIME, MEDIA, AND THE “AMERICAN DREAM”

IAT asserts that the “American Dream” is something that is built into the very foundation of society, accepted and promoted by social institutions, groups, and individuals. Messner and Rosenfeld (2001) suggest that the “American Dream” represents the core values of our culture, which includes “its achievement orientation, individualism, universalism, and peculiar form of materialism that has been described as the ‘fetishism of money’” (68). They suggest that these core beliefs are socialized into members “with few exceptions.” This poses an important question that remains largely unanswered by the theory: How are these beliefs transmitted universally to members of society?

The Transmission of the “American Dream”

Sociological studies of culture and subcultures make clear that no two groups are culturally identical. They are influenced by their physical surroundings, racial and ethnic makeup, spiritual beliefs, and a number of other important factors. Some subcultural theorists take the position that sociological inquiry can only truly be conducted at the subcultural level (Gordon 1947 is one of the first to argue this point in relationship to

American criminologists). Just as the data and conclusions of a study of one subculture are not generalizable to a larger group, studies of nations are not generalizable to subcultures within that nation. The problem, argue these scholars, is that subcultural

30 values, beliefs, and behaviors are often times affected very little by outside groups. This line of thinking challenges the assumptions of Messner and Rosenfeld (1994), as it could argue the “American Dream” may not be as universally accepted as the theory posits. In order to overcome this challenge, there must be an institution or some agent of socialization that is able to circumvent subcultural differences and instill the “American

Dream” in all members of society. I argue that this institution does indeed exist, and no matter the physical isolation, or the cultural differences, its influence is felt by everyone.

This institution is the mass media.

Messner and Rosenfeld (2001:70) briefly mention that the consumption of media

“play a pivotal role” in transmitting these values, especially in relationship to the

“fetishism of money,” perhaps the key and underlying component of the “American

Dream.” However, the extent of the relationship between media and the “American

Dream” has yet to be elaborated or tested. Messner and Rosenfeld (2001) do not elaborate on the media’s role beyond helping to transmit the cultural goals of the

“American Dream.” While literature supports the idea that media representations are an important part of transmitting certain goals (materialism and individualism), the impact may be far more significant. It may be that the media not only transmits the values of the

“American Dream” to viewers, but also reduces the crime-buffering effects of noneconomic institutions, thus, directly influencing criminal offending. While tests of

IAT have not yet explored the affects of media consumption on the theory, existing literature offers insights on how the two may be related.

Cultivation Theory

There is an extensive literature that attempts to deconstruct media messages and measure their perceived impact. Perhaps the largest focus of research on the effects of media consumption is cultivation theory, which is defined as the study of the effects of television consumption on viewer’s perception of reality. Shanahan and Morgan (1999) offer perhaps the most simple hypothesis of cultivation research stating, “those who spend more time watching television are more likely to perceive the real world in ways that reflect the most common and recurrent messages of the television world” (4). To be clear, cultivation analysis is not concerned with how individual representations in the media influence a person’s attitudes or beliefs. Instead, cultivation analysis focuses on how repetitive patterns in television shape our views of reality (Shanahan and Morgan

1999).

In an early attempt to determine the influence of consuming heavy amounts of television, in the late 1970’s and early 1980’s George Gerbner and his associates began the “Cultural Indicators Project.” This research utilized what Gerbner (1973) referred to as a “three-pronged” research strategy to determine the effects of television consumption.

First, they determined how policies were designed to control the flow of media messages

(Gerbner 1998). The second phase of the research strategy involved determining the patterns and trends that were most common in media messages. Finally, the third prong was meant to determine if the perception of reality among heavy television consumers were more likely to reflect the messages being sent by media representations than actual reality.

Gerbner and his associates first used content analysis to try and determine what types of overarching messages are sent via television representations. Using the findings from this portion of the study, they were able to determine what messages were being sent. The idea that television messages send overarching messages to viewers is a controversial one (see Hughes 1980). Gerbner (1998) recognized that there may be differences in television messages based on the program, channel, or an individual’s preference for certain types of television. However, he believes that it “is only repetitive, long-range, and consistent exposure to patterns common to most programming, such as casting, social typing, and the “fate” of different social types, that can be expected to cultivate stable and widely-shared images of life and society” (Gerbner 1998: 181).

Although cultivation theory broadly investigates the influence of media representations, much of Gerbner’s research focused on violent behavior. Gerbner and

Gross (1976) hypothesized that the television world contains vast amounts of violence and provides viewers with an inaccurate perception of how much violence takes place in the real world. They coined this idea the cultivation hypothesis. Results from the

“Cultural Indicators” project show support for the cultivation hypothesis and offer other insights on the effects of television consumption. Specifically, Gerbner and his associates (1977, 1978) find that individuals who consume higher amounts of television are more likely to fear crime and believe it is much more prevalent than it is in the real world (Gerbner et al. 1977). Further, Gerbner and Gross (1976) suggest that heavy television consumers are less likely to trust people. They described the belief system that develops in heavy consumers as the “mean-world view.”

Further research conducted by Gerbner et al. (1980) found support for two important processes related to media consumption: resonance and mainstreaming.

Resonance is the idea that individuals may be more likely to accept television representations if they can relate to the depiction (Gerbner et al. 1980). For example, a depiction of a violent assault against a young Caucasian woman may have a greater impact on a viewer who has had a similar experience or belongs to the same demographic group. Thus, Gerbner et al.’s (1980) research suggests that certain depictions may have a varying degree of impact on viewers depending if the depictions resonated with the consumer.

The concept of mainstreaming suggests that television representations work in line with the mainstream values and beliefs of a given culture (Gerbner 1986). Thus, mainstreaming is a process that involves the erosion of sub-cultural or group differences through media consumption. The mainstream messages of the media serve a few purposes in modern society according to Gerbner et al. (1986). Stories in the media

(whether print, television, radio, internet, or film) serve as a mechanism that unites publics that come from tremendously diverse cultural, racial, educational, and financial backgrounds. Media messages provide all Americans with what Gerbner refers to as “a packet of common consciousness—wherever they go” (Gerbner et al. 1986:22). This allows diverse groups of individuals to live and work together with “some degree of cooperation” (22). The dominant theme of these messages is the reinforcement of the structure that dominates the country.

As technology has evolved so has the number of different types of media outlets that pervade our lives. Some may argue that since news and entertainment has been

34 expanded to various media formats that the messages may be very different. However, the process of mainstreaming suggests that even these alternative media formats are oriented to the widest possible audience. Further, it has been argued that while numerous media formats exist, the same messages are being repackaged to fit a different medium.

This is a process referred to in media research as “looping” (Surette 2001). As Gerbner

(1998) suggests, mainstreaming represents “a relatively homogenization, an absorption of divergent views, and an apparent convergence of disparate outlooks on the overarching patterns of the television world’ (183). Certainly individuals can seek out alternative viewpoints, and representations that diverge from the mainstream, but these are singular and short-lived experiences for the consumer. Cultivation analysis suggests that the pervasive and overriding messages sent through the media are the ones that will ultimately influence a consumer’s view of the social world.

The cultivation hypothesis and the work of Gerbner have not been accepted by the academic community without challenges. For example, Hughes (1980) critiqued the approach of Gerbner and his colleagues, arguing that the relationship between television consumption and “mainstream” could be explained by some third party variable. Further, replications of Gerbner’s research indicated that the relationship between television consumption and the cultivation of mainstream values is much more complicated than presented (Heath and Gilbert 1996). However, modern tests of the relationship between media consumption and the cultivation of beliefs, while controlling for a range of demographic and experiential factors, do exist. For example, research suggests media consumption influences fear of crime (Madriz 1997; Chiricos, Padgett, and Gertz 2000;

Romer, Jamieson, and Aday 2003), public opinion of the police (Eschholz et al. 2002;

Dowler and Zawilski 2007; Callanan and Rosenberger 2011), and views about criminal sentencing (Roberts and Doob 1990; Dowler 2003; Callanan 2005). It seems likely that media representations also shape the values and beliefs discussed by Messner and

Rosenfeld. Especially considering the vast amount of media that focuses on the primary tenet of the “American Dream;” money.

Media representations and the “American Dream”

American media is not only flooded with depictions of violence, but it saturated with materialistic images. According to a report by the Nielsen Company (2013), the average media consumer watches nearly 145 hours of television per month. It is estimated that roughly 30 percent of this is comprised of commercials. That equates to about an hour and forty minutes per day that the average American consumes materialistic depictions. This has steadily increased over the years, and in 2011 television commercial expenditures grew 2.5 percent to reach over 68 billion dollars

(Television Bureau of Advertising 2012). Further, Americans also consume an average of more than 60 hours of alternative media forms through the internet, DVDs, and mobile devices. Advertising agencies use all media forms to promote goods and services. It is likely that this incredible amount of consumption has an effect on viewers.

Materialism is depicted not only in commercial advertising, but it is itself a staple of American media. For example, reality television shows depicting the lives of

America’s rich have been and continue to be some of the most popular programs currently on television. Americans’ fascination with materialism can be traced back to programs like Lifestyles of the Rich and Famous (1984-1995). Every week the program would show viewers how the wealthiest individuals in American society carry out their

36 daily lives and spend their money. There are currently numerous shows following a similar premise; popular programming like Keeping Up With the Kardashians, My Super

Sweet 16, Shahs of Sunset, and the Real Housewives Series follow the lives of wealthy individuals. The Real Housewives franchise has been so successful that there have been six versions of the show and other spin-offs. In 2004 Wealth TV was launched, representing the first cable network devoted solely to the lives of the economically elite.

The current programming lineup includes shows like Addicted to Money, Planet Luxury, and Private Islands. The popularity of these types of programs suggest that television consumers are obsessed with materialistic lifestyles. Further, they offer viewers the opportunity to live vicariously through the lives of the upper-class citizens that are depicted (Meloy 2009). This no doubt sends the message that the “American Dream” is alive and well, while simultaneously making a viewer’s current social class and relative deprivation more apparent.

Other popular media topics may also contribute to the “American Dream.” For example, sporting events often draw the largest number of viewers and account for a significant period of nearly every news program. Merton (1938) first pointed out that the popularity of sports and the goal of winning above all else are a reflection of our anomic culture. Sporting events and recent issues of cheating like the admission of steroid use by

Lance Armstrong, reinforce and support the idea that cutting corners can often lead to success. Further, sports and materialism are highly interconnected. Companies spend more money on advertising during the Super Bowl (four million dollars for a 30 second ad) than for any other event in America, sporting or otherwise (Forbes 2013). In

37 addition, athletes make incredibly high salaries and are often the focus on “reality” television programs documenting their extravagant lifestyles.

There is little doubt that materialistic messages are present in American media.

Socializing viewers to value material possessions is an essential part of IAT. If these materialistic views are established in young viewers, they are likely maintained as youth enter the prime age of criminal offending in their late teens and into their early 20’s.

Studies have been conducted to determine if values, like materialism, are cultivated through media consumption (Churchill and Moschis’s 1979; Buijzen and Valkenburg

2003; Shrum et al. 2011). One of the earliest studies in this vein, found a significant relationship between television consumption and levels of materialism among adolescents (Churchill and Moschis’s 1979). Since then, multiple attempts have been made to determine if media consumption cultivates materialism.

Using a parent-child survey that included over 350 dyads for example, Buijzen and Valkenburg (2003) tested the hypothesis that television consumption cultivates materialistic views in young children, and concluded that television consumption has a number of effects. These include a direct positive relationship between exposure to television advertisements and materialism, and an indirect positive relationship between advertisement consumption and parent-child conflict. The results of the study suggested that materialism as a result of exposure to advertising is established in early to middle childhood, and throughout adolescents.

Conducting a classic laboratory study, Shrum et al. (2011) exposed 142 undergraduate students to different media representations; one classified as highly materialistic (Wall Street) and the other as having few materialistic depictions at all

(Gorillas of the Mist). They found that those who watched Wall Street were more likely to hold materialistic views in the post-study survey. The results suggest that fictional depictions do cultivate materialistic views in consumers. In addition to this laboratory study, Shrum et al. (2011) also conducted a nationally representative survey of 1,500 individuals across the United States that collected detailed information on materialistic views, television consumption, and life satisfaction. The results suggested a positive relationship between television viewing and holding materialistic views.

Materialism is a vital part of the Messner and Rosenfeld’s “American Dream;” however, literature has linked media consumption to other values related to the

“American Dream.” For example, Carlson (1993) examined whether or not television viewing contributed to incorrect perceptions about the amount of affluence in the United

States and the support for the values of capitalism. Using a survey of over 340 registered voters in Providence, RI, capitalist values were measured based on the scale created by

McClosky and Zaller (1984) that provides respondents with seven questions. They include questions on effort, the fairness of capitalism, why individuals are poor, and what a person’s wage should be based upon. Each question includes two responses: one that is considered supportive of capitalist values, and one that is not. The results suggested heavy television consumption is associated with individualistic attitudes, support for capitalist values, and the belief that capitalism is a fair and beneficial system (Carlson

1993).

The staggering amount invested by corporations in advertising, the popularity of media focused on the lives of wealthy citizens and the pursuit of success through competition, as well as the empirical literature reviewed above, suggests that materialism,

39 consumerism, and pro-capitalist ideals related to the “American Dream” are all transmitted through media representations. Jensen (2002) argued that IAT inadequately explained how the “American Dream” is transmitted to all Americans, across subcultures, regions, and a variety of other backgrounds. Gerbner and associates suggest that television representations socialize viewers to hold “mainstream” views that are presented and repeated through media representations. Given the saturation of materialism and the focus on material and financial wealth, “mainstreaming” may explain how viewers from many different backgrounds all buy into the same materialistic visions of the “American Dream.”

It is important to point out that testing for media effects is difficult. Researchers lack the ability to compare participants who have and have not been exposed to media representations. In other words, modern media research lacks the ability to compare those exposed to media representations to a control group who has not. Media is ubiquitous in modern society and developed nations such as the U.S. have numerous media outlets, including print, television, and the internet. The messages being sent through the media pervade our lives; even those who attempt to avoid all media content still feel the effects of living in mediated society. Thus, media researchers must explore the effects of relatively slight differences in an individual’s exposure to the media. The lack of a true control group likely limits the statistical significance of media in quantitative analyses. While the classic laboratory design has been used in media research (perhaps most famously by Bandura, Ross, and Ross 1963), studies utilizing this approach are not working in line with cultivation analysis. The cultivation hypothesis focuses on the effect of media over time, through repetition.

The majority of research related to the values of the “American Dream” and media consumption has focused on materialism. While I argue that the media transmits the values associated with the “American Dream” to its viewers, it is likely the primary value sent through media consumption is materialism. However, materialistic attitudes are an essential part of the “American Dream,” perhaps even the value that underlines and drives the others. Thinking specifically about individualism and being goal oriented, these values are necessitated by materialistic pursuits. In America, individual competition and being goal oriented are values that help individuals pursue the goals valued by our society. Messner and Rosenfeld (1994) and Merton (1938) make abundantly clear that the primary goal of individuals in American society is financial gain. It is possible that the values of individualism and goal orientation stem from

Americans’ pursuit of material and financial success. Thus, materialism may be more than just one value in American culture, it may be the underlining and driving value that has promoted the development of the others.

Contribution to IAT and hypotheses

As the literature suggests, media representations may help to instill values and beliefs that contribute to the dominance of economic factors and the de-emphasis of noneconomic institutions in the lives of individuals. Moreover, the prevalence of materialistic messages within media suggests that media influences crime in a number of ways. These may include a direct effect, where media consumption directly increases the likelihood of an individual to commit crime, but also a moderating effect, as media consumption influences the relationships between the economy, noneconomic institutions, and crime.

If the mass media socializes viewers to hold the values associated with the

“American Dream,” then heavy television consumers may be more likely commit crime.

Merton (1938) and Messner and Rosenfeld (1994) maintain that these values contribute to anomic society that is prone to criminal behavior. Further, literature has long suggested that violence depicted in the media translates to violent behavior in the real world (Bandura et al. 1963; Comstock 1980; Bushman and Huesman 2001). While this literature has not been accepted without significant critique, heavy television consumers may be more likely to use violence and to turn to criminal offending to attain cultural goals.

Because media consumption strengthens the effect of the economy in the lives of viewers, it will in turn weaken the influence of noneconomic institutions identified by

IAT as crime-reducing. Thus, heavy media consumption will reduce the influence of the family, polity, education, and religion on criminal offending. When the influence of these institutions is weakened in the lives of individuals, there is a greater likelihood that noneconomic institutions will fail to buffer the effects of the economy. For example, heavy media consumers may grow more materialistic and be socialized to value economic attainment. Because of this socialization, messages sent by noneconomic institutions that do not promote the accumulation of wealth are more likely to be ignored.

Without the crime buffering influence that can be provided from education, religious institutions, the family, or other noneconomic institutions, the likelihood of using crime as a means of economic gain increases.

Individuals who consume higher amounts of television may be more invested in the “American Dream,” and thus more likely to commit criminal acts. The values

42 associated with the “American Dream” lend themselves to committing crime regardless of that individual’s current economic situation. In order to be successful, it is not enough that individuals carve out an average, middle-class existence. Attaining the “American

Dream” is about winning and having more than everyone else. Simply stated, in America no one remembers or cares who finishes second. While the “American Dream” socializes us to want more, there is not an identifiable level where success has been fully achieved.

In essence, the “American Dream” professes success by economic means, however it never indicates how much is needed before a person is successful, and so the accumulation of wealth and possessions may be never-ending. It should then be expected that the effects of an individual’s income will be felt differently between high and low media consumers. Thus, for heavy media consumers the amount of money they make should have less of an impact on the decision to commit crime, as the “American Dream” pressures them to attain more.

This research extends Messner and Rosenfeld’s work as it is one of the few tests of IAT at the micro-level. In addition, the individual-level applications of IAT that exist do not test a wide range of serious crime, something Messner and Rosenfeld (2010) suggested. The paper extends the scope of IAT not only testing it at the micro-level, but by theoretically expanding its explanation of how the “American Dream” is transmitted.

The theoretical and methodological extensions proposed lead to hypotheses about a number of relationships that may exist between individual television consumption, the economy, noneconomic institutions, and criminal behavior. The hypotheses are laid out below:

 Hypothesis 1: Television consumption will increase criminal behavior.

 Hypothesis 2: In comparison to individuals who consume low levels of television,

heavy television consumers will be less influenced by the buffering effects of

noneconomic institutions.

 Hypothesis 3: In comparison to individuals who consume low levels of television,

heavy television consumers will have higher odds of committing criminal

behavior regardless of household income.

CHAPTER IV

DATA AND METHODS

The National Longitudinal Study of Adolescent Health

The media is an important socialization agent throughout the life of an individual.

However, the impact may be more influential in childhood when individuals often develop ideas and opinions that remain with them throughout their lives (Strasburger

1995). Gerbner et al. (1980) use the “ice age” analogy to explain that the impact of media consumption is slow and steady across time. Therefore, in order to properly study the effects of media consumption on criminal offending, specifically the assumptions made about criminal offending by IAT, it is necessary to have longitudinal data on the participants’ media consumption across adolescence and into adulthood. The National

Longitudinal Study of Adolescent Health1 (ADD Health) offers measures of media consumption throughout participants’ lives, beginning in adolescence. In addition, it includes detailed information on participants’ relationships to both economic and noneconomic institutions identified by IAT as important to criminal offending. Self- reported criminal behavior is also collected in the study, providing a unique opportunity to study the relationship between media consumption and the tenets of IAT using longitudinal variables not offered by other existing data sources.

1 See Appendix A for data collection dates and citations.

The ADD Health study is the largest and most comprehensive study of adolescents ever collected (NICHD 2012). Funding for the project came from the

National Institute of Child Health and Human Development (NICHD) in addition to 17 other federal agencies in the United States (NICHD 2012). The data set collected information on a large variety of topics including participants’ friends, families, education, communities, physical health, mental health, sexual activity, criminal activity, and a range of other social and demographic characteristics. As it stands, the ADD

Health is not only one of the largest, but one of the most utilized data sets in social science research (NICHD 2012).

In its entirety, ADD Health spans across 14 years and includes four unique waves that utilize multiple data collection methods, which together provide public use data on over 6000 participants and include well over 1000 variables in each wave. Wave I was collected as part of the initial 1994 project on adolescents in grades 7 - 12, while Wave II was collected just one year later. Wave III was collected between August 2001 and April

2002 with about 5000 of the original 6500 respondents. Finally, Wave IV was collected in 2008 when the participants were between the ages of 24 and 32. Using a nationally representative sample of adolescents, Wave I and Wave II used a number of techniques to collect information pertinent to the youths’ lives. These included in-home and in-school interviews, a parent questionnaire, and a completed vocabulary test. Wave III and Wave

IV included both in-home interviews and the vocabulary test.

The data had excellent participant retention, with 80.3 percent of the original sample retained in Wave IV. The data is available in both a public and private use form, with the private data being restricted to contractually designated researchers. The more

46 extensive private use data set includes additional cases, primarily being comprised of siblings (cases involving the interview of siblings), the study’s oversampling of African-

Americans from college educated parents, and additional variables. The additional variables included in the private use data set include geographical data making multilevel modeling possible. Testing the hypotheses posited by this study does not require the additional cases attained through oversampling, or access to geographical data. This being the case, the public use data is utilized to examine the hypotheses laid out at the end of the previous chapter.

There are a number of limitations with the ADD Health data, which include some differences in the questions asked at each wave of the study. Ideally, this study would fully utilize the longitudinal nature of ADD Health by observing changes in offending throughout the life-course. This would have provided an interesting look into the relationship between media consumption and the components of IAT as individuals age.

However, the study lacks consistency between interview questions, especially in relationship to criminal behavior. Across the waves, variation in the wording and the meaning of questions related to criminal offending makes cross wave comparisons largely impossible. The data set also lacks direct measures of some demographic variables, but close proxies were constructed. Despite these limitations, the ADD Health data set is one of the most robust sources of information on adolescents and young adults.

The data for this study comes primarily from Wave IV, but multiple measures draw on responses from the earlier waves of ADD Health. The longitudinal nature of

ADD Health allows for the control of causal order and helps to create variables that provide cumulative measures. For example, media consumption was measured in all four

47 waves of ADD Health and then combined to create a measure of media consumption through the life span. Further, the longitudinal nature of the data set allows controls for prior delinquency, which is an important predictor of adult criminal behavior. This is beneficial because it strengthens the argument that differences in criminal behavior are not due to a predisposition to criminal behavior. All independent variables are measured before or at Wave IV, which is the wave that the dependent variables come from. This strengthens the inference that the temporal sequence of the independent and dependent variables is correct (see McClendon 2001).

Dependent variables

This study examines three types of criminal behavior: crimes of economic attainment, crimes of violence, and general criminal behavior. As noted earlier, these measures were collected from Wave IV to ensure causal order. IAT is primarily tested on property crime, as the drive to achieve material success using any means available lends itself to committing crimes like burglary and robbery. However, Messner and Rosenfeld

(2001) argue that IAT explains acts of violence and higher rates of crime in general. In subsequent publications Messner and Rosenfeld (2010) are direct about encouraging the use of IAT to explain multiple types of offending.

Crimes of economic attainment is an index that includes eight questions asking respondents to indicate the number of times they committed one of the following within the last year: “steal something worth more than $50,” “went into a house or building to steal something,” “use a weapon to get something from someone,” “sell marijuana or other drugs,” “steal something worth less than $50,” “buy sell or hold stolen property,”

“use someone else’s credit card, bank card, or automatic teller card without their permission knowledge,” and “deliberately write a bad check.”

The measure of violent behavior is an index that asks respondents to indicate how often they have participated in various acts of violence. These include three questions asking participants to indicate the number of occurrences within the last year that they have been involved in a “serious physical fight,” “a physical fight where a group of your friends was against another group,” and “hurt someone badly enough in a physical fight that he or she needed care from a doctor or nurse.” In addition, the index includes two dichotomous variables measuring whether or not the respondent “pulled a knife or a gun on someone” and whether or not they have “shot or stabbed someone.” Finally, the variable for all types of criminal behavior combines the indexes for crimes of economic attainment and violent crime into one variable. In addition, it includes a response gauging participation in acts of vandalism or the destruction of other people’s property.

In all data analyses the indices are dichotomized because of the relatively low number of criminal incidents indicated.2 All three dependent variables were highly skewed, with very few participants indicating that they had participated in any type of criminal behavior in the year prior to Wave IV. This is not surprising when we consider their ages at Wave IV (25 – 34), given that most have desisted from heavy criminal behavior by this point in their lives. However, the skewness of the variables does limit the variability of these measures. Dichotomizing the dependent variables simplifies the

2 See Appendix B, Appendix C, and Appendix D for a detailed description of all items included in the three dependent measures.

49 presentation of the results and makes the results interpretable to a wider audience

(Farrington and Loeber 2000)

Independent variables

IAT posits that the economy dominates other institutions causing higher rates of criminal offending. At the macro-level this is commonly modeled in terms of a country’s

GDP, the distribution of wealth, or the number of citizens who live in poverty.

Measuring the dominance of the economy at the micro-level presents a unique challenge.

Messner and Rosenfeld (2001) believe that the economy socializes individuals to adhere to the “American Dream.” Social structure dictates the extent to which an individual will be granted or blocked access to legitimate ways of attaining cultural goals. Someone who lacks legitimate access to these goals and who is exposed to the forces of the market may be more likely to commit crime. Given this logic, this study uses two measures of an individual’s economic condition as the main causal variable in relationship to criminal offending: household income and employment status.

Household income is a scale variable measuring the amount of income a respondent indicates is being collected in his/her respective household. Responses were originally coded into a 12 point scale that ranged from less than $5,000 to more than

$150,000. The variable was recoded into a 7 point scale with the following categories:

<$10,000, 10 – $24,999, 25 – $49,999, 50 – $74,999, 75 – $99,999, 100 – $149,999, and

>$150,000. Employment status is measured with a dichotomous variable that has been coded so that 1 represents respondents who are employed. Only 4.5 percent of the sample described themselves as “unemployed and looking for work,” so all other work statuses are coded as 0 (including students, those temporarily laid off, and respondents

50 who are permanently disabled). Both household income and employment status were recorded in Wave 4 of the ADD Health study. It could be argued that a better measure for explaining criminal behavior would be a variable representing income or employment status over the life-course of the participants. However, IAT seems to suggest that it is current economic forces that lead individuals to utilize criminal means to attain success.

Using this logic, using economic variables collected at the same time as the dependent variable best fit the theory.

Institutional variables

Messner and Rosenfeld (2001) and empirical tests of IAT offer insight into which institutions seem to be important in the relationship between the economy and crime.

Using these sources I include measures for the strength of the following institutions in the respondent’s lives: education, polity, religion, and family.

Education is a scale variable that asks respondents to indicate the highest level of education they have completed. Education is recorded on a 5 category scale that includes

“less than high school,” “high school graduate,” “some college or technical school,”

“college graduate,” and a “masters or doctoral degree.” Polity is a dichotomous variable that measures whether or not the respondent voted in the last election. Theoretically, individuals who participate in the democratic process may be bonded with the community and the nation, as they take an active role in its political process.

The measure of religion comes from a question asking respondents how important religion is in their lives. The responses range from (1) “not important at all” to (4) “more important than anything else.” Religious institutions generally denounce criminal behavior for various reasons, thus it is reasonable to assume that an individual’s self-

51 indentified religiosity should be negatively correlated with criminal behavior. Further, many religious institutions promote charitable acts within their community, which has been found in macro-level studies of IAT to be negatively related to crime (Chamlin and

Cochran 1997).

Three measures of family are used in the study, which included the respondent’s marital status, whether or not the respondent has any children, and a measure of the respondent’s relationship with his/her parents. Both marital status and whether or not the respondent has children were not asked directly in Wave 4. To ascertain this, the results of a series of questions asking respondents who they shared housing with was utilized.

Respondents were asked to indicate their relationship with each person living in the home. To determine marital status and whether or not the respondent had children, the results of these questions were used to determine if the respondent was living with a spouse or with children. Dichotomous variables were created for whether or not the respondent is married and whether or not they have children. These measures are not true measures of being married or having a child, as the spouse or the child would have to be physically living with the respondent. However, this still represents a strong measure of both being married and having children as it is likely the benefits and burdens of marriage or being a parent would be experienced fullest for individuals living with their respective spouse or children.

As an additional measure of the institution of family in the lives of the participants, two dummy variables are included that measure respondent’s relationships with both their mother and their fathers. Relationship was originally measured with two questions asking respondents about their relationship with their mother and their father.

Both were recorded using a 10 response scale ranging from (0) “No relationship” to (10)

“Very close.” The variables had a large number of respondents indicating that they had either a very positive or negative relationship with their parents. Dummy variables were created for respondents that indicated they had “Very close” relationships with their mother and their father. The result is two separate dummy variables that are included in the analyses, with individuals who have less than a “Very close” relationship with their respective parent and those whose parent is deceased or not known to the respondent serving as the reference category.

Media variable

Consumption of media is measured using the average number of hours that respondents watch television per week. Media consumption combines responses from three waves of ADD Health providing a cumulative measure of media exposure for the participants. Wave I, Wave III, and Wave IV are included in the measure because they are relatively equally spaced from one and other, with each wave coming about six years apart. After the waves were combined the variable was divided by three to reflect the average number of television hours consumed per week across the duration of the study.

The variable ranged from an average of no television consumed to as many as 99 hours per week.

Gerbner suggested that the effects of television consumption are cumulative across time. Thus, trying to determine small differences in outcome variables across relatively slight gradations of media consumption may be ineffective. Further, when estimating the number of hours consumed respondents tended to select numbers in increment of fives, as opposed to producing a more specific estimate of television

53 consumption. To help alleviate these issues television consumption was recoded into 7 categories with each representing a 5 hour increase in the average number of hours spent watching television across the length of the study. While television represents only one of many types of media consumption, it is heavily saturated with advertisements that may be vital to the transmission of cultural goals. Television also represents one of the primary forms of news, information, and entertainment. While multiple media measures would have been ideal, the ADD Health data set only included measures of general television, internet, and video game consumption.

Criminal predisposition

We would expect that individuals who committed crime in their youth to be much more likely to commit crime as adults. In order to determine if the relationship between media and crime is not due to individuals being predisposed to criminal behavior, it is necessary to control for prior delinquency. Prior delinquency is measured with an index that includes all forms of criminal behavior committed in the first wave of the survey.

The questions included in the index asked respondents how many times in the past 12 months that they had “painted graffiti on someone else’s property,” “deliberately damaged property that did not belong to them,” “lied to their parents about where they had been and who they had been with,” “shoplifted,” “got into a serious physical fight,”

“ran away from home,” “stolen a car,” “stolen something worth more than $50,” “stolen something worth less than $50,” and “sold drugs.” The index created was highly skewed as only a small percentage reported criminal behavior, so the variable was dichotomized.

Control variables

Control variables include numerous demographics that have been linked to criminal offending. While the longitudinal study draws from the same sample across the four waves, its participants vary significantly in age. Wave I was collected on a sample of 7th through 12th graders, so ages ranged from 25 to 32 during Wave IV. For this reason age is controlled for in the sample. Racial groups include three categories: Black, White, and “Other.” White respondents are used as the reference group, while the Black and

“Other” category are included in the model. The “Other” category is comprised of

America Indians, Asians, Latino/Latinas, and all races that did not fall into one these categories. White respondents serve as the omitted category. Sex is controlled for using a dichotomous variable with males coded as 1.

Analytical Plan

The questions that are combined to make up the three categories of criminal offending are skewed. The vast majority of the sample indicates that they were not involved in any criminal behavior over the last year. Therefore, the best way to deal with skewed dependent variables is to dichotomize them and use logistic regression. Since the majority of the sample has committed no criminal acts, grouping individuals with any criminal tendencies seems appropriate. Further, although the variables are skewed criminal behavior is still not a rare enough event in the sample to justify the use of alternative approaches, such as Zero Inflated Poisson Regression (Lambert 1992).

Logistic regression will first be used to test the major tenets of IAT. Specifically,

I will use logistic regression to determine if a relationship between television consumption and criminal behavior exists. Further, these initial models will provide

55 insight to whether or not the assumptions of IAT have relevance at the micro-level. An additive approach will be used to determine how the addition of each group of variables influences the last. First, the statistical control variables, including the measure for prior delinquency, will be entered into the model. Next, household income and employment status are entered in the model to represent economic pressure. Third, institutional variables are included into the analysis and last, the measure for average hours of television consumed across the sample is entered into the final model. With each additional group of explanatory variables included in the model the effects are recorded.

To determine if television consumption affects the relationship between noneconomic institutions and criminal behavior, the sample will be split by high and low media consumption. Very, few studies have split the amount of television consumed into high and low groups, so existing literature offers little insight into the most appropriate way to distinguish between high and low media consumption. However, Gerbner and his associates have examined differences between high and low television consumers, and others have argued its utility in testing for cultivation effects (Signorielli and Morgan

2008). Given the fact that no clear precedent has been set, splitting television consumption at the mean makes the most sense statistically. The average hours of television consumed per week across the study was 8, so low media consumption was coded as all respondents consuming 8 or less hours of television per week, while high consumers include anyone watching more than 8 hours on average per week.

There are a couple of issues worth noting that arise when splitting a sample at the mean. First, while I discuss the two groups as high and low television consumers a great deal of the two groups consume similar amounts of television. For example, someone

56 who watches 9 hours of television per day would be considered a heavy consumer, while someone who consumes 7 hours would be included in the low consumers group.

Alternative ways to split the sample were considered. For example, analyses were conducted with three levels of consumption (low, medium, and high). Results suggested very little difference between the medium and high consumers, likely reflecting that media consumption has a curvilinear relationship with criminal behavior. Given the lack of research that has split groups by level of media consumption, this research chose to follow in the footsteps of Gerbner and his associates.

The equality of coefficients test (or Z-test) is used to determine whether or not differences between the separated models reflect actual differences. While there are different formulas used to conduct z-tests, this study uses the method described by

Paternoster, Brame, Mazerolle, and Piquero (1998).3 Z-tests are common in criminological research; however, Paternoster et al. (1998) argue that research commonly uses the incorrect test, which favors the rejection of the null hypothesis. The test described by Paternoster et al. (1998) represents the most conservative version of the z- test, and helps to prevent biased estimations.

Splitting the sample by high and low media consumption offers a couple of advantages over simply running a series of interactions between key variables and television consumption. First, it allows for observing the effect of differences in media consumption across two models simultaneously and it includes all control variables.

Interaction terms are typically entered one at a time and conducted only on key variables.

Splitting the sample allows for differences across any variable by television consumption

3 2 2 Z = (b1 – b2)/√(SEb1 + SEb2 )

57 levels to be observed. Since I am interested in how television consumption affects the relationship between variables identified by IAT and variables indentified by criminological research in general, splitting the sample provides a more complete and efficient way to observe differences.

Mediation and moderation

Tests of IAT suggest two possible relationships between the economy, noneconomic institutions, and criminal offending. These include noneconomic institutions mediating the relationship between the economy and crime, and a moderating relationship with the economy and noneconomic institutions interacting to influence criminal behavior. These two approaches are commonly referred to as the “mediating effects” and “moderating effects” models of IAT. While this study does not suggest that either the “mediating effects” or the “moderating effects” model represents a better approach to studying IAT, the study does provide some insight into whether noneconomic institutions and television consumption mediate or moderate the relationship between economic forces and crime. Thus, it is important that we draw a clear distinction between a mediating and a moderating effect.

Baron and Kenny (1986) describe a moderator as a “variable that affects the direction and/or strength of the relation between an independent or predictor variable and a dependent or criterion variable” (1174). A moderator is an additional variable or group of variables that interacts with the independent variable to influence the dependent variable. In IAT, the idea that the economy interacts with noneconomic institutions to inhibit or increase criminal offending has been suggested and supported by empirical tests (Chamlin and Cochran 1995; Savolainen 2000; Pratt and Godsey 2002; Stuckey

2003). For example, Chamlin and Cochran (1995) found that an individual with low church attendance and who is unemployed is significantly more likely to commit a criminal offense than an individual with only one of these characteristics. Thus, church attendance and being unemployed has a moderating effect on criminal behavior.

A mediating relationship implies that a third variable partially or fully accounts for the relationship between the independent and dependent variable (Baron and Kenny

1986:1176). In other words, mediating variables explain a relationship, whereas moderating variables influence a relationship. With respect to IAT, Maume and Lee

(2003) find support that strong noneconomic institutions mediate the relationship between the economy and both expressive and instrumental homicide.

Summary

The ADD Health data set has many advantages, including measures for each of the demographic and institutional factors identified as important by IAT. There are also multiple measures of deviant and criminal behavior. This allows for IAT to be tested on serious forms of crime as encouraged by Messner and Rosenfeld (2010). However, the amount of deviant and criminal behavior committed by the respondents is relatively low.

For this reason, appropriate methodological steps were taken to ensure that the proper statistical procedures were used. This included recoding the dependent variables into dichotomous variables to utilize logistic regression. Two primary approaches were used to determine if television consumption influences criminal behavior and the assumptions of IAT. First, the media effect models test whether or not television consumption influences crime controlling for the factors identified as important by IAT. Finally, models are split by high and low television consumption to determine if differences in

59 television consumption impact the economic and noneconomic correlates of crime. The measurements and the statistical techniques will provide a thorough test of IAT, using the strongest methodological procedures available.

CHAPTER IV

ANALYSIS AND DISCUSSION

The analysis begins with a description of the sample, including control variables, economic and noneconomic variables, the television consumption variable, and the dependent variables. In addition, bivariate correlation analysis is conducted between all variables included in the analysis to test for initial direct relationships and issues of multicollinearity. Next, a serious of logistic regressions will be discussed to test the major hypotheses laid out in the previous chapters. The first series will test the tenets of

IAT at the micro-level, while determining if television consumption influences criminal behavior. Finally, the sample will be split by high and low television consumption to examine its effects on the models specified by the theory.

Descriptive and Bivariate Results

Within the sample, 18 percent of participants admitted that they committed some act of criminal behavior in the year prior to the collection of Wave IV. This is the highest percentage of deviance across the three measures. Only 11 percent of respondents admitted that they had committed criminal behavior with the intention of economic benefit. Lower still, only about 9 percent of the sample admitted being involved in any violent activities.

The majority of the sample is employed (84%) and has a household income of between $50,000 and $75,000. The average achievement level in education is at least

“some college” and about 25 percent of the sample indicated that they “always” vote in local and state elections. The majority of the sample indicated that religion is

“important” to them, with the variable having a mean of 2.55, on a four point scale from

“not important” (coded as 1) to “more important than anything else” (coded as 4). About

40 percent of the sample is married, and 46 percent of the sample have children that they live with. The majority of respondents have positive relationships with their mothers

(64%), while only 42 percent indicated having a positive relationship with their father.

Television consumption has a mean of 2.9, which translated to average respondent consuming an average of 11 to 15 hours a week across Wave I, III, and IV of the study.

Less than half of the respondents are male (46%), with all of the respondents falling between the ages of 25 and 34 (the average age is 29). The majority of the respondents identified themselves as “White,” with only 25 percent of the sample identifying as “Black,” and 14 percent of the sample being recoded into the “Other” category. The vast majority of respondents (about 72%) were involved in some act of deviance at the time the first wave of the study was collected.

Table 1. Descriptive Characteristics of the Sample

Variable Description Range Mean Dependent Variables Criminal Behavior Dichotomized index of all forms of criminal behavior 0 - 1 0.18 committed in the last year. Crimes of Economic Dichotomized index of all criminal behavior committed for the 0 - 1 0.11 Attainment purpose of economic attainment in the last year. Crimes of Violence Dichotomized index of all violent criminal behavior committed 0 - 1 0.09 in the last year. Economic Variables Household Income 1< 10,000, 2=10 – 24,999, 3=25 – 49,999, 4=50 – 74,999, 5=75 1 - 7 3.81 – 99,999, 6=100 – 149,999, 7= >150 Employed Measure of current employment status. 1=Employed, 0 - 1 0.84 0=Unemployed Noneconomic Variables Education Measure of degree completion ranging from 1=less than high 1 - 5 3.09 school through 5=graduate degree or higher. Religion Measure of how important religion is to R. 1=not important 1 - 4 2.55 through 4=more important than anything else Polity Measure of whether or not R voted in last presidential election. 0 - 1 0.25 Married Measure of whether or not R is married and living with spouse. 0 - 1 0.40 0=not married, 1=married Children Measure of whether or not R has his/her own children living 0 - 1 0.46 with them. 0=no children, 1=has children Relationship Mother Dummy variable measuring the strength of R’s relationship 0 - 1 0.64 with Mother. 0 = all else, 1=very close Relationship Father Dummy variable measuring the strength of R’s relationship 0 - 1 0.42 with Father. 0 = all else, 1=very close Media Variable Television Variable measuring the average hours R spent watching 1 - 7 2.9 television per week recoded into 7 categories. 1≤5, 2= 6-10, 3=11-15, 4=16-20, 5=21-25, 6=26-30, 7=31+ (W1, W3, W4) Control Variables Age Age of respondent at W4 25 - 34 29.00 Black Black = 1, Other = 0 0 - 1 0.25 Other Other = 1, White or Black = 0 0 - 1 0.14 White (Reference) White = 1, Other = 0 0 - 1 0.61 Male Male = 1, Female = 0 0 - 1 0.46 Criminal Predisposition Prior Delinquency Dichotomized index of all forms of criminal behavior 0 - 1 0.68 committed in the first year of the survey (W1).

Most of the bivariate correlations were significant at p<.001 (see Table 2). This is especially true for correlations between the dependent variables and all the other variables included in the analysis. Of particular interest to this study, television

63 consumption is significantly correlated at the p<.001 level with all three dependent variables. In other words, without controlling for any other factors, television consumption is significantly and positively related to committing crimes of economic attainment, violent crime, and all types of crime in general.

With the exception of polity and respondent’s relationship with their mothers (in relationship to violent crime only), all of the measures of noneconomic institutions

(married, children, relationship with mother, relationship with father, religion, and educational attainment) are significantly and negatively correlated with the three dependent variables. These correlations are all in line with IAT, as the theory suggests involvement in noneconomic institutions reduces the chances that individuals will engage in criminal behavior. Admittedly, whether or not someone has voted does not represent the best measure of polity. However, it has been used in studies of IAT at the macro-level, and the dataset lacked additional measures that could have provided a better representation of polity. The lack of correlation between polity and the three measures of criminal behavior is likely a reflection of this.

Being employed and having higher levels of income are both negatively correlated with criminal behavior. Income is significantly correlated with all three types at the p<.001 level, while employment status is significantly correlated with general and violent crime but is not significantly related to crimes of economic attainment. Of the statistical control variables, all are significantly correlated with the three dependent variables. Prior delinquency, being Black, being male, and belonging to the “Other” racial category all had a positive relationship with the three types of criminal behavior.

Belonging to the “Other” racial category was positively related to violent and general

64 criminal behavior, but was not correlated with committing crimes of economic attainment. Age was negatively correlated with all three dependent variables.

The bivariate correlation analysis demonstrated a number of important elements.

First, the basic relationship between economic variables, noneconomic variables, and criminal behavior is confirmed. Second, television consumption is positively correlated with all types of criminal behavior. Because these correlations exist, it indicates that further exploration of the relationship between television consumption and the tenets of

IAT is justified.

Media Effects Models

A total of three logistic regressions are conducted for the media effects models.

Table 3 depicts the odds ratios of the effects of media consumption and the components of IAT on the dichotomous variable measuring involvement in criminal behavior for the purpose of economic attainment. Table 3 includes four models; Model 1 has only the control variables, Model 2 adds the economic variables of income and employment status, Model 3 adds the institutional variables, and Model 4 is the full model including the measure for television consumption. This procedure is repeated in Tables 4 and 5 with dependent variables for violent behavior and general criminal behavior, respectively.

The odds ratios reported are interpreted as the percent change in the odds of committing criminal behavior. Odds ratios that are over one indicate a positive relationship with the dependent variable, while odds ratios under one suggest a negative relationship.

A total of 4965 out of 5114 respondents are included in the first media effect model with the results presented in Table 3. The missing data is missing at random and does not bias the results. In Model 1 of Table 3, being male, being Black, and having committed criminal behavior during the first wave of the ADD Health data set significantly increase the odds of respondents committing a crime for economic gain.

Age is negatively correlated with participating in a crime of economic attainment, with respondents over 13 percent less likely to commit the act with each year they age.

Belonging to the racial category of “Other” is the only control variable that does not affect the odds of committing economic-based crime in the initial model.

As one would expect, household income is negatively related to committing economic-based crimes. Employment status is not significant. The addition of economic

67 variables in Model 2, does not change most of the control variables. All relationships that were significant continue to influence the odds of committing economic-based crimes in the same direction and at the same significance level. The one exception is that

Black is now significant at the .01 level instead of the .001 level, which suggests that income and employment status may account for some of the original relationship between being Black and committing crimes of economic attainment.

Model 3 introduces the measures for noneconomic institutions into the analysis and again the strength and direction of the control variables are relatively unaffected.

Most of the noneconomic institutions significantly influence the respondent’s odds of committing crimes of economic attainment. Level of educational attainment

(Exp(B)=.812) and marital status (Exp(B)=.638) significantly decrease the odds of committing economic crimes. Respondents who have children (Exp(B)=.769) and a positive relationship with their mother (Exp(B)=.773) and father (Exp(B)=.791) are less likely to commit economic-based crimes than those who do not. Religiosity

(Exp(B)=.868) decreases the odds of committing crimes of economic attainment.

Table 3: Odds Ratios of the Influence of Television on Committing Crimes of

Economic Attainment

Model 1 Model 2 Model 3 Model 4 Controls Economic Noneconomic Media Exp(B) N=4965 Control Variables Male 2.276*** 2.397*** 2.038*** 2.007*** Age .867*** .872*** .890*** .891*** Other 1.156 1.181 1.139 1.131 Black 1.501*** 1.385** 1.410*** 1.349* Prior Deviance 2.202*** 2.151*** 1.990*** 1.977*** Economic Variables Income .841*** .895** .897** Employed .930 .951 .965 Noneconomic Institutions Education .812*** .824*** Religion .868** .876* Polity 1.167 1.175 Relationship Mother .773* .772* Relationship Father .791* .787* Children .769* .768* Married .638*** .638*** Media Variable Television 1.092* Naglekerke R2 .083 .103 .142 .144 ***p<.001, **p<.01, *p<.05 4

Finally, Model 4 adds the measure for television consumption to the model.

Television consumption significantly increases the odds that a respondent will commit economic-based crimes. With every five hour average increase in television consumption per week, the odds of a respondent committing economic-based crimes increased by

1.092 or about 9 percent. Moreover the inclusion of the television variable did not

2 4 Logistic regression reports pseudo R . Given the debate about their utility (Veall and 2 Zimmermann 2006), Naglekerke R is reported but not discussed.

69 significantly affect the relationships that the control, economic, and noneconomic institution variables have with economic-based crimes.

Table 4 depicts the odds ratios from the logistic regression testing the influences of television consumption and the tenets of IAT, on violent criminal behavior. In Model

1 all control variables significantly influence the odds of respondents committing violent criminal behavior. Being male, being Black or a member of the “Other” racial category, and committing previous acts of deviance all significantly increase the odds of committing violent behavior at the .001 level. As one would expect, age is negatively related to violent behavior. While traditionally age is one of the most consistent and strongest predictors of violence, the sample only includes individuals between the ages of

25 and 34, so the effects are not as robust as prior studies.

In Model 2 the economic variables are included in the analysis. Both household income and being employed reduce the odds of committing acts of violence. Household income has an odds ratio of .799 (p<.001), suggesting that with each additional increase in an income category the odds of committing violence decrease by about 20 percent.

Being employed reduces the odds of committing violence by nearly 25 percent; however, this relationship is only significant at the .05 level. With the inclusion of the economic variables age is no longer significant in the model. All other control variables retain their original relationship with violent behavior.

Table 4: Odds Ratios of the Influence of Television on Committing Violent Crimes

Model 1 Model 2 Model 3 Model 4 Controls Economic Noneconomic Media Exp(B) N=4533 Control Variables Male 3.586*** 3.940*** 3.593*** 3.538*** Age .938* .945 .959 .961 Other 1.770*** 1.838*** 1.779*** 1.766*** Black 1.900*** 1.705*** 1.670*** 1.608*** Prior Deviance 1.719*** 1.661*** 1.552*** 1.544*** Economic Variables Income .799*** .872** .875** Employed .768* .715* .722* Noneconomic Institutions Education .747*** .755*** Polity 1.045 1.051 Religion .883 .889 Relationship Mother 1.035 1.034 Relationship Father .810 .806 Children 1.092 1.087 Married .597*** .598*** Media Variable Television 1.089* Naglekerke R2 .083 .089 .119 .124 ***p<.001, **p<.01, *p<.05

With the inclusion of noneconomic institutions in Model 3, the influence of household income on the odds of committing violent behavior is somewhat reduced

(Exp(B)=.872). This may suggest that the effect of income of violence is partially mediated by the noneconomic institutions. However, only education and marital status significantly decrease the odds of committing violent behavior. Attaining one additional level of education decreases the likelihood of committing violence by over 25 percent

(p<.001). In addition, being married decreases the likelihood of committing violent behavior by 40 percent, which is significant in the model at the .001 level. All other noneconomic variables in the model are not related to violent behavior. Finally, Model 4

71 includes the measure for average hours of television consumed per week across ADD

Health’s waves. For each additional five hours of television consumed the odds of committing violent crime increase by nearly 9 percent.

Table 5 displays the results of the final logistic regression with a dependent variable that measures participation in any act of criminal behavior in Wave 4 of the study. To reiterate, this includes measures of violent crimes, economic-based crimes, and a measure determining whether or not the respondent had committed an act of vandalism in the last year. In Model 1, males are more than 2.5 times more likely to commit a criminal act in comparison to women in the study. Committing a delinquent act in wave

1 increased the odds of committing criminal behavior by more than two. In comparison to white respondents, Blacks were 51 percent more likely and individuals classified as belonging to the “Other” racial category were about 36 percent more likely to commit a criminal act than Whites. Finally, age was the only control variable that reduced the propensity to commit a criminal act, decreasing the likelihood by 12 percent with each additional year. With the exception of individuals classified into the “Other” (p<.01) racial category, all variables were significant at the .001 level.

Table 5: Odds Ratios of the Influence of Television on Committing General

Criminal Behavior

Model 1 Model 2 Model 3 Model 4 Controls Economic Noneconomic Media Exp(B) N=4526 Control Variables Male 2.599*** 2.771*** 2.262*** 2.379*** Age .880*** .885*** .905*** .906*** Other 1.362** 1.399** 1.336* 1.359** Black 1.513*** 1.392*** 1.500*** 1.378** Prior Deviance 2.029*** 1.978*** 1.837*** 1.803*** Economic Variables Income .836*** .894*** .897*** Employed .829 .877 .883 Noneconomic Institutions Education .803*** .812*** Polity 1.166 1.172 Religion .825*** .830*** Relationship Mother .859 .857 Relationship Father .801* .797* Children .875 .873 Married .573*** .573*** Media Variable Television 1.081* Naglekerke R2 .088 .109 .144 .146 ***p<.001, **p<.01, *p<.05

The relationships between the control variables and criminal behavior are not significantly altered with the inclusion of the economic variables into Model 2. Income is the only variable of the two significantly correlated with criminal behavior, as an increase of one income bracket reduces the likelihood of committing criminal behavior by 16.4 percent (p<.001). Model 3 adds the noneconomic variables into the analysis.

Education, religion, relationship with father, having children, and being married all reduce the likelihood of committing criminal behavior. For example, attaining just one

73 additional level of education reduces the likelihood of committing a crime by 20 percent

(p=.001), while one additional increase in the importance of religion in one’s life decreases the likelihood of committing crime by 17.5 percent (p<.001). Being married decreases the likelihood of committing crime by 42.7 percent (p<.001) compared to those who are married, while having a positive relationship with one’s father reduces the likelihood of committing crime by 20 percent (p<.05).

In the final model, television consumption is included and the relationships between criminal behavior and the other variables in the model do not change significantly. Television consumption is significant in the model, with each additional 5 hours of television consumed per week across the span of the data increasing the odds of committing criminal behavior by about 8 percent. This relationship is significant at the

.05 level.

Media effects models: discussion

The media effects models included three separate logistic regressions testing the influence of television consumption on criminal behavior, while controlling for variables identified as important by Messner and Rosenfeld’s IAT. Three dependent variables were used to represent criminal behavior: criminal acts committed for economic gain, criminal behavior involving the use of violence, and all types of criminal behavior. Logistic regressions were used to analyze each dependent variable, and additive models entered each theoretically important variable or group of variables into the analysis. This allowed for determinations to be made about the possible mediating effects of these variables.

The results of the three media effect analyses are important for a number of reasons. First, they provide one of the first micro-level tests of IAT on serious forms of

74 criminal behavior. The components of IAT have primarily been tested at the macro-level, and a few studies have explored IAT at the micro-level (Muftic 2006; Karstedt and Farrell

2006). Further, these studies did not focus on multiple forms of serious criminal behavior, leading Messner, Thome, and Rosenfeld (2008) to suggest additional attempts be made to apply the theory at the micro-level. Second, while television consumption has been linked to behaviors associated with crime, like violence, it is unknown whether or not television consumption directly influences the likelihood of individuals committing serious criminal behavior.

Control variables included in the analyses consistently influenced the odds of committing all three types of criminal behavior. Males, Blacks, individuals included in the “Other” racial category, and respondents who have committed a criminal act during

Wave I of the study consistently had higher odds of committing criminal acts. Belonging to the “Other” racial category was not related to committing crimes of economic attainment, but it was associated with higher odds of committing violent behavior and general acts of crime (which includes violence). This finding is important to IAT, as the

“Other” category includes foreign born individuals and individuals that may be influenced by subcultures other than that which dominates the United States. While low sample size prevents further examination of this finding, it could be that the “Other” category is not correlated with committing a crime of economic attainment because of differences in culture. Another micro-level test of IAT came to a similar conclusion when looking at cheating in college, as foreign-born students were less likely than American born students to cheat on college assignments (Muftic 2006).

Age was the only control variable that reduced the likelihood of committing criminal acts in almost all three models. However, age was not found to be significantly related to violent behavior after controlling for economic variables. While this is a surprising finding given the importance of the relationship between age and violence identified in the vast majority of criminological research on the topic, it is important to keep in mind that the age data is truncated, only ranging from 25 to 34. Further, the violent crime variable had little variability, with a fewer number of respondents indicating they had participated in a violent crime than in the other two types of crime.

The combination of these two factors likely limits the effects of age on violent behavior.

Measures for household income and a dummy variable for whether or not the respondent is employed are used in all the analyses to represent economic pressure, or given the way they are coded in this analysis, the alleviation of economic pressure.

Having a higher household income consistently reduced the odds of committing all three types of criminal behavior. The relationship between income and the three dependent variables remained even after controlling for noneconomic institutions and television exposure. Surprisingly, employment was not consistently correlated with criminal behavior across the models. The only exception was it was weakly correlated with committing a violent act. Employment had less of an impact than one might expect given that research tends to support the idea that employment status is highly correlated with crime. Perhaps employment status may not be as strong of a measure for economic pressure for individuals between the ages of 25 and 34. Only 4.5 percent of the sample identified themselves as being unemployed and looking for work, and the study did not differentiate between working full or part-time. Thus, employed respondents are

76 compared to individuals who are temporarily laid off, who are students, and who are disabled. This in all likelihood limits the effects of being employed on the odds of committing crime.

Measuring the noneconomic variables identified by Messner and Rosenfeld as important was difficult. The results of the analyses do support many of the assumptions made by the theory and suggest that the theory has micro-level application. Educational attainment and marital status were the strongest and most consistent predictors of criminal behavior across the three models. Across all three dependent variables, achieving higher levels of education and being married significantly reduced the odds of committing a criminal act. These relationships remain significant with the inclusion of television consumption, which suggests that television consumption does not mediate the relationship between noneconomic institutions and criminal behavior.

Believing that religion is an important factor in your life reduced the odds of committing a crime of economic attainment and all types of crime in general, but it had no influence on violent crime. Respondents who had a positive relationship with their mother were less like to commit a crime for economic benefit, while respondents who had positive relationships with their fathers were less likely to commit economic crime and all crime in general. The correlation between respondent’s relationship with their parents and committing a crime of economic attainment could be related to the idea that individuals in good standing with their parents may receive financial support from them as well. This may provide a buffer between the individual and the full burden of the economy. Further, the finding that a positive relationship with one’s father reduces the

77 odds of committing crime is in line with research looking at father/son relationships and criminal outcomes (Jaffee et al. 2003).

Polity was not found to be significantly related to any type of criminal behavior in the study. This is likely because voter participation is not a strong measure for polity, but this was the best measure available. On the other hand, having children did reduce the odds of committing a crime of economic attainment, but it was not significantly related to crimes of violence or to general criminal behavior. While having children represents a family bond and motivation to abstain from criminal behavior, stress from having children could make violence in and outside the home more likely. This may explain why it does not strongly reduce the odds of committing crime. In fact, although it never reaches statistical significance it consistently has a positive relationship with violence in the analysis.

The results discussed above suggest that IAT has relevance at the micro-level.

Just as predicted in the theory, economic pressure caused from having low income was significantly related to committing all three types of serious crime. Further, noneconomic institutions were negatively correlated with criminal behavior, serving as mechanisms that reduce the odds of committing crime. The influence of noneconomic institutions did appear to be strongest when explaining crimes of economic attainment. All noneconomic institutions, with the exception of polity, significantly reduced the odds of respondents committing a crime for economic gain. This may suggest that IAT is best suited for explaining financially motivated crimes. However, noneconomic institutions like educational attainment, strength of religious beliefs, and being married reduced crime consistently across all three dependent variables.

Finding support for IAT at the micro-level is an important finding in the development of the theory, especially as this is the first test on serious forms of criminal behavior. However, the focus of this research is to determine the role that television consumption may play in relationship to IAT. Since Messner and Rosenfeld are unclear about what this relationship may be (or at least they do not elaborate on it fully), it was important to first establish that a direct relationship between television consumption and criminal behavior does exist. While there have been a number of studies linking media consumption to aggression and violent behavior (Hearold 1986; Paik and Comstock

1994; Ybarra et al. 2008), very few have tested for a relationship between television consumption and other forms of serious criminal behavior.

Across all three types of criminal behavior, television consumption significantly increased the odds of committing crime. This relationship exists even while controlling for economic, noneconomic, and control variables identified by IAT and other criminological research as being highly correlated with criminal behavior. Further, this relationship remains while controlling for prior deviant behavior, suggesting that television consumption impacts criminal behavior even for those who may have a propensity towards crime. Across the three models, each additional 5 hours of television consumption increased the odds of committing crime by about 8 to 9 percent. While this may not be considered a large increase or a strong relationship, when considering the difficulties associated with studying media consumption this represents a substantial finding.

Many studies of media consumption fail to find statistical significance. This is sometimes interpreted as media consumption being of little importance to behavior or

79 opinions, but a more likely explanation lies in the difficulty of conducting media research. Everyone is exposed to media messages, even those who attempt to isolate themselves, and thus researchers are left without a statistical control group. Gerbner

(1980) explains the media’s limited significance in quantitative research by using his “ice age” analogy. The basic idea is that media consumption does not have a single large impact, like sex or race, but it has a steady impact on individuals throughout their lives.

Just as at the beginning of an ice age the temperature only drops a few degrees at a time, media has a slow but steady effect across an individual’s life. What may be more important than the statistical significance determined in the study, is that the direction and the relationship between media consumption and criminal behavior is consistent and in the expected direction.

Issues with studying the media, and the “ice age” analogy presented by Gerbner

(1980), make it clear that differences in media consumption are not likely to yield the same kind of statistical results as other variables. This of course does not mean that the media is not important; it simply means that differences in small gradations of media consumption are unlikely to yield results. Thus, it may be necessary to test for media effects by splitting the sample by high and low media consumption. Differences in criminal behavior due to television consumption may become more apparent when comparing large differences in television consumption. Further, splitting the micro-level test of IAT by high and low television consumption may offer further insight into the role that media plays in the theory.

Moderating Effect Models

The following analyses split the sample by high and low television consumption to determine if the predictor variables affect the odds of committing crime differently across the two groups. In other words, television consumption may moderate the relationship between the noneconomic institutions and crime. In order to determine if differences across high and low media consumption reflect actual differences, the equality of coefficients test described by Paternoster et al. (1998) is utilized.

Table 6 displays the results of separate logistic regressions for high and low media consumers. Analyses for both high and low consumption include two models;

Model 1 including control and economic variables and Model 2 which adds the noneconomic variables into the analysis. The comparison of coefficients test (labeled as a z-test), is a two-tailed test determining if differences in Model 2 for low and high television consumption reflect statistical differences. Variables that are not statistically different across low and high television consumption cannot be interpreted as representing a real difference. For example, as seen in Model 2 low television consumers who are married are much less likely to commit a crime of economic attainment

(Exp(B)=.600, p<.001) than those who are not married. However, being married is not statistically related to crimes of economic attainment for respondents who consume high amounts of television. Although the effect of being married appears to be different across the two models the equality of coefficients test does not reach statistical significance (Z=-.925). This means that the coefficients are not statistically different from each other, and that we cannot interpret the effect of being married on committing crimes of economic attainment to be different across high and low television consumers.

Table 6: Odds Ratios of the Influence of Institutional Factors on Committing Crimes

of Economic Attainment by Levels of Television Consumption

Variables Low Media High Media Z-Test Model 1 Model 2 Model 1 Model 2 Economic Noneconomic Economic Noneconomic Exp(B) N=3213 Exp(B) N=1753 Control Variables Male 2.309*** 1.947*** 2.029*** 1.818*** .319 Age .889** .917* .856*** .858*** 1.183 Other 1.124 1.118 1.155 1.123 -.014 Black 1.325 1.237 1.383* 1.546* -.924 Prior Deviance 2.181*** 2.134*** 2.048*** 1.688** 1.726* Economic Variables Income .801*** .845*** .923 .953 -1.734* Employed 1.218 1.210 .790 .791 1.593 Social Institutions Education .777*** .938 -1.781* Religion .903 .828* .738 Polity 1.073 .983 1.002 Relationship Mother .887 .671* 1.340 Relationship Father .775* .835 -.343 Children .713* .796 -.474 Married .600*** .755 -.925 Naglekerke R2 .079 .116 .066 .104 ***p<.001, **p<.01, *p<.05

Looking at low television consumers in Table 6, being male (Exp(B)=2.309, p<.001) and committing prior deviance (Exp(B)=2.181, p<.001) increases the odds of committing an economic-based crime. Age is negatively correlated with the dependent variable, as each additional year decreases the propensity to commit economic-based crime by about 11 percent. Income is also significant in the model, with each additional income bracket reducing the likelihood to commit crime by 20 percent. Looking specifically at models 1 and 2 for individuals who consume low amounts of television, the addition of noneconomic variables into the model does not appear to impact the

82 relationship between income and committing crimes of economic attainment. In Model 2 for low television consumers education (Exp(B)=.777, p<.001), relationship with father

(Exp(B)=.775, p<.05), having children (Exp(B)=.713, p<.05), and being married

(Exp(B)=.600, p<.001) reduce the likelihood of committing crimes of economic attainment. Other variables in the model did not reach a level of statistical significance.

As seen in Model 1, for high television consumers, being male and prior deviance increases the odds of committing a crime of economic attainment by about two-fold.

African-American respondents were about 38 percent more likely to commit a crime of economic attainment than Whites, which is significant at .05 level. Age is negatively correlated with economic-based crime, with each year of age reducing the respondents’ likelihood of committing economic crimes by 14.4 percent (p<.01). Other control variables and the economic variables were not significantly related to whether or not individuals with high hours of television consumption committed economically motivated crime. With the addition of noneconomic institutions in Model 2, the relationship between the control and economic variables are relatively unaffected. Of the noneconomic variables only religion (Exp(B)=.828) and the respondent’s relationship with their mother (Exp(B)=.671) significantly decreased the odds of committing an economic-based crime. Both of these relationships are significant at the .05 level.

Table 7 displays the results of separate logistic regressions for high and low television consumers on the dependent variable measuring participant’s involvement in violent crime. In Model 1 for low television consumers, being male, Black, and committing prior deviance increase the odds of being involved in an act of violence.

Having higher income (Exp(B)=.816, p<.001) significantly reduces the odds of

83 committing a violent act, while employment status is not related. As seen in Model 2, with the addition of noneconomic variables, income is no longer significantly related to violent behavior. Only two noneconomic variables are significant in Model 2; education

(Exp(B)=.708) and being married (Exp(B)=.452), both which reduce the odds of committing a violent act.

Table 7: Odds Ratios of the Influence of Institutional Factors on Committing Crimes of

Violence by Levels of Television Consumption

Variables Low Media High Media Z-Test Model 1 Model 2 Model 1 Model 2 Economic Noneconomic Economic Noneconomic Exp(B) N=2927 Exp(B) N=1607 Control Variables Male 3.762*** 3.416*** 4.129*** 3.855*** -.445 Age .993 1.021 .894* .896* 1.959* Other 1.397 1.361 2.519*** 2.471*** -1.927* Black 1.526* 1.342 1.833*** 2.017*** -1.453 Prior Deviance 1.669** 1.565** 1.629* 1.499 .145 Economic Variables Income .816*** .906 .784*** .835*** .917 Employed .733 .745 .658* .686 .277 Social Institutions Education .708*** .811* -1.121 Religion .889 .881 .072 Polity 1.178 .897 .954 Relationship Mother 1.034 1.036 -.004 Relationship Father .781 .835 -.271 Children 1.178 .991 .628 Married .452*** .845 -2.111* Naglekerke R2 .090 .128 .130 .152 ***p<.001, **p<.01, *p<.05

As seen in Model 1 of Table 7, being male, being Black or belong to the “Other” racial category, and having committed prior deviant acts increases the odds of committing violent acts among high television consumers. Males (Exp(B)=4.129,

84 p<.001) are more likely to commit violent crime than women, with male respondents being over four times as likely than females. Age (Exp(B)=.894) reduces the odds of committing violence; this relationship is significant at the .05 level. Both household income (Exp(B)=.784, p<.001) and employment status (Exp(B)=.658, p<.05) also reduce the odds of committing violent behavior for heavy television consumers. With the exception of employment status which becomes non-significant, these relationships were not affected by the inclusion of noneconomic variables. Only education is significantly related to violent behavior, with each additional education level attained decreasing the likelihood of committing violent behavior by nearly 19 percent (p<.05).

Table 8 displays the results of separate logistic regressions for high and low television consumers testing the tenets of IAT on all types of criminal behavior. In Model

1, low television consumers who are male (Exp(B)=2.817, p<.001), Black

(Exp(B)=1.300, p<.01), and who committed prior acts of deviance (Exp(B)=1.838, p<.001) are significantly more likely to participate in criminal behavior. Age

(Exp(B)=.922, p<.01) and household income (Exp(B)=.818, p<.001) significantly decrease the odds that respondents with low television consumption will commit criminal acts. With the addition of the noneconomic variables, age and being Black are no longer significant. Of the noneconomic variables education (Exp(B)=.763, p<.001), religion

(Exp(B)=.853, p<.05), relationship with father (Exp(B)=.767, p<.05), and being married

(Exp(B)=.500, p<.001) significantly reduce the odds of committing criminal behavior.

Table 8: Odds Ratios of the Influence of Institutional Factors on Committing General

Criminal Behavior by Levels of Television Consumption

Variables Low Media High Media Z-Test Model 1 Model 2 Model 1 Model 2 Economic Noneconomic Economic Noneconomic Exp(B) N=2923 Exp(B) N=1604 Control Variables Male 2.817*** 2.409*** 2.645*** 2.379*** .065 Age .922** .956 .841*** .845*** 2.514** Other 1.248 1.238 1.586** 1.565* -.982 Black 1.300* 1.224 1.381* 1.569** -1.188 Prior Deviance 1.838*** 1.709*** 2.178*** 2.031*** -.800 Economic Variables Income .818*** .888** .871** .907* -.324 Employed .904 .903 .780 .795 .556 Social Institutions Education .763*** .880 -1.657* Religion .853* .788** .787 Polity 1.264 1.047 .934 Relationship Mother .895 .813 .534 Relationship Father .767* .837 -.479 Children 859 .873 -.080 Married .500*** .702* -1.734* Naglekerke R2 .092 .141 .109 .138 ***p<.001, **p<.01, *p<.05

For high television consumers males were two times more likely than females to commit a criminal act. In addition, Black respondents (Exp(B)=1.138, p<.05), “Other” respondents (Exp(B)=1.586, p<.01), and individuals involved in prior deviance

(Exp(B)=2.187, p<.001) were all more likely to commit crime. Age (Exp(B)=.841, p<.001) and income (Exp(B)=.871, p<.01) significantly reduce the odds of committing crime, while employment status is not significant in the model. Model 2 adds noneconomic variables into the analysis, and for heavy television consumers religion

(Exp(B)=.788, p<.01) and being married (Exp(B)=.702, p<.05) significantly reduced the

86 odds of committing crime. All other noneconomic variable are not significant in the model.

Comparison of Coefficients Test

Table 9 includes displays all of the variables that were statistically different across media consumption according the equality of coefficients test. Prior deviance, income, and education all have a significantly larger impact on committing a crime of economic attainment for participants who consume low amounts of television. Prior deviance significantly increases economic-based criminality for both high and low television consumers; however, the coefficient is statistically larger for individuals who consume low amounts of television. While both income and education significantly decrease the likelihood of committing a crime of economic attainment for low media consumers, they are not statistically related to committing crimes of economic attainment for heavy television consumers.

Table 9: Tests for Equality of the Influence of Institutional Factors on Criminal Behavior

across High and Low Television Consumption

Economic Attainment Violence General Crime Age X X Other X Prior Deviance X Income X Education X X Married X X “X” denotes statistically significant difference between high and low television consumers.

The results of the equality of coefficients test shows that only three variables are statistically different across high and low television consumers in reference to violent behavior. Age, the racial category of “Other,” and being married have statistically

87 different effects on violent behavior for high and low media consumers. Age significantly reduced the likelihood of committing a violent act for heavy television consumers, but it was not significantly related to violence for low television consumers.

Similarly, participants belonging to the “Other” racial category who are heavy television consumers are nearly 2.5 times as likely to commit violent crime as White heavy television consumers. The racial classification of “Other” is not significantly related to violence for low television consumers but is correlated with violence for heavy consumers, and the difference between high and low consumers is statistically significant. Finally, being married strongly reduces the odds of committing violent acts for low television consumers, but it has no effect on individuals who consume high amounts of television.

Looking at general criminal behavior, for heavy television consumers age decreases the odds of committing any type of crime, while age is not significantly related to crime for individuals with low television consumption. Similar to the crimes of economic attainment models, higher levels of education strongly reduce the odds of committing crime for low television consumers while having no impact on heavy television consumers. Similarly, there is a statistical difference between the strength of the relationship between being married and committing crime across television consumption. Being married has a greater impact on reducing the odds of committing crime for low television consumers than high television consumers.

Moderating effect models: discussion

The equality of coefficients test identified a number of variables that have statistically different effects on criminal behavior for high and low television consumers.

Some of these variables were only significantly different for one dependent variable; however, education and being married had significantly different effects for high and low media consumers across multiple dependent variables. The result of these split models offer some insight into how media consumption affects the relationships between variables identified as important by IAT and the propensity to commit criminal behavior.

Three statistically significant differences between high and low television consumption emerged from the first split model test. For individuals with low amounts of television exposure, prior deviance, household income, and education all had a significantly larger impact on the odds of committing crimes of economic attainment in comparison to high television consumers. While prior deviance does have a significant influence on the odds of committing a crime of economic attainment for both high and low media consumers, the relationship is stronger for low television consumers. This is an interesting finding, as it suggests that television consumption moderates the relationship between prior deviance and committing crimes of economic attainment.

Prior deviance is no doubt one of the strongest predictors of committing future criminal acts. However, the findings suggest that consuming high amounts of television reduces the influence of previous delinquency on committing future crimes of economic attainment. It may be that the “American Dream,” transmitted through television representations, moderates the relationship between prior delinquency and criminal behavior. Thus, even individuals who were not previously delinquent have similar odds of committing crime when they consumer large amounts of television.

Having higher levels of household income significantly reduced the odds of committing economically motivated crimes for low television consumers, but it had no

89 impact on individuals who consume high amounts of television. This finding is in line with the theory. Television representations are littered with depictions of happiness through the accumulation of financial and material success. Someone who consumes high amounts of these representations, having a high household income has less influence on the decision to commit economic-based crimes. Even individuals who can afford to live a modest life may not be satisfied if they consume heavy amounts of television that suggest that the middle-class lifestyle does not equate to happiness.

The final difference observed across television consumption for the models involving economically-based crime concerns the influence of education. Educational attainment, much like income, significantly reduced the odds of committing an economically motivated crime for low television consumers but had no effect on heavy consumers. This suggests that heavy television consumption may eliminate the crime reducing effect that attaining higher levels of education produces. In essence, heavy television consumption decreases the ability of education to reduce the likelihood to commit crime. This suggests that television consumption may moderate the relationship between noneconomic institutions and crimes of economic attainment.

The comparison of coefficients test produced three statistically different relationships in the variables explaining violent criminal behavior across media consumption. These included the varying effects of age, the racial category of “Other,” and being married. Age and belonging to the “Other” racial category significantly affected the odds of individuals committing crimes of violence for high television consumers but had no effect on low media consumers. Age reduced the odds of committing violent crime, while belonging the “Other” racial category more than doubles

90 the odds of an individual committing a violent offense in comparison to Whites. The effect of age across high and low media consumption is a perplexing finding for a number of reasons. It is hard to speculate what it is about television consumption that would make an individual’s age more prominent in the decision to commit violent crime.

It could be that television representations of materialism and individualism have a greater impact on younger viewers, which is supported in other literature looking at the effects of media consumption violence, crime, and other risk-taking behaviors (see Kirsh 2011 for a synopsis). Thus, the relationship may exist because heavy television consumers are less likely to be influenced by television representations as they age.

The relationship between being in the “Other” racial category and violent behavior, which varies across television consumption, is in line with IAT. The “Other” race category likely includes many individuals who are foreign born or may be first or second generation immigrants. IAT contends that these individuals may be less affected by IAT, as the “American Dream” and the values associated with it may play less of a part in their socialization as children within their family. Television consumption may be transmitting the values identified by IAT causing high television consumers belonging to the “Other” racial category to have an increased likelihood of committing criminal behavior. It may be that television consumption has a greater impact on this group because of its potential to transmit the values of the “American Dream.” Alternatively, the difference could also be due to the “Other” group’s exposure to mediated violence, which is of course prevalent in American media representations.

Finally, being married reduces the odds of committing a violent crime differently across television consumption. While having no significant effect on heavy television

91 consumers, being married strongly decreased the odds of committing violent crime for low television viewers. Whereas other measures of the family, such as relationship with mother and father, and having children, have little effect on violent behavior, being married is a strong predictor of nonviolence for low media consumers. This suggests that television consumption moderates the relationship between being married and committing violent behavior. As hypothesized, this offers further evidence that media consumption may reduce the crime inhibiting effects of certain noneconomic institutions.

Testing for differences in the odds of committing all types of crime, the results again produce three significant differences across television consumption. As witnessed in the model for violent crime, age significantly reduces the odds of committing all types of crime for high media consumers, but not for low television consumers. Again, literature on the effects of the media suggests it has a greater influence on youth (Kirsh

2011), which could explain why age is more influential for heavy consumers. It is again important to recognize that age is truncated ranging from 25 to 34, which limits its variability.

Two noneconomic institutional variables are significantly different across media consumption, as education and marriage significantly reduce the odds of committing crime for low television consumers, but have no effect on high consumers. Both of these variables were significant in the other split models, suggesting that the relationship between them and criminal behavior by television consumption is fairly consistent. This finding offers further evidence that television consumption reduces the crime buffering influence provided by noneconomic institutions. Again, it may be that individuals who

92 consume heavy amounts of television are less likely to be influenced by noneconomic institutions like the family and education.

Summary of Hypotheses

Below each of the three major hypotheses are discussed based on the results above. While these do not represent the only significant contributions of this dissertation, they constitute its focus.

 Hypothesis 1: Television consumption will increase criminal behavior.

Hypothesis 1 was confirmed in all models. Television consumption had a significant and consistent positive relationship with criminal behavior across all media effect models.

For economic-based crime, violent crime, and general criminal behavior, consuming higher amounts of television throughout adolescence and into adulthood significantly increased the odds of committing all three types of crime. This relationship held true even while controlling for some of the most consistent and statistically relevant predictors of crime, such as prior crime, age, race, sex, and income.

 Hypothesis 2: In comparison to individuals who consume low levels of television,

heavy television consumers will be less influenced by noneconomic institutions to

abstain from criminal behavior.

Hypothesis 2 was partially supported based on the analysis above. Certain noneconomic variables did have significantly less of an impact on heavy television consumers than on light television consumers. Education decreased the likelihood that participants would commit both crimes of economic attainment and all types of crime for low television consumers, but had no effect on heavy consumers. This suggests that media consumption

93 moderates the relationship between education and crime. Further, being married significantly reduced the odds of respondents committing both a violent act and any type of criminal behavior. It may be that the effect of the noneconomic institution of the family, specifically being married, is nullified by heavy television consumption. These findings suggest that television consumption does reduce the crime curbing effect of certain noneconomic institutions. The effects of other noneconomic institutions were not significantly different across high and low television consumption.

 Hypothesis 3: In comparison to light television consumers, heavy television

consumers will have higher odds of committing criminal behavior regardless of

household income.

Heavy television consumers had higher odds of committing a crime of economic attainment than those who consumed lesser amounts of television. However, this is only true for economic based crime, as the effect of household income did not vary significantly by television consumption in the models for violent or general criminal behavior. IAT suggests that the more exposure to the values associated with the

“American Dream” the less an individual’s current income should matter, since everyone feels economic pressure. The “American Dream” promotes the idea that individuals can have a lot of money and possessions, but these are all relative. Someone else is always going to have more, so individuals are always going to want more. If our society is built on the idea that success is only achieved monetarily and by accumulating possessions, then they would not simply halt their pursuit. Going back to the sports analogy used by

Merton, if you are not winning then you are losing. As Messner and Rosenfeld (2001)

94 describe it, the “American Dream offers no final stopping point” and “it requires “never- ending achievement.” (70)

CHAPTER V

CONCLUSION

This study tested whether or not media consumption affects the tenets of

Institutional Anomie Theory. While there are multiple criminological theories that would benefit by taking into consideration the role of the media, I believe a specific critique of

IAT can be addressed through its application. As Jensen (2002) points out, the logic of

IAT is flawed if it cannot properly account for the way in which America’s cultural values are transmitted to individuals from all regions and backgrounds. Messner and

Rosenfeld (2001) recognize that the media is important in the transmission of these values, but they fail to discuss its role beyond this basic idea.

Mass media is a powerful institution. The effects of media messages have been studied and recognized for some time, beginning with the work of George Gerbner (1977,

1978, 1980) and his Cultivation Theory and the work of Albert Bandura (1961, 1963) on media consumption and adolescent violence. While early attempts to unravel the effects of media consumption have not been accepted without dissent, multiple lines of research exist that link media consumption to both behaviors and opinions (see Roberts and Doob

1990; Madriz 1997; Chiricos, Padgett, and Gertz 2000; Eschholz et al. 2002; Dowler

2003; Dowler and Zawilski 2007). However, studies of the media or even contemplation of its relationship with criminal behavior are rarely undertaken within “mainstream” criminology.

Perhaps the difficulty studying the media, the disagreements in the field about how influential it may or may not be, or just as a limitation of the scope of IAT, Messner and Rosenfeld did not fully integrate media consumption into their explanation of crime.

This is surprising given the cultural values that the theory identifies as critical to the creation and reinforcement of the “American Dream.” Messner and Rosenfeld (2001) believe that the values rooted in the “American Dream” lead to high levels of anomie.

Previous literature supports the idea that the promotion of these characteristics is embedded in media representations, providing evidence that the media is a major socializing agent in the transmission of these values.

As identified in the literature there are a number of existing studies that link the values associated with IAT and unethical behavior. For example, Buijen and Valkenburg

(2003) found that television consumption promoted materialist views in young viewers, an idea that is supported in earlier research as well (see Ward and Wackman 1971;

Churchill and Moschis 1979). In addition, television consumption has been linked to pro- capitalist views, like individualism and achievement orientation (Carlson 1993). These findings support the idea that media consumption universally spreads these values across all segments of society. While cultural values and beliefs vary significantly in different regions of the country, media messages are relatively consistent across these areas.

Not only does the mass media help to spread the cultural values identified by

Messner and Rosenfeld as key contributors to criminal behavior, but it likely affects the relationships between noneconomic institutions and criminal offending. If an individual is instilled with values that promote greed coupled with a diminished concern over ethical behavior in the pursuit of success (see Cullen et al. 2004), these may override messages

97 sent by noneconomic institutions. Specifically, individuals who consume heavy amounts of media and are more influenced by the “American Dream,” will be less influenced by crime-curbing institutions like religion, education, and the community.

IAT cannot fully explain the relationship between culture, institutions, and crime without first accounting for the role of the media. This research provided one test of the role that media consumption plays in IAT. The findings suggest that the effect of media consumption on crime and IAT is two-fold. First, media has an impact on criminal behavior because it promotes the values identified by IAT as leading to criminal behavior.

Second, media consumption diminishes the positive effects of noneconomic institutions, as it socializes viewers to chase the “American Dream” by “any means necessary.”

Summary of Findings

This study represents the first empirical application of the role media consumption plays in Institutional Anomie Theory. While limitations of the data make measuring the cultural dynamics identified by the theory impossible, based on previous research this study suggests that the media serves as a socializing agent that instills the

“American Dream” into its viewers. For this reason, this research tested for a relationship between the consumption of one particular medium (television consumption) and criminal behavior, arguing this relationship is at least partially due to the transmission of the cultural values identified. In addition, this research tests for the possibility of a moderating relationship between media consumption and crime, due to the media’s influence on the institutions identified by IAT.

Media effects

The findings suggest that television consumption significantly influences the odds of committing crimes of economic attainment, crimes of violence, and general criminal behavior. Watching an average of 5 additional hours of television over the life of the survey increases the odds of committing these crimes by an average of 8 to 9 percent.

The consistency of the results across the three dependent variables is particularly promising. The results hold even while controlling for the institutional variables deemed important by Messner and Rosenfeld (1994) and others who have tested IAT. In addition, this relationship was even significant while controlling for previous delinquent behavior, one of the strongest predictors of crime identified in criminological research. Controlling for previous crimes helps eliminate the possibility that the relationship between media consumption and crime is a spurious one. In other words, without controlling for previous criminality it could be argued that individuals who are predisposed to crime may be more attracted to media representations.

While it could be argued that the relationship between television consumption and criminal behavior is statistically weak, the direction and consistency of the relationship strengthens the likelihood that this represents a real and perhaps powerful relationship.

Due to the difficulties in studying media, it has been argued that finding statistical relationships between media consumption and any behavior or belief is difficult (Gerbner

1980; Callanan 2001; Rosenberger and Callanan 2011). Since everyone is exposed to media messages in some form, this and other studies are left measuring gradations in media consumption. As opposed to variables like income and educational attainment there is no pure zero, as individuals who have not been exposed to mass media

99 representations are rare and certainly not comparable to the average United States citizen.

Despite this, this study finds a significant and consistent relationship between media consumption and criminal behavior.

In relationship to IAT, this research suggests that the relationship between media consumption and criminal behavior is a result of media serving as one of the major socializing agents of the cultural values identified by Messner and Rosenfeld. As one would expect, if media representations are instilling consumers with these values then it would be correlated with criminal behavior. Since this is supported in the model, then the logic of IAT (see Figure 1) suggests that media consumption may also influence the institutional dynamics of the theory, as the cultural and institutional causes of crime are interrelated.

Moderating effects

This study tested for a possible moderating relationship between television consumption and criminal behavior by splitting the sample by high and low consumption, and then using the comparison of coefficients test to determine if the institutional variables affect the two groups differently. As Gerbner et al. (1980) believed, the influence of mass media takes place gradually over time and is only observable when looking at large differences in consumption. Taking this into account, television consumption was separated into just two categories. Further, this is done with a cumulative measure of media consumption that takes television viewing across the life of the study (14 years) into account. This helps to make the effects of television consumption more apparent.

100

The findings suggest that television consumption affects the relationships between

IAT’s institutional predictors and criminal behavior in a number of ways. Educational attainment and being married are significantly less likely to reduce the odds of committing criminal behavior for heavy television consumers across multiple dependent variables. This suggests that media consumption reduces the impact of these institutions on the odds of committing crime. It may be that heavy television consumers are less affected by these crime curbing factors, because they are more immersed in the cultural goals identified by the theory. Perhaps the “American Dream” overrides the effects of these institutions. This can greatly diminish their potential to curb criminal behavior, as even these historically crime reducing institutions become mechanisms by which individuals can chase the “American Dream.” For example, education becomes a means to attain higher paying jobs, politics is a tool to protect one’s financial gains, and the family’s primary function becomes financial support.

In support of IAT, household income had a significantly larger influence on the odds of committing economic-based crime for light compared to heavy television consumers. It may be that heavy television consumption overrides the effects of income, an argument similar to Messner and Rosenfeld’s (2013) explanation of white-collar crime. The pursuit of the “American Dream” has no apparent finish line, so it could be that individuals more immersed in its pursuit are unaffected by their financial state. In addition to household income, the relationship between prior delinquency and crimes of economic attainment is significantly different by television consumption. For individuals who consume high amounts of television, prior delinquency did not significantly

101 influence their odds of committing an economic-based crime. This may suggest that television consumption trumps the influence of even prior delinquency.

Limitations

The limitations of this dissertation research are primarily related to the availability of existing data. The ADD Health data set has a number of advantages; including its longitudinal nature, its large sample size, and its tremendous pool of available variables.

However, the data set was primarily collected on issues related to physical and mental health. The amount and the quality of measures related to criminal behavior, media consumption, and the cultural values described by IAT led to a number of limitations.

Perhaps the largest limitation of this research is the lack of measures for the cultural dynamics of IAT. The cultural values described by Messner and Rosenfeld account for half of their theoretical argument. Lacking a way to test for a relationship between media consumption and the cultural values described by IAT leaves me to make assumptions about how media influences these factors. As it stands, this dissertation tests only the institutional dynamics. There is a strong enough body of existing literature to assume a relationship between media consumption and the cultural dynamics of IAT; however, this study would greatly benefit from the inclusion of direct measures.

Within the study it is argued that all types of media consumption may influence crime and the tenets of IAT. It is likely that internet consumption, newspaper consumption, and other forms of media increase the strength of the “American Dream.”

All these media are used by companies to advertise goods, and most media formats likely reflect and reinforce the “American Dream.” However, this research only has data on television consumption, and lacks strong measures of other media. While I argue they

102 may all promote similar messages, previous research testing the effect of different types of media finds that they have a varying degree of impact on viewers (Dowler 2005,

Callanan and Rosenberger 2010, Rosenberger and Callanan 2011). Further, research suggests that the general cultivation theory is too broad, and careful examination of the types of media must be considered (Harmon 2001).

In addition to the lack of measures of different types of media, television consumption is measured generally by asking respondents how many hours they watch per week. This measure does not differentiate by the type of programming that individuals consume. For example, a person who consumes 8 hours of Fox News per day is coded the same as an individual who only watches PBS. This is problematic as different types of programming do not send viewers the same messages or impact viewers in the same way (Dowler 2002; Eschholz, Mallard, and Flynn 2004).

Additionally, different television networks will run different types of advertising and promote different types of lifestyles. While materialistic messages probably remain no matter the product being pushed, these may influence the viewers differently. Using general hours of television consumption in media research is not uncommon (Gerbner and Gross 1976; Gerbner et al. 1977; Gerbner et al. 1978), but the increase in cable television networks and their catering to specific groups, cause media messages to vary significantly by television network.

The findings presented in this dissertation suggest that there may be a causal relationship between media exposure and criminal behavior, which has important implications for IAT. However, it is important to note that the relationship between media consumption and criminal behavior could be spurious due to a number of

103 important factors that are correlated with both activities. In the next section, the possible role of low self-control in both attracting individuals to media consumption and crime is discussed. Beyond this, there are other factors that are unaccounted for that could explain this relationship. For example, the link between television consumption and criminal behavior could be related to social learning theories ideas on imitation. Research stemming from the work of Bandura, Ross, and Ross (1963) suggests that violent behavior in the media is imitated in real life by its consumers. Broadening this idea, television and other media outlets that provide graphic depictions of criminal behavior may be providing heavy viewers with the motivations and the techniques necessary to commit crime. In addition, other factors related to mental health, physical disabilities, and growing up in troubled families could account for both the increase in media consumption and criminal behavior. This represents a limitation of the research as these possibilities are not fully accounted for; however it is a limitation that can be addressed in future research.

Related to measurement issues, operationalizing macro-level noneconomic institutions at the micro-level and the skewness of the dependent variables led to two specific limitations. First, because the dependent variables were dichotomized valuable information on how media and institutions influence individuals with multiple offenses, compared to those who have committed only a few, is lost. Future research should test the hypotheses presented in this dissertation using a continuous measure of criminal behavior. Second, polity was measured using a question gauging whether or not the participant voting in the most recent presidential election. This is recognizably a weak measure of polity although it has been used in other studies of IAT (see Schoepfer 2004).

104

A stronger measure would have been involvement in community service, which ADD

Health does include. However, community service is strongly related to criminal behavior as it is commonly used as an alternative to fees and jail time by the courts.

ADD Health lacks an effective way to control for individuals who conduct this service voluntarily or involuntarily.

Finally, there are some limitations related to survey research and measuring crime in general. ADD Health was primarily collected using survey methodology when the participants were still in high school. While the study has a strong participation rate across the life of the data collection, it is likely that data collected on crime excludes

“serious” criminal offenders. Researchers argues that survey research primarily collects data on what is referred to as the “garden variety” criminal (Inciardi, Horowitz, and

Pottieger 1993), referring to an individual who may commit some minor crimes, but rarely involves themselves with serious criminal behavior. The vast majority of serious delinquent and criminal behavior is committed by a very small percentage of individuals and these “serious” criminals rarely take time to fill out surveys (Inciardi et al. 1993).

Future Research

The findings justify a number of future studies that aim to untangle the relationship between IAT and media consumption. First, it would be beneficial to repeat the study while overcoming the limitations identified above. Testing the hypotheses put forward in this research with measures for the cultural dynamics of IAT and with data that includes multiple types of media, and accounts for different programming within media outlets, will provide further knowledge of how the media influences crime and its role in

105

IAT. In addition to correcting these limitations, there are a number of avenues that are worth investigating in future research.

IAT is a macro-level theory often times tested by comparing the strength of institutions and their effect on crime rates across different nations (Messner and

Rosenfeld 1997; Savolainen 2000; Pratt and Godsey 2003). Future research should test the role of media on IAT cross-nationally. Media could be measured by corporate expenditures on advertisement across nations or data on the availability of certain types of media within a nation. This type of data should be readily available, as companies and research institutions track spending on advertisements. If the hypotheses supported in this research hold true when tested on the macro-level, high amounts of advertising expenditure should translate into higher crime rates and affect the vitality of noneconomic institutions.

The finding that media affects criminal behavior and the institutions identified by

IAT even while controlling for previous delinquency requires further investigation. Self- control theory represents perhaps the most dominant theory of criminal behavior in the field of criminology. Its basic premise is built on the idea that the propensity to commit crime is established early in life, believed to be the result of low self-control (see

Gottfredson and Hirschi 1990). Self-control theory suggests that, media consumption would have little effect on crime because self-control is established very early in life.

Thus, the relationship observed in this study may be related to individuals with low self

106 control being more attracted to television.5 Future research should control for the effect of self-control in the relationship between television consumption and crime.

While this study has helped to identify the role media plays in relationship to

IAT’s explanation of crime, further research is still needed. Correcting for limitations in the data will help to determine how different types of media affect both the institutional and cultural dynamics of the theory. While this study represents one of the few micro- level tests of IAT, future research could help to fully determine the utility of the theory at the individual-level. While this type of research is important, media consumption can and should also be tested on the macro-level, as I believe media consumption may work in similar ways cross-nationally. Future research should fully explore the role of media within the theory, and the implications media consumption has on IAT at all levels of investigation. Additionally, while this study represents an important test of IAT, its findings warrant further investigation into the role of media consumption on other theories of crime.

Implications for the Field of Criminology

In addition to having implications for Institutional Anomie Theory, this study has broader implications for the field of criminology. Mass media is often recognized as an important socializing institution, but is rarely included in studies of criminal behavior. It seems that studies linking media consumption to crime have been pushed to the fringe of criminology. Other institutions that occupy far less time in the individual’s life, such as religion or politics, have been thoroughly tested in relationship to crime. Studies like this

5 Analyses accounting for self-control have been conducted. Findings suggest that media consumption is an important predictor of serious criminal behavior even when accounting for low self-control.

107 provide support for the idea that media is important to the explanation of crime and may affect the relationship between criminal behavior and institutions like education, the economy, and the family.

This study is also unique because provides a micro-level analysis of a historically macro-level theory. This type of theoretical application is not often undertaken in criminological research (Muftic 2009). Macro-level theories often talk generally about characteristics held by large groups and nations, which perhaps causes scholars to lose sight of the fact that behaviors, values and norms, and other characteristics are ultimately held, produced, or acted out by individuals. Losing sight of this promotes a split in criminological research and criminological theories that does not need to exist, and perhaps is a detriment to the field. Merton (1938) the founder of both strain (micro-level) and anomie (macro-level) theories never intended that these two be separate, because he realized that both macro and micro-level factors contribute to crime. The work in this dissertation suggests that micro and macro theoretical integration may provide new insight into the existing explanations of crime.

Summary

Institutional Anomie Theory has much strength and has been supported in research testing its assumptions (Chamlin and Cochran 1995; Chamlin and Cochran

1997; Messner and Rosenfeld 1997; Hannon and Defronzo 1998; Savolainen 2000; Pratt and Godsey 2003; Stucky 2003; Maume and Lee 2003). While IAT has primarily been tested on the macro-level, studying cross-national differences in criminal offending, this research represents one of the first applications of the theory at the micro-level on serious forms of criminal behavior. Like all theories, there are a number of identifiable

108 weaknesses that have been pointed out in the literature. Perhaps one of the largest critiques comes from the work of Jensen (2002), who suggests IAT does not properly explain how the cultural values associated with the “American Dream” are transmitted

“universally” to all members of society. This dissertation represents a theoretical and empirical attempt to shed light on one possible mechanism transmitting these values: mass media. Findings suggest that not only is television consumption, one powerful medium, directly related to crime, but it has a moderating effect on criminal behavior through institutional variables identified by IAT as producing or inhibiting criminal behavior.

In summary, this research suggests that media consumption may be a driving force behind the reinforcement of the values associated with the “American Dream” and the dominance of the economic institution over all others. As hypothesized, heavy media consumers were more likely to commit all types of criminal behavior, and were less affected by the crime curbing influence of institutions such as education and the family.

Further research is needed to determine the full extent to which the media influences IAT.

The findings from this dissertation research support the idea that theoretical and empirical studies could improve our understanding of crime by considering the role of the media in committing criminal acts.

109

REFERENCES

Andrews, Donald and James Bonta. 2010. “Rehabilitating Criminal Justice Policy and Practice.” Psychology, Public Policy, and Law, 16(1): 39-55.

Bandura, Albert, Dorothea Ross, and Shelia A. Ross. 1961. “Transmission of Aggression through Imitation of Aggressive Models.” Journal of Abnormal and Social Psychology, 66(5): 575-582.

Bandura, Albert, Dorothea Ross, and Shelia A. Ross. 1963. “Imitation of Film-Mediated Aggressive Models.” Abnormal and Social Psychology, 66(1): 3-11.

Baumer, Eric P. and Regan Gustafson. 2007. “Social Organization and Instrumental Crime: Assessing the Empirical Validity of Classic and Contemporary Anomie Theories.” Criminology, 45(3): 617–663.

Bjerregaard, Beth and John Cochran. 2008. “A Cross-National Test of Institutional Anomie Theory: Do the Strength of other Social Institutions Mediate or Moderate the Effects of the Economy on the Rate of Crime?” Western Criminology Review, 9(1): 31-48.

Buijzen, Moniek. and Patti M. Valkenburg. 2003. “The Unintended Effects of Television Advertising: A Parent–Child Survey.” Communication Research, 30(5): 483–503.

Bureau of Justice Statistics. 2010. “Correctional Populations in the United States, 2010.” Retrieved May 20th, 2012 (http://bjs.ojp.usdoj.gov/index.cfm).

Bushman, Brad J. and L. Rowell Huesmann. 2001. “Effects of Televised Violence on Aggression.” Pp. 223-254 in Handbook of Children and the Media, edited by D. Singer and J. Singer. Thousand Oaks, CA: Sage Publications.

Batton, Candice and Gary Jensen. 2002. "Decommodification and Homicide Rates in the 20th-Century United States." Homicide Studies, 6(1): 6-38.

Callanan, Valerie J. 2005. Feeding the Fear of Crime: Crime-related Media and Support for Three Strikes. New York, NY: LFB Scholarly Publishing LLC.

Callanan, Valerie J. and Jared S. Rosenberger. 2011. “Media and Public Perceptions of the Police: Examining the Impact of Race and Personal Experience.” Policing and Society, 21(2): 167-189.

110

Cao, Liqun. 2004. “Is American Society More Anomic? A Test of Merton’s Theory with Cross National Data.” International Journal of Comparative and Applied Criminal Justice, 28(1): 17–31.

Carlson, James M. 1993. “Television viewing: Cultivating Perceptions of Affluence and Support for Capitalist Values.” Political Communication, 10(3): 243 – 257.

Chamlin, Mitchell B. and John K. Cochran. 1995. "Assessing Messner and Rosenfeld's Institutional Anomie Theory: A Partial Test." Criminology, 33(3): 411-429.

Chamlin, Mitchell B. and John K. Cochran. 2007. "An Evaluation of the Assumptions That Underlie Institutional Anomie Theory." Theoretical Criminology, 11(1): 39- 61.

Chiricos, Ted, Kathy Padgett, and Marc Gertz. 2000. "Fear, TV News, and the Reality of Crime." Criminology, 38(3): 755-785.

Churchill, Gilbert A. and Ceorge P. Moschis. 1979. “Television and Interpersonal Influences on Adolescent Consumer Learning.” Journal of Consumer Research, 6(1): 23-35.

Comstock, George. 1980. “New Emphases in Research on the Effects of Television and Film Violence.” Pp. 129 -148 in Children and the faces of Television: Teaching, Violence, Selling, editing by E.L. Palmer and A. Dorr. New York: Academic Press.

Cullen, Francis T. and Robert Agnew. 2006. Criminological Theory: Past to Present. 3rd Edition. New York: Oxford University Press.

Cullen, John B., K. Praveen Parboteeah, and Martin Hoegl. 2004. “Cross-National Differences in Managers’ Willingness to Justify Ethically Suspect Behaviors: A Test of Institutional Anomie Theory." Academy of Management Journal, 47(3): 411-421.

Dowler, Kenneth. 2003. “Media Consumption and Public Attitudes toward Crime and Justice: The Relationship between Fear of Crime, Punitive Attitudes, and Perceived Police Effectiveness.” Journal of Criminal Justice and Popular Culture, 10(2): 109-126.

Dowler, Kenneth and Valerie Zawilski. 2007. "Public Perceptions of Police Misconduct and Discrimination: Examining the Impact of Media Consumption." Journal of Criminal Justice, 35(2): 193-203.

Eschholz, Sarah, Brenda S. Blackwell, Marc Gertz and Ted Chiricos. 2002. "Race and Attitudes toward the Police. Assessing the Effects of Watching 'Reality' Police Programs." Journal of Criminal Justice, 30(4):327-341.

111

Farrington, David P. and Rolf Loeber. 2000. “Some Benefits of Dichotomization in Psychiatric and Criminological Research.” Criminal Behaviour and Mental Health, 10(2): 100-122.

Federal Bureau of Investigation. 2009. Crime in the United States. Retrieved May 22, 2012 (http://www2.fbi.gov/ucr/cius2009/index.html).

Gerbner, George. 1973. “Cultural Indicators: The Third Voice.” Pp. 555-573 in Communication Technology and Social Policy, edited by G. Gerbner, L. Gross, and W.H. Melody. New York: Wiley.

Gerbner, George. 1998. “Cultivation Analysis: An overview.” Mass Communication and Society, 1(3/4): 175-194.

Gerbner, George and Larry Gross. 1976. “Living with Television: The Violence Profile.” Journal of Communication, 26(2): 172-194.

Gerbner, George, Larry Gross, M.F. Eleey, M. Jackson-Beeck, S. Fox, and Nancy Signorielli. 1977. “TV Violence Profile No. 8: The Highlights.” Journal of Communication, 27(2): 71-180.

Gerbner, George, Larry Gross, M. Jackson-Beeck, S. Jefferies-Fox, and Nancy Signorielli. 1978. “Cultural Indicators: Violence profile, No. 9.” Journal of Communication, 28(3): 176-207.

Gerbner, George, Larry Gross, Michael Morgan, and Nancy Signorielli. 1980. “The “Mainstreaming” of America: Violence Profile No. 11.” Journal of Communication, 30(3):10-29.

Gerbner, George, Larry Gross, Michael Morgan, and Nancy Signorielli. 1986. “Living with Television: The Dynamics of the Cultivation Process.” Pp. 17-40 in Perspective on Media Effects, edited by J. Bryant and D. Zillmann. Hillsdale, NJ: Lawrence Erlbaum.

Gordon, Milton M. 1947. “The Concept of the Sub-Culture and Its Application.” Social Forces, 26(1): 40-42.

Gottfredson, Michael and Travis Hirschi. 1990. A General Theory of Crime. Stanford: Stanford University Press.

Hannon, Lance and James Defronzo. 1998. “The Truly Disadvantaged, Public Assistance, and Crime.” Social Problems, 45(3): 383-392.

Hearold, S. 1986. “A Synthesis of 1043 Effects of Television on Social Behavior.” Pp. 65-133 in Public Communication and Behavior, edited by George Comstock. Orlando, FL: Academic Press.

112

Heitner, Darren. 2013. “Is it Worth Spending $4 Million On a Super Bowl Commercial.” Forbes, January 2013.

Hirschi, Travis. 1969. Causes of Delinquency. Berkeley: University of California Press.

Hochschild, Jennifer L. 1996. Facing up to the American Dream: Race, Class, and the Soul of the Nation. Princeton, NJ: Princeton University Press.

Hochschild, Jennifer L. and Nathan Scovronick. 2004. The American Dream and Public Schools. New York: Oxford University Press.

Hughes, Michael. 1980. “The Fruits of Cultivation Analysis: A Reexamination of Some Effects of Television Watching.” Public Opinion Quarterly, 44(3): 287-302.

Inciardi, James, Ruth Horowitz, and Anne Potteiger. 1993. Street Kids, Street Drugs, Street Crime: An Examination of Drug Use and Serious Delinquency in Miami. Belmont, CA: Wadsworth.

Interpol. 2007. “Interpol News.” Retrieved May 18, 2012 (www.interpol.int/news/news2009.asp)

Jaffee, Sara R., Avashalom Caspit, Terry E. Moffitt, Alan Taylor, and N. Dickson. 2001. “Predicting Early Fatherhood and Whether Young Fathers Live with Their Children: Prospective Findings and Policy Considerations.” Journal of Child Psychology and Psychiatry, 42(6): 803-815.

Jensen, Gary. 2002. “Institutional Anomie and Societal Variations in Crime: A Critical Appraisal.” International Journal of Sociology and Social Policy, 22(1): 45–74.

Karstedt, Susanne and Stephen Farrell. 2006. “The Moral Economy of Everyday Crime: Markets, Consumers, and Citizens.” British Journal of Criminology, 46(6): 1011– 1136.

Kirsh, Steven J. 2011. Children, Adolescents, and Media Violence. Los Angeles, CA: Sage.

Lambert, Diane. 1992. “Zero-Inflated Poisson Regression, with an Application to Defects Manufacturing.” Technometrics, 34(1): 1 -14.

Madriz, Esther. 1997. “Nothing Bad Happens to Good Girls: Fear of Crime n Women's Lives.” Berkeley: University of California Press.

Maume, Michael O. and Matthew R. Lee. 2003. “Social Institutions and Violence: A Sub-National Test of Institutional Anomie Theory.” Criminology, 41(4): 1137- 1172.

113

McClendon, McKee J. 2002. Multiple Regression and Causal Analysis. Prospect Heights, IL: Waveland Press.

McClosky, Herbert and John Zaller. 1984. The American ethos. Cambridge: Harvard University Press.

Meloy, Mike. 2009. “From Kid Nation to Caste Nation: Mobility, Privilege, and the Paradox of Class on Reality Television.” The Journal of American Popular Culture, 8(1).

Merton, Robert K. 1938. “Social Structure and Anomie.” American Sociological Review, 3(5): 672-682.

Messner, Steven F. 1988. “Merton’s ‘Social Structure and Anomie’: The Road not Taken.” Deviant Behavior, 9(1): 33–53.

Messner, Steven F. and Richard Rosenfeld. 1997. “Political Restraint of the Market and Levels of Criminal Homicide: A Cross-National Application of Institutional- Anomie Theory.” Social Forces, 75(4): 1393–1416.

Messner, Steven F. and Richard Rosenfeld. 1994. Crime and the American Dream, 1th ed. Belmont: Wadsworth.

Messner, Steven F. and Richard Rosenfeld. 2001. Crime and the American Dream, 3th ed. Belmont: Wadsworth.

Messner, Steven F. and Richard Rosenfeld. 2007. Crime and the American Dream, 4th ed. Belmont: Wadsworth.

Messner, Steven F. and Richard Rosenfeld. 2010. “The Present and Future of Institutional Anomie Theory.” Pp. 127-148 in Taking Stock: The Status of Criminological Theory. Vol. 16 of Advances in Criminological Theory, edited by F.T. Cullen, J.P. Wright, and K.R. Blevins. New Brunswick: Transaction.

Messner, Steven F. and Richard Rosenfeld. 2013. Crime and the American Dream, 5th ed. Belmont: Wadsworth.

Messner, Steven F., Helmut Thome, and Richard Rosenfeld. 2008. “Institutions, Anomie, and Violent Crime: Clarifying and Elaborating Institutional-Anomie Theory.” International Journal of Conflict and Violence, 2(2): 163–181.

Muftic, Lisa R. 2006. “Advancing Institutional Anomie Theory: A Microlevel Examination Connecting Culture, Institutions, and Deviance.” International Journal of Offender Therapy and Comparative Criminology, 50(6): 630–653.

114

Muftic, Lisa R. 2009. “Macro-Micro Theoretical Integration: An Unexplored Theoretical Frontier.” Journal of Theoretical and Philosophical Criminology, 1(2): 33-71.

National Institute of Child Health and Human Development. 2012. “ADD Health Study.” Retrieved July 30, 2012 (http://www.nichd.nih.gov/health/topics/add_health_study.cfm).

Nielsen Company (2013). State of the Media: U.S. Consumer Usage Report 2012. Retrieved January 13, 2013 (http://www.nielson.com).

Paik, Haejung and George Comstock (1994). “The Effects of Television Violence on Antisocial Behavior: A Meta-Analysis.” Communication Research, 21(4): 516- 546.

Paternoster, Raymond, Robert Brame, Paul Mazerolle, and Alex Piquero. 1998. “Using the Correct Statistical Test for the Equality of Regression Coefficients.” Criminology, 36(4): 859-866.

Perrone, Dina, Christopher J. Sullivan, Travis C. Pratt, and Satenik Margaryan. 2004. “Parental Efficacy, Self-Control, and Delinquency: A Test of a General Theory of Crime on a Nationally Representative Sample of Youth.” International Journal of Offender Therapy and Comparative Criminology, 48(3): 298–312.

Piquero, Alex and Nicole Leeper Piquero. 1998. "On Testing Institutional Anomie Theory with Varying Specifications." Studies on Crime and Crime Prevention, 7(2): 61-84.

Piquero, Alex R. and Stephen G. Tibbetts. 1996. “Specifying the Direct and Indirect Effects of Low Self-Control and Situational Factors in Decision Making: Toward a More Complete Model of Rational Offending.” Justice Quarterly, 13(3): 481– 510.

Pratt, Travis C. and Timothy W. Godsey. 2002. “Social Support and Homicide: A Cross- National Test of an Emerging Criminological Theory.” Journal of Criminal Justice, 30(6): 589–601.

Pratt, Travis C. and Timothy W. Godsey. 2003. "Social Support, Inequality, and Homicide: A Cross-National Test of an Integrated Theoretical Model." Criminology, 41(3): 611-643.

Roberts, Julian V. and Anthony N. Doob. 1990. "News Media Influences on Public Views of Sentencing." Law & Human Behavior, 14(5): 451-458.

Rosenberger, Jared S. and Valerie J. Callanan. 2011. “The Influence of Media on Penal Attitudes.” Criminal Justice Review, 36(4): 435-455.

115

Rosenfeld, Richard. 1989. "Robert Merton's Contributions to the Sociology of Deviance." Sociological Inquiry, 59(4): 453-466.

Savolainen, Jukka. 2000. “Inequality, Welfare State, and Homicide: Further Support for the Institutional Anomie Theory.” Criminology, 38(4): 1021–1042.

Schoepfer, Andrea. 2004. “Exploring White-Collar Crime and the American Dream.” Graduate Thesis: The University of Florida.

Schoepfer, Andrea and Piquero, Nicole L. 2006. “Exploring White-Collar Crime and the American Dream: A Partial Test of Institutional Anomie Theory.” Journal of Criminal Justice, 34(3): 227-235.

Sellers, Christine S. 1999. “Self-Control and Intimate Violence: An examination of the scope and specification of the general theory of crime.” Criminology, 37(2): 375– 404.

Shanahan, James and Michael Morgan. 1999. Television and its Viewers: Cultivation Theory and Research. Cambridge, UK: Cambridge University Press.

Shrum, L. J., Jaehoon Lee, James E. Burroughs, and Aric Rindfleisch. 2010. “An Online Process Model of Second-Order Cultivation Effects: How Television Cultivates Materialism and its Consequences for Life Satisfaction.” Human Communication Research, 37(1): 34-57.

Signorielli, Nancy and Michael Morgan. 2008. “Cultivation Analysis: Research and Practice.” Pp. 106-125 in An Integrated Approach to Communication Theory and Research, edited by Michael Salween. New York: Routledge.

Strasburger, Victor C. 1995. Adolescents and the Media. Thousand Oaks, CA: Sage.

Stucky, Thomas D. 2003. "Local Politics and Violent Crime in U.S. Cities." Criminology, 41(4): 1101-1135.

Surette, Ray. 1998. Media, Crime, and Criminal justice: Images, Realities, and Policies. Belmont, CA: Thomson Wadsworth.

Tonry, Michael. 1999. “Why are U.S. Incarceration Rates so High?” Crime and Delinquency, 45(4): 419-37.

Television Bureau of Advertising. 2012. Ad Spending (Full Year 2010-11). Retrieved May 28, 2012 (http://www.tvb.org/trends/898295).

United Nations Office on Drugs and Crime. 2011. Global Study on Homicide. Vienna: UNODC Publishing.

116

United Nations Office on Drugs and Crime. 2002. Statistics on crime and the criminal justice system. Retrieved May 23, 2012 (http://www.unodc.org/documents/southeasterneurope /Doc_4_Eurostat_Offence_Definitions_and_Explanatory_Notes_2002.pdf).

Veall, Michael R. and Klaus F. Zimmermann. 2006. “Pseudo-R2 Measures for Some Common Limited Dependent Variable Models.” Journal of Economic Surveys, 10(3): 241–259.

Ward, Scott and Daniel Wackman. 1971. “Family and Media Influences on Adolescent Consumer Learning.” American Behavioral Scientist, 14(3): 415-427.

Ybarra, Michele L., Marie Diener-West, Dana Markow, Philip J. Leaf, Merle Hamburger, and Paul Boxer. 2008. “Linkages between Internet and Other Media Violence with Seriously Violent Behavior by Youth.” Pediatrics, 122(5): 929-937.

117

APPENDICES

118

APPENDIX A

DATA SOURCES

Data collection dates. a Wave Year Collected Wave I 1994 - 1995 Wave II 1996 Wave III 2001 - 2002 Wave IV 2007 - 2008

a Harris, Kathleen Mullan, and J. Richard Udry. National Longitudinal Study of Adolescent Health (Add Health), 1994-2008. ICPSR21600-v11. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2012-11-01. doi:10.3886/ICPSR21600.v11

119

APPENDIX B

MEASUREMENT

Questions used to create variable Crimes of Economic Attainment

120

APPENDIX C

MEASUREMENT

Questions used to create variable Crimes of Violence

Question Range Mean SD In the past 12 months, how often did you take part in a physical 0 - 3 .04 .22 fight where a group of your friends was against another group? In the past 12 months, how often did you get into a serious 0 - 3 .06 .27 physical fight? In the past 12 months: You shot or stabbed someone? 0 -1 .01 .11 In the past 12 months: You pulled a knife or gun on someone? 0 - 1 .03 .16

121

APPENDIX D

MEASUREMENT

Questions used to create variable All Criminal Behavior

Question Range Mean SD In the past 12 months, how often did you steal something worth 0 - 3 .02 .18 more than $50? In the past 12 months, how often did you go into a house or 0 - 3 .01 .13 building to steal something? In the past 12 months, how often did you use or threaten to use 0 -3 .01 .14 a weapon to get something from someone? In the past 12 months, how often did you sell marijuana or 0 - 3 .09 .47 other drugs? In the past 12 months, how often did you steal something 0 - 3 .05 .29 worth less than $50? In the past 12 months, how often did you buy, sell, or hold 0 - 3 .03 .22 stolen property? In the past 12 months, how often did you use someone else's 0 - 3 .01 .12 credit card, bank card, or automatic teller card without their permission or knowledge? In the past 12 months, how often did you deliberately write a 0 - 3 .03 .20 bad check? In the past 12 months, how often did you take part in a physical 0 - 3 .04 .22 fight where a group of your friends was against another group? In the past 12 months, how often did you get into a serious 0 - 3 .06 .27 physical fight? In the past 12 months: You shot or stabbed someone? 0 -1 .01 .11 In the past 12 months: You pulled a knife or gun on someone? 0 - 1 .03 .16 In the past 12 months, how often did you deliberately damage 0 - 3 .05 .25 property that didn't belong to you?

122

123