©2011

Beth Adubato

ALL RIGHTS RESERVED

FANNING THE FLAMES: TELEVISED, PROFESSIONAL FOOTBALL GAMES AND DOMESTIC VIOLENCE by Beth Adubato

A Dissertation submitted to the Graduate School-Newark, Rutgers, The State University of New Jersey in partial fulfillment of the requirements for the degree of Doctor of Philosophy Graduate Program in Criminal Justice written under the direction of Dr. Ronald Clarke and approved by

______Dr. Ronald Clarke (chair)

______Dr. James Finckenauer

______Dr. Joel Miller

______Dr. Paul Boxer (outside reader)

Newark, New Jersey May 2011 ABSTRACT Fanning the Flames: Televised, Professional Football Games and Domestic Violence

Dissertation Director: Dr. Ronald Clarke

Images of athletes as criminal suspects seldom shock society; newspapers run “police blotters” in their sports sections. “Doping” presents a serious problem among Olympians, professional team players, and even cyclists of the Tour de France. Sports fans across Europe, Asia, and South America have wreaked deadly havoc on each other after soccer matches. With all of these obvious associations, criminology still lags behind psychology in the inclusion of the study of sports within its purview. Throughout the rest of the world, much of the sports/crime focus is on the fans—so-called “hooliganism.” This dissertation attempts to address a sports/crime issue in the United States, while largely availing itself of these European hooligan studies. The issue at-hand is whether televised, professional, American football games affect domestic violence. The purpose of this study is to not only examine possible correlation between these two events in one geographical area (namely Philadelphia), but further, to possibly influence sports/crime study in the field of American criminology. A good deal of research into “hooliganism” attributes the behavior to the concept of BIRGing or “Basking in Reflected Glory.” This concept provides much insight into the “highly-identified” sports fan. It is these highly-identified sports fans that this dissertation presumably examined. Most specifically, does the highly-identified sports fan feel a strong bond with his favorite football players and imitate their behavior? Do televised football games bring about copycat, violent behavior? Using the copycat framework, this dissertation research looked at domestic violence arrests in the city of Philadelphia on the days that Eagles games were played, for an eight-hour period, beginning with kick-off time. These relationships were tested using comparison of means tests—both the Levene test and the Mann-Whitney tests. As predicted, there was no difference between the mean average of holidays and football gamedays, This hypothesis was specifically designed to compare football gamedays to those days highly-connected to alcohol consumption. Also as predicted, there was no statistically significant difference between home games and away games, taking away the possible bias that fans were at the game and then became violent, as opposed to watching the game on television. The mean average of domestic violence arrests on football was statistically significantly different from both comparison Sundays and other sports’ gamedays. This study could be expanded to include more years and/or replicated in another city. This study addresses the media hype and misconceptions surrounding football and domestic violence and challenges criminology to expand its field to include sports and crime.

ii ACKNOWLEDGMENTS

I would like to thank the members of my committee for their insight and guidance—my outside reader from psychology, Paul Boxer, who has conducted much research on the effects of media and violence…Joel Miller, who enlightened me on the statistical parts of this study and also contributed to the theoretical portion…James

Finckenauer, who has an uncanny ability to clearly point-out the unclear and who showed great enthusiasm for the topic, as the one actual sports fan on the committee…and my chair, Ronald Clarke, who helped me to form this study from its complicated roots, to cull the unnecessary from the literature review, who painstakingly went through every word and showed me how journalistic writing differs from academic writing, and who helped me to see the error of my ways in table-making.

I also wish to thank Corporal Len DeMalto of the Research and Planning Unit of the Philadelphia Police Department, without whose patient help this study would not have been possible. Special thanks should be given to my student colleagues who helped me in many, invaluable ways. Also deserving of praise are the students who have taken my classes over the years, as they have taught me much.

Finally, I would like to thank my family for supporting me in

iii

TABLE OF CONTENTS Summary—p. viii

Introduction—p. 7 --Genesis of Study --Most Dangerous Day of the Year—p. 8

CHAPTER I--Sports and Crime—p. 10 --Frenzy—p. 11 --Fans—p. 14 --Social Identity—p. 16 --Team Identification—p. 23 --NFL BIRGing—p. 25 --Sports Fans: The Numbers—p. 27 --Machismo—p. 27 --Hooliganism—p. 30 --Spectator Violence in North America—p. 34 --Self-Reported Spectator Violence—p. 34 --The Promise of Violence—p. 35 --Superstars—p. 36 --Out of Bounds—p. 37 --Chapter Summary—p. 40

CHAPTER II--Media and Crime—p. 42 --Studies on Effects of Violent Media—Television—p. 42 --Effects on Children—p. 43 --Making the Case for Media and Aggression—p. 44 --More Violent Visuals—p. 47 --Video Games—p. 49 --Chapter Summary—p. 51

CHAPTER III—Domestic Violence—p. 53 --What is Domestic Violence?—p. 53 --Pros and Cons—p. 56 --“Go O.J. Go!”—p. 59 --Domestic Violence in Philadelphia—p. 60 --Chapter Summary—p. 60

CHAPTER IV—Previous Studies—p. 62

iv --Football and Fan-Aggression Studies—p. 62 --Advantages and Limitations—p. 67 --Additional Limitations and Advantages—p. 70 --Chapter Summary—p. 71

CHAPTER V—Theoretical Framework—p. 72 --Copycat Crime/Media Violence Framework —p. 77 --Copycat Research—p. 79 --Mechanism—p. 80 --Hypotheses—p. 83 --Theoretical Framework/Flowchart—p. 84 --Chapter Summary—p. 85

CHAPTER VI—Methods—p. 86 --Research Design—p. 86 --Sample—p. 88 --Sample Limitations—p. 89 --Data—p. 90 --Data Sets—p. 91 --Measures—p. 93 --Analysis Plan—p. 95 --Chapter Summary—p. 96

CHAPTER VII—Results—p. 98 --Findings—p. 98 --Additional Findings—p. 118 --Chapter Summary—p. 122

CHAPTER VIII—Discussion—p. 123 --Introduction—p. 123 --Wins vs. Losses—p. 124 --Rivals and Playoffs—p. 125 --Home vs. Away—p. 125 --Holidays—p. 126 --Football Compared to Other Major Sports—p. 127 --Football Gamedays vs. the Average Sunday—p. 129 --Domestic Rape—p. 130 --Chapter Summary—p. 130

CHAPTER IX—Conclusion—p. 132 --Summary of Findings—p. 132 --Theoretical Implications—p. 133 --Findings and Theory—p. 136 --Branches of the Flowchart—p. 136

v --Policy Implications—p. 138 --Alternative Explanations/Future Studies—p. 141 --Conclusion—p. 147

Bibliography—p. 151

Appendix—p. 163 --Data Charts—p. 163 --SPSS results—p. 169 --Fact sheet for Governor Rendell—p. 192 --Domestic Crime Incidents for 2009 by Code, Time and Day—p. 194

Curriculum Vitae—p. 197

TABLES

Table 1 “Media Generated Crime”—p. 76 Table 2 “Designing Out Biases”—p. 82 Table 3 “Philadelphia Football Game Days”—p. 93 Table 4 “Descriptive Statistics for Domestic Violence Arrests”—p. 94 Table 5 “Descriptive Statistics by Comparison Groups”—p. 95 Tables 6-33—Tables for each statistical test run for each comparison group—pages 96-115.

vi

SUMMARY Images of athletes as criminal suspects seldom shock society; newspapers run “police blotters” in their sports sections in a matter-of-fact manner. “Doping” presents a serious problem among Olympians, professional team players, and even cyclists of the Tour de France. Sports and crime are no strangers to each other; for example, sports and crime intersect with illegal betting. Cheating is often discovered during the Olympics— our planet’s most noble and all-encompassing goodwill event. Sports fans across Europe, Asia, and South America have wreaked deadly havoc on each other after soccer matches. With all of these obvious associations, criminology still lags behind psychology in the inclusion of the study of sports within its purview. In the United States, the crimes athletes are accused of range from public fighting to domestic violence to rape and murder. Throughout the rest of the world, much of the sports/crime focus is on the fans—so-called “hooliganism.” It is in the area of hooliganism studies that criminology addresses sports and crime most prominently. This dissertation attempted to address a sports/crime issue in the United States, while largely availing itself of these European hooligan studies. The issue at-hand is whether televised, professional, American football games affect domestic violence. The purpose of this study is to not only examine possible correlation between these two events in one geographical area (namely Philadelphia), but further, to influence sports/crime study in the field of criminology. Like the already “established” areas such as “gender and crime,” and “race and crime,” sports and crime needs to become a much more salient area of criminology. A good deal of research into “hooliganism” attributes the behavior to the concepts of BIRGing and CORFing; these acronyms stand for “Basking in Reflected Glory” and “Cutting Off Reflected Failure.” These concepts provide much insight into the “highly- identified” sports fan (as opposed to the casual fan). It is these highly-identified sports fans that this dissertation examines. Most specifically, does the highly-identified sports fan feel a strong bond with his favorite football players and imitate their behavior? Do televised football games bring about copycat, violent behavior?

vii Ray Surette—one of the few researchers in the field of criminology to study copycat crimes—states that the anecdotal cases in combination with research on media- copied suicides and studies of the effects of news coverage “establish reasonable grounds that copycat crimes occur, but at an unknown rate” (2002). In the copycat crime literature, Wilson and Herrnstein (1985) implicated media consumption with low academic achievement, as related to media-induced juvenile criminality. Heller & Polsky (1976) and Pease & Love (1984a, 1984b) suggested that “offenders who held attitudes toward the media as useful and influential would be associated with copycat behaviors.” Most importantly, with the mechanism being social learning, the emergence of an effect depends on the interaction between each individual, the content of the media, and the setting in which exposure occurs (Surette, 2002). Using the copycat framework, this dissertation research looks at domestic violence arrests in the city of Philadelphia on the days that Eagles games were played, for an eight-hour period, beginning with kick-off time. Also included in football gamedays were Super Bowl Sunday and the Pro Bowl bringing the sample to 20. These arrests numbers were the dependent variable for the following hypotheses:

HypothesisA: During the 8-hour period following “kick-off” on a televised Philadelphia Eagles game, domestic violence arrests will be greater than the average number of arrests for day of the week and time of day, for the calendar year of 2009. HypothesisB: Domestic violence arrests will be equal following Eagles home games and away games. HypothesisC: Domestic violence arrests will be greater following wins than losses. HypothesisD: Domestic violence arrests will be greater following games vs. rivals than following games vs. average opponents. HypothesisE: Domestic violence arrests will be greater following playoff games than following regular-season games. HypothesisF: Domestic violence arrests will be equal to the number of arrests on a holiday associated with socializing and the drinking of alcoholic beverages. HypothesisG: Domestic violence arrests will be greater following football games than followinghockey, basketball, and baseball games.

These relationships were tested using comparison of means tests—both a parametric t-test and the nonparametric Mann-Whitney U tests. Hypotheses C, D, E were

viii not confirmed. There was no statistical significance between wins and losses, rivals and non-rival games, and playoff and regular games. Hypotheses A, B, E, and F were confirmed. One unexpected result from the data was the finding that hockey gamedays (n=7)—when segregated from the other two sports—showed no difference of means in DV arrests. In conclusion, this study found that football gamedays are more highly associated with domestic violence than basketball and baseball and than the average Sunday in Philadelphia. Additionally, the tests showed support for the media/copycat theory in that home games did not produce more DV arrests. This study could be expanded to include more years and/or replicated in another city. Further study is also warranted by the small but intriguing subset of hockey games. While this was not hypothesized in this study, it is not entirely unexpected, as both football and hockey are considered violent, combative sports (McDaniel et al., 2007). This study may be able to illuminate a sociological phenomenon that carries with it much media hype and misconception. It could also lead to policy that would perhaps ameliorate this pernicious problem. Finally, it may help to bring a new area of study to the criminological field.

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x 1

INTRODUCTION

GENESIS OF STUDY

It is commonly believed among employees of television news affiliates that domestic violence calls-for-service increase in the aftermath of a “major” local sporting event. Police officers—at least those in the city of Philadelphia in which this research was conducted—believe it, too (Corporal DeMalto, Personal Interview, January 2010).

This belief is not random or based on hearsay, but based on the experience of these employees.

In every television news station, police scanners are activated 24-hours per day, seven days per week. Assignment desk editors and producers listen to these scanners, as it is their job to direct reporters to breaking news stories. Every police call is scrutinized for their “newsworthiness.” Small accidents and minor break-ins are not covered by local news reporters, but neither are rape calls or those for domestic violence. Like suicides of non-celebrities, these criminal events simply are not covered.

Although news crews are not sent to cover these certain stories, every police call is assessed and therefore, leaves an impression on those within earshot. During the busy

(and noisy) news day, many calls are heard only by the employees of the desk. During the overnight shifts, however, when many of these domestic and rape calls come in, the quiet of the newsroom allows all those working to hear the calls.

The idea for this study stemmed from this form of “street knowledge” and is therefore a product of grounded theory. The researcher of this dissertation began the study of criminal justice after six years of working as a television news reporter and this 2 study sprang from the desire to see if the general knowledge of the newsroom could hold up to vigorous statistical testing.

MOST DANGEROUS DAY OF THE YEAR

A “google search” on domestic violence and football will yield over three million

“hits.” An Internet site devoted to verifying or debunking myths—snopes.com—sums up its response by flatly calling the subject an urban legend. The site says in essence that calling Super Bowl Sunday the most dangerous day of the year is a myth. This statement unfortunately dismisses as myth an extremely complicated and dangerous topic. It is reflective of a frustration that researchers in social science face that perhaps researchers in the natural sciences do not—the topics are readily available to the public and are, therefore, vulnerable to uneducated scrutiny. Additionally, football’s popularity is so widespread and overwhelming that this concept seems like an assault on a sacred cow, an assault on the American way. Football is perceived to be as wholesome and American as apple pie and only those who truly hate America (or in this case, American men) could suggest that it carries a deleterious effect.

In 1992, White, Scarborough and Garland presented the results of their study on football and hospital trauma admissions in northern Virginia in a panel discussion to the

American Society of Criminologists. Somehow, the results of their study—which showed a percentage increase in admissions during Washington Redskins’ win, but was only “close” to statistical significance—leaked to the mainstream media (Katz & White,

1993). What the researchers experienced after that would be called a blitz in the parlance of American football. 3

Although they were experienced researchers and academics, they were unused to the wiles of the media. When asked about their study in countless interviews, they wavered in their responses—not able to explain to reporters the difference between a percentage increase and statistical significance. They were labeled frauds and their study was ridiculed. Both the initial study and the complete character assassination of the researchers were major news stories for a couple of months. The authors received “10 to

15 calls an hour” (Katz & White, 1993, p. 2) just five days before the Super Bowl. Every major media outlet took a position on these criminologists and their work was eventually cast aside as feminist, anti-football nonsense. The experience was so jolting for the researchers that the published an article that solely addressed the media aftermath of their

1992 study and the backlash that condemned their work.

Two days before the Super Bowl in 2011, the Philadelphia Police Department held a press conference for news crews in Pennsylvania and New Jersey, announcing that

“there may or may not be a link between football and domestic violence, but let’s just all try to stay calm” (Personal Interview, Phil Johnson, February 6, 2011).

Part of the urban myth emanates from the leaking of half-truths and the ability to then decry legitimate research. No researchers claimed that Super Bowl Sunday is the most dangerous day of the year, but the media took up that catch-phrase. Phrasing it so simply makes it all-the easier to yell “Fraud!” without considering the merit of the research. It is the hope of this researcher that this dissertation will add to both the criminological field and public discourse.

4

CHAPTER I--SPORTS AND CRIME

As the relatively young field of criminal justice continues to grow, new areas of focus spring up and become part of the bounty of knowledge. Surprisingly, however, one area that is under-explored is that of “sports and crime.” Perhaps it is the unconscious, underlying supposition that sports participation and appreciation are a healthy, human expression that precludes criminologists from considering sports and crime as a major area of focus? Clearly, however, sports and crime are common bedfellows.

Sports and crime intersect with illegal sports betting. “Doping” presents a serious problem among Olympians, professional team players, and apparently cyclists of the

Tour de France. Cheating is often discovered during the Olympics—our planet’s most noble and all-encompassing goodwill event.

Regarding violent crime, sports is certainly connected. In the United States, it is a common occurrence that an athlete is accused of a crime. The more successful and wealthy the athlete, the more media attention is given to the accused, but newspapers— both local and national—contain stories of “athlete suspects” from Tiger Woods to unknown high school players. The crimes range from public fighting to domestic violence to rape and murder. In Europe, Asia, and South America, much of the sports/crime focus is on the fans—so-called “hooliganism.” It is in the area of hooliganism studies that criminology addresses sports and crime most prominently.

This dissertation will address a sports/crime issue in the United States, while largely availing itself of these European hooligan studies. The issue at-hand is whether televised, professional, American football games affect domestic violence. The purpose of this dissertation is to not only examine possible correlation between these two classes 5 of event in one geographical area (namely Philadelphia), but further, to possibly influence sports/crime study in the field of criminology. Like the already “established” areas such as “gender and crime,” and “race and crime,” sports and crime needs to become a much more salient area of criminological study.

FRENZY

As the summer begins to fade, American sports fans are lulled into a sense of comforting sameness, as the sounds of a baseball hitting a bat become commonplace.

With baseball season beginning in the chilly spring and giving fans an almost daily dose of diamond ball, by late August, fans know that one win or one loss will not make or break a season. With months to go before the World Series, baseball fans can calmly take in an afternoon game and in towns like Pittsburgh or at stadiums like Sun Life

Stadium in Florida, fans may have entire sections to themselves. There is an easiness about these games—the pace is slow, the air is warm, it is often relatively quiet in between pitches. With 162 regular season games per year, baseball fans can afford to be patient.

It is just when the national mood of sports fans becomes almost complacent that six simple words--in a certain combination--serve to raise the pulses of millions of

Americans, with what has become a national rallying cry—Are you ready for some football?

As opposed to baseball’s 162 regular-season games and the 82-regular season games of both the National Basketball Association and the National Hockey League, professional teams of the National Football League play a mere 16 games during the regular season. As one NBC sportscaster put it, “Because the season is shorter, the NFL 6 and the television networks ‘hype’ each game into a major event (NBC Sports, 2010). ”

This may be one reason why fans are as frenzied at regular season football games as they are during playoffs of other sports. With so few games, the pressure to win becomes so much greater.

The popularity of the NFL in this country cannot be overstated. For example, the

NFL “received more than eight times as much money each year for TV and cable broadcast rights as MLB, despite the fact that MLB teams play about 10 times more games yearly than NFL teams (Plunkett, 2010).” Is it any surprise, then, that the slogan

“Are you ready for some football?” has become what former NFL commissioner, Paul

Tagliabue, calls “part of the lexicon of sports?” (Mihoces, 2002).

For the non-sports fan, this may seem like a benign set of words, but the import and the impact of this expression must be understood. The way these words are delivered is part and parcel of the fervor of football season. In 1989, Hank Williams Jr. opened each broadcast of Monday Night Football with his “rowdy musical question: ‘Are you ready for some football?’” An article in the St. Petersburg Times asked, “What’s with this Hank Williams Jr. opening each and every show with a bunch of apparently semi- soused yahoos yelping in the background?” (in Mihoces, 2002). Although other media sources were critical of the “grating” theme song at the time, not only did it become a staple of Monday Night Football, it is now part of American culture. The song is loud and rowdy and uses the language of battle:

Well, it’s Monday night and we’re ready to strike, our special forces are in full- flight, we’re comin’ by air and on the ground, Monday Night Football is takin’ over the town. We gotta get ready, we gotta get right, it’s gonna be a battle in the NFL tonight…All my rowdy friends drop in on Monday night…They are ready for action across the land, the boys in the trenches, the fans in the stands…The 7

guys with cannons—the way they through, ABC’s got the most explosive show…”

“War talk” is not uncommon in the sports world. Often, after a championship game or a match of extreme importance, whether in the United States or Europe or South

America, it is said that the “fans stormed the field.” It happens so frequently, in fact, that the term itself does not cause alarm. Because it is an expected result, various police agencies around the world stand guard to control the rowdy and potentially dangerous crowds. Teams “roll over” their opponents. A long throw by a quarterback is called a

“bomb” and one who can throw a ball with accuracy and strength is said to have “ a rifle for an arm.” A certain defense is called a “blitz.” When the quarterback is brought-down by a defense, it is considered a “sack.” The quarterback leads the team in a “march down the field.”

Even in baseball, a pitcher who gives up many hits and/or runs in an inning is said to “get shelled.” In hockey, when a team prevents another from scoring on a hockey play, it is called a “penalty kill.” One of the most famous basketball coaches in American sports history, former Indiana University coach, Bobby Knight, studied the “Art of War” by Sun Tzu, a Chinese military philosopher, to develop his personal coaching philosophy.

Knight’s extremely successful coaching career only came to an end after his violent actions went too far and put one of his players into a choke-hold. Violence, war, and sports frequently share common attributes.

Although other sports utilize some of this “war talk,” it is more commonplace in football. A recent article in the Journal of Sport Behavior (a peer-reviewed journal) looked into the use of “war analogies as descriptors for sport” in the post-September 11th climate (End et al., 2003). 8

To begin with, the authors speak of a “sports-specific” vocabulary (End et al.,

2003), which Tannenbaum and Noah (1959) termed “the unique language of sports fans, sportugese. Tannenbaum and Noah (1959) found that the verb used to describe an outcome of a game was more informative for sports writers and sports readers in comparison to nonsports readers. The results of their work suggested that both sports writers and sports readers had a greater knowledge of sportsugese than nonsports readers.

This is just another example of how sports is a culture within a culture.

In the war analogy study, End et al. (2003) note that “several national sports columnists have expressed disdain toward the use of sport-war analogies.” The purpose of the study was to assess if sports fans would share this negative view of sport-war analogies. The authors’ hypothesis that “high-identifying sports fans would approve of and endorse the use of sports-war analogies to a greater extent that low-identifying fans”—even in the aftermath of the World Trade Center disaster—was supported (2003).

While this was a somewhat small study (n=95), based in one midwestern university, and the average age of respondents 19, the fact that the use of war analogies is still widespread shows that the backlash against its use was culturally insignificant. This acceptance of war analogies helps to make the case for a profile of a faction of fanatical sports fans—fans who take “fan-dom” to frenzied heights.

FANS

Shank & Beasley (1998) in their article, “Fan or fanatic: Refining a measure of sports involvement,” found—not surprisingly--that “sports involvement” is related to viewing sports on television, reading about sports in magazines and newspapers, attending sporting events, and participating in sports. They used a psychological 9 construct defined as “a person’s perceived relevance of the object based on inherent needs, values, and interests (1998).” In their study, the stimulus of interest is sport.

What applies to this dissertation is their finding on the demographic of the sports fan— consistent with previous findings, they found that the highly involved sports fan was more likely to be young, single, and male. It was, however, only in the case of gender that there was a statistical significantly difference of highly involved or not highly- involved; in other words, there were no significant differences in the age, marital status, and income levels of high or low levels of fans.

As to gender and the sports fan, James & Ridinger (2002) conducted a study comparing “sport consumption motives.” Although early research into sports fans’ motivations came from marketing sources, there is now a growing body of academic research that examines the reasons people watch and follow sports. It is from this body of work that the MSSC (Motivation Scale for Sport Consumption) was developed (James

& Ridniger, 2002). The MSSC provides an assessment of nine motives for sports consumption: achievement, acquisition of knowledge, aesthetics, drama/eustress (or positive stress), escape, family, physical attractiveness of participants, the quality of the physical skill of the participants, and social interaction. James & Ridinger (2002) note that after this scale was developed, research has shown that there is an increasing female fan base. Their research looked at the similarities and differences between male and female sport fans.

The authors point to a study by Dietz-Uhler et al. (2000) that indicated females and males did spend about equal time attending sporting events, but males had a greater interest in discussing sports with someone and watching it on television. They possessed 10 more knowledge of the subject. James & Ridinger (2002) examined the difference between females and males in their motives to be fans of a specific team. They found that males reported a stronger connection to sports in general. Females reported a stronger connection to a specific team than to sport in general (2002).

A finding with great importance to this dissertation is that while females enjoy sports, males both enjoy and derive an important social identity from sports. Males gave higher rating on the Achievement (sharing in a team’s success), Empathy (feeling the disappointment of a loss or poor play), and Knowledge (wanting to know the technical aspects and strategy of a sport) measures, suggesting that sports do provide an important identity not shared by females (2002).

SOCIAL IDENTITY

In 1979, L.R. Sloan found that “sports fans who become strongly identified with a sport team often experience a team defeat as though it were a personal defeat and report the same emotional reaction and team preparation as the team they support.” This group identification can be explained by social identity theory (Dietz-Uhler & Murrell, 1999).

Social identity refers to the part of a person’s identity involving his or her memberships in various social groups and categories (16). Research has shown that people are motivated to maintain a positive social identity and one way of achieving this is to favor members of one’s own group over other groups (1999). Essentially, the choice to become a fan of a certain team is a choice that others share and it is important for that choice to be vindicated.

Hirt, Zillmann, Erickson, and Kennedy (1992)--ascribing to the “symbolic interactionist view”--define the self as a set of internalized roles or identities. They 11 believe that for many sports fans, commitment to their identity as a fan of a particular team constitutes an integral part of their self-identity. As such, threats to identities of such importance and prominence are treated as a threat to self. According to Dietz-Uhler and Murrell (1999), there has been a variety of research that has examined the reactions people have when their identities have been threatened. Some of this research examines the effects of a team’s defeat on fans’ feelings about themselves. Hirt, Zillmann,

Erickson, and Kenney (1992) found that, after a team loss, fans felt worse about themselves, their own abilities, and the team.

Much of the work in this area refers back to two concepts—BIRG (basking in reflected glory) and CORF (cutting off reflected failure). Stemming from an article in the

Journal of Personality and Social Psychology, Cialdini et al. (1976) state that it is a common and understandable tendency for people who have been successful in some positive way to make others aware of their connection with that accomplishment, but there appears to also be a “seemingly less rational” (366) tendency for people to publicize a connection with another person who has been successful. They termed this tendency

“BIRG.” As the authors point out, the public trumpeting of an association with a successful other is understandable when one has been instrumental to that success. They further say, however, that the more intriguing form of this phenomenon occurs when “the one who basks in the glory of another has done nothing to bring about the other’s success” (366).

Before conducting three (football) field studies, Cialdini et al. (1976) point out the

“abundant anecdotal evidence that people try to make us cognizant of their connections with highly positive or successful others” (366). The forms of this, they state, are varied; 12 for example, states and cities that list famous people who live or reside there in publications, ethnic and religious affiliations, sexual identity, and even physical similarities—‘”Napoleon was short, too.’” The authors stated that while there “appears to be rich informal support…for the existence of a BIRG phenomenon, there seem to be no experimental investigations of the effect” (367). They, therefore, conducted a series of studies to examine BIRG and chose the athletic arena for their studies. They set out to a) reliably demonstrate the existence of the phenomenon, b) establish its generality over experimental contexts and measures, c) determine a mediating process for its occurrence, and d) discover some of its limiting conditions and thereby gain further information as to its nature (367). They also point out, “It is perhaps informative that the chant is always

‘We’re number one,’ never ‘They’re number one’” (368).

Cialdini et al. (1976) simultaneously conducted their study at seven universities with “powerful intercollegiate football teams” during part of the 1973 football season.

They predicted that students at these schools would be more likely to announce publicly their connection with their universities after the varsity football team had been successful than after the team had not been successful. They measured this by means of an examination of “wearing apparel”—the frequency with which students wore apparel that clearly identified the university that they attended.

After finding strong support for their hypothesis, the authors conducted two additional experiments—using two other methodologies—and found that the tendency to proclaim a connection with a positive source was strongest when one’s public image was threatened (372). Finally, Cialdini et al (1976) assert that, although they have stressed

“an interpersonal mediator of the BIRG phenomenon—the perceived esteem of others,” 13

(374-375) they do not wish to preclude the possibility of the tendency to BIRG privately.

They state, “The fact that in Experiment 2 we were able to influence the BIRG response simply by manipulating the characteristics of the observer suggests that the BIRG phenomenon is not mediated solely by intrapersonal phenomena” (375).

A theoretical basis for this process is found in Heider’s “balance formulations

(1958) in his theory of naïve psychology (Cialdini et al., 1976, Cialdini & Richardson,

1980). Heider (1958) proposed that observers, in the interest of cognitive consistency, perceive two objects as being similar when the relationship between them is positive.

Conversely, when the relationship between two objects is negative, these objects are cognitively processed as being dissimilar.

Snyder, Lassegard, and Ford (1986) propose that a second form of “indirect image management” is also suggested by Heider’s balance theory (1958). In addition to the

BIRG process “in which people theoretically decrease the distance between themselves and successful others,” people may increase the distance between themselves and unsuccessful others in order to avoid any negative association (1986). In this latter vein,

Snyder, Higgins, and Stucky (1983) proposed that increased distancing behavior is a distinct form of image management and called this phenomenon CORF “cutting off reflected failure” (383).

Snyder et al. (1986) make the claim that one can attain a greater understanding of this “distancing” process by distinguishing between the two processes—BIRG and

CORF. Specifically, basking in reflected glory can be more clearly understood as an enhancement tactic and in contrast, cutting off reflected failure can be understood as an 14 image-protection tactic. As such, basking in reflected glory may tap an enhancement motive; whereas cutting off reflected failure may tap a protection motive (383).

Snyder et al. (1986) state that overall, Cialdini and his associates have demonstrated that people are inclined to connect themselves with others who have been successful. They contend, however, that the CORF process has not been equally supported and set out to further investigate “distancing.” Their results replicate those of

Cialdini et al. (1976), with stronger support that cutting off reflected failure can be distinguished as image-protection strategy for the purpose of avoiding a negative evaluation.

So, the CORF process is useful to protect self-image, but how does that account for sports fans who continue to root for losing teams, year after year? Baseball’s Chicago

Cubs have not won a World Series since 1908, yet the home games are always well- attended. Is there something stronger than the protection of self-image when it comes to sports “fan-ship?”

In 1992, Hirt, Zillmann, Erickson, and Kennedy published an article titled,

“Costs and Benefits of Allegiance: Changes in Fans’ Self-Ascribed Competencies After

Team Victory Versus Defeat.” They assert that the previously published research on

BIRG and CORF provided some “very intriguing implications for understanding the phenomenon of sports fanship” (375). This previous research suggests that individuals choose to associate or not to associate themselves with a team depending on the team’s level of success and as such, provides an excellent explanation for the “fair weather” fanship observed when teams are successful. Hirt et al. (1992) say that this, however, does not address the consequences for the individual once an association with a team has 15 been formed; for example, fans of the Chicago Cubs. They contend that fans who have formed a strong unit relationship with a favorite team are not free to choose to associate or disassociate themselves from that team. Fanship, like any other important social identity, constitutes an affiliation in which a great deal of emotional significance and value are derived from group membership (725).

Ascribing to the symbolic interactionist view (cf. Stryker, 1968) that defines the self as a set of internalized roles or identities, they “believe that for many sports fans, commitment to their identity as a fan of a particular team constitutes an integral part of their self-identity” (McCall & Simmons, 1966; Nuttbrock & Freudiger, 1991). The team’s performance reflects directly upon the fan: Team success is personal success and team failure is personal failure. Hirt et al. (1992) write that several theorists believe that

“although fanship provides an individual with an opportunity to affirm his or her self- worth…fanship holds some unavoidable consequences and costs as well” (725). Namely, if the team loses, the fan, too, is a loser in his or her own eyes.

Hirt et al. (1992) theorize that since team success is viewed as personal success and team failure as personal failure, “we should observe the same effects following victories and losses as we see following personal success and failure.” They conducted two studies—results from both of which attested to the powerful effects of a team’s performance on its fans. Game outcome significantly affected both subjects’ current mood state and their state of self-esteem (735). Additionally, they found that game outcome not only influenced subjects’ estimates of the team’s future performance, but also on their own future performance on a number of tasks. Further, the results from their second study indicated that team success does work similarly to personal success and 16 team failure—like personal failure—leads to lowered estimates of both team and personal performance.

Central to the issue, Hirt et al. (1992) conducted a mediational analysis in “Study

2” and suggest that “it is changes occurring in subjects’ current level of self-esteem rather than changes in mood that mediate the observed effects on both team and self estimates”

(735). The authors claim that these results support the notion that challenges to an important identity for an individual (in other words, for sports fans with strong team affiliation) are treated as threats to the self. In fact, the effects were observed only for those subjects who reported high levels of fanship; subjects for whom fan identity was not so important did not seem to be influenced by team outcomes. On the other hand, for strong fans, this fan identity is so integral to their sense of self that they respond to team outcomes as if they directly affected the self.

One of the limitations of their studies—as the authors point out—is that the duration of these changes in fans’ perceived self-competence is unknown. The aforementioned study by Dietz-Uhler & Murrell (1999) is a longitudinal study that looks at fan reaction over the course of a university football season. They collected data from

74 participants on their perceptions of the team following each game. According to the social identity theory, they state that after a defeat, fans who have a strong identity should still be motivated to think about their team in positive ways. This concept could be crucial for this dissertation research, because it could lead to positive policy implications.

Dietz-Uhler & Murrell (1999) note that strategies for maintaining a positive image of one’s team are to offer explanations for the defeat or reorient one’s perceptions 17 of the game. This is why their study examines the effects of social identity on fans’ perceptions of their team over a season. They predict that fans who identify strongly with their university will evaluate the team more favorably than those who do not identify strongly with their team’s university (18).

A second issue in the Dietz-Uhler & Murrell (1999) study is the contextual factors that affect evaluations of outcomes. Here, they quote Durkheim’s work on the effects of social context on behavior on being relevant. They point to how previous research looks at whether the game was a win or a loss, but a number of other components of the game may be important. These factors include whether the team was expected to win or lose the game and the type of media coverage that the game received. These are both pertinent issues to this dissertation.

They found that fans who identified with their teams strongly evaluated the team more favorably over the course of the season and this effect occurred regardless of wins or losses. The authors suggest that to maintain a positive social identity, fans who identified more strongly with their university saw their team in a favorable light (25).

The second part of their study—looking to clarify contextual components—found that fans evaluated the team more positively when the team won, when the win was expected, and when media attention surrounding the game was positive. Finally, their results show that all fans tended to evaluate their team more favorably after the last game of the season, than the first game (1999).

TEAM IDENTIFICATION

It was believed (Wann et al., 2000) that two subject variables would impact fans’ decisions to present themselves as followers of a specific team: team identification and 18 self-esteem. Team identification “involves a fan’s psychological connection and attachment to a team (Wann, 1997). While the previous sections dealt with the self- esteem aspect of fanship, it is important to highlight that the role of team follower is a central component of the self-identity of highly identified fans (Tajfel, 1981; Tajfel &

Turner, 1979; Wann, 1997). In other words, this team identification exists outside the scope of these studies—time identification does not end six hours a game is over, nor does it stop in the off-season. Conversely, for lowly-identified fans, the role of team follower is only a peripheral component of their self-concept (Wann, 2000). The hypothesis for Wann’s 2000 study, therefore, is that highly identified fans would be more likely to use their association with a team in a self-presentational manner than lowly identified fans.

The second subject variable expected to affect the self-presentation of sports fan level was self-esteem (199). Although previous sections have dealt with the self-esteem issue, the combination of the two variables makes for an interesting study that—again— has special importance to this dissertation.

For Wann et al. (2000) another hypothesis, therefore, became—highly identified sports fans would be more likely to present themselves as a fan of a specific team to a rival supporter than lowly identified fans. Only those highly identified fans who were also high in self-esteem, however, were expected to present themselves as fans.

Surprisingly, the results suggested that self-esteem did not play a part in fan presentation; again the key seemed to be whether or not the fan was highly or lowly identified to a specific team. 19

So what are the attributions of the highly identified fan? Research on the attributional processes operating within sports fans originated in Hastorf and Cantril’s

(1954) investigation of the differential attributions of supports of a victorious college football team (Princeton) relative to followers of the losing team (Dartmouth). They noted that the fans for the two teams seemed to have been observing a different game— with each blaming the other for the rough and dirty play characterizing the contest (in

Wann & Dolan, 2001). Data reported in Wann & Dolan (2001) seem to indicate that not only do supporters of different teams “perceive different games,” (789) but that supporters of the same team who differ in level of identification also see different games.

Another finding is that fans who identify with a local sports team—as opposed to a distant team—become attached to a larger social group (Wann & Dolan, 2001). This has shown direct positive effects on psychological well-being, therefore, identifications with local sport teams may become increasingly valuable as “effective venues for social capital formation” (Wann & Dolan, 2001, p. 187).

NFL BIRGing

Of course, the concept of “local” may be rapidly changing. While these studies comparing fans of local teams to fans of distant teams are relatively recent studies, they overlook a major sociological trend—computer networking. It is simple enough for a

Cincinnati Bengals fan, living in Los Angeles, to find an online group to share his or her thoughts and fears and to celebrate wins, as well as commiserate after losses. If fans exhibit lower estimates of personal performance after a loss (Hirt et al., 1992), then one possible way to assuage this negative feeling would be to share in the loss anonymously.

This is referred to as “impression management in the face of defeat” (End, 2003 p.165). 20

For fans who want to bask in the reflected glory, an online outlet would be another arena to do so.

End (2003) conducted a study on NFL fans’ computer mediated BIRGing. He hypothesized that more people will link their web pages to the official NFL home pages of teams categorized as being successful compared to those that are considered unsuccessful. Further, he hypothesized that NFL fans will post more messages on the message boards of successful teams that unsuccessful teams. What he found was in direct opposition to his first hypothesis—there is no difference between fans of successful teams compared with unsuccessful teams—they basically show the same allegiance on the Internet.

On the other hand, as far as posting on message boards, End (2003) found an increase in the proportion of BIRGing messages following wins. What is most intriguing, however, is the finding regarding “blasting;” a strategy used to help maintain a positive social identity while reducing the threat to their self-esteem on occasions when their team loses (Cialdini & Richardson, 1980). End’s data suggest that fans may be using blasting tactics on the Internet because of the “deindividuated state afforded them by the Internet” (177-178). As End points out, if “a fan blasts another individual or individual’s team in a face-to-face situation, the fan runs the risk of physical violence or psychological harm” (178). Fans using message boards, however, do not fear physical retaliation and as a result, blasting may be seen as a plausible option for protecting or enhancing one’s sport fan identity.

21

SPORTS FANS: THE NUMBERS

The sports industry is so vast and varied it is difficult to quantify. As one marketing research company puts it, “To one person, sports are a venue for gambling; to another they are a mode of personal recreation and fitness; to business people, sports provide a lucrative and continually growing marketplace worthy of immense investments.

(Plunkett Research, 2010)”

In the United States, the “Big 4” refers to the four “major” spectator sport leagues—the National Football League, Major League Baseball, the National Basketball

Association, and the National Hockey League. These leagues earn approximately $17 billion in annual revenue, but that does not supply the entire picture of the market

(Plunkett, 2010). According to this research company, a reasonable estimate of the total

U.S. sports market would be $400 to $425 billion yearly. Obviously, this constitutes a huge percentage of American industry and there would be no sports industry, if there were not sports fans.

MACHISMO

When American baseball teams face-off in their championship series each year, the games comprise the “World Series.” With just one Canadian team in Major League

Baseball and teams from no other countries, it is hard to see the justification for this title.

Likewise, with American basketball and football, the champion for the season is often referred to as the “world champion.” The exception to this among the Big 4 is hockey, which is shared with Canada and therefore does not carry the same weight for American fans (the championship for the NHL is called the Stanley Cup Finals, named for Lord 22

Stanley, a former Canadian governor). The root cause for this chauvinistic attitude could be a topic for myriad studies, but regardless of how or why, many Americans see the

“Big 3” sports as emblematic of America’s status in the world.

Americans certainly have no monopoly on sports enthusiasts. Soccer, or what is referred to as “football” by most of the rest of the world is considered the most popular sport on the planet. Following the FIFA (Federation Internationale de Football

Association) World Cup in Germany, reports indicate there were 4.2 billion views of

FWC.com pages in just the first two weeks of the tournament (FIFA, 2010). Thirty-two countries send teams to the World Cup, which is played every four years. Fans from all

32 countries will cheer-on their heroes and carry their flags while dancing in the streets in celebration of their national pride. The U.S. will have a team in the World Cup, although the interest will not be as great as in the other countries.

Whether one’s view is international or a more myopic American view, it cannot be denied that sports—the production and consumption of—are a major part of human existence. Sports create an enormous amount of profit—through live events, television and radio broadcasts, and product marketing. Sports betting—both legal and not— heightens interest in games and adds another dimension of stress and celebration.

If this devotion to sports seems overstated, consider the proliferation of sports television and radio programming, sports magazines and newspapers—ESPN, started as a small cable network in 1979, now has a “family of networks” which includes 13 channels

(ESPN, 2010). To underscore the point of the gendered nature of sports and its consumption, the sold-out advertising on ESPN is aimed at the 15-35 year old, male audience (Plunkett, 2010). Bryant and Raney (2000) note that several studies on sport 23 media audiences propose that group differences, such as gender, can account for variance in viewing enjoyment and programming preferences (in McDaniel et al, 2007). Sargent et al., for example, use cluster analysis to group descriptive data on sports media into three general classifications: combative, mechanized, and stylistic (1998).

Combative sports are those characterized by the involvement of direct physical contact and are divided into the following categories: violent combative (e.g., football, ice hockey) and aggressive combative (e.g., basketball, soccer) contests. Mechanized sports are categorized based on the use of tools by the performers, for events such as golf and auto racing (with the former being further classified as non-risky and the latter being classified as violent). Sporting competitions that stress movement and elegance (e.g., tennis, figure skating) are categorized as stylistic sports (McDaniel et al., 2007, p.607).

Analyses of viewing preferences related to the above sports typology reveal that males report significantly greater viewing enjoyment of combative and mechanized as compared to females, who on the other hand, report more enjoyment of stylistic sports than males.

McDaniels’s (2007) typology research comes from the business world and its importance lies in its connection to the use of violent images to promote consumption of sports entertainment. While the United States Federal Trade Commission (FTC) and

Department of Justice both focus on the marketing of violent entertainment and have pushed for the use of a content ratings system (Grier, 2001; Teinowitz et al., 1999), violence in televised news and sports have not yet been subject to content ratings in the

U.S. and Canada (McDaniel et al., 2007). Studies that have examined the level of violence in on-air promotions during sports broadcasts have also neglected to examine the violence in promotions for sports telecasts, as some contend that aggressive physical 24 acts in such entertainment contexts is considered to be “socially tolerated” (Walker,

2000).

Broadcast media is not the only outlet for sports, but it is the most influential.

ESPN, for example, has divested into other business ventures that include a magazine, a chain of restaurants, a book publishing company, and “ESPN Original Entertainment,” which produces made-for-television films. This is not an exhaustive list and is illustrative of the growth of sports as an industry. This growth began—not coincidentally—at the same time that television media expanded with the advent of cable.

One British scholar, Eric Dunning, notes a similar phenomenon. Dunning refers to the factual increase of “football [author’s note: European football] hooliganism” and an increase of press interest in football hooliganism as a “newsworthy” subject (Dunning,

2000). ***He asserts that this increase also occurred correlatively with growing popular and political interest in football hooliganism as a social problem and with what “one might jargonistically call the ‘tabloidisation’ of the popular press, that is, the rise to prominence, largely as a result of intensifying competition with television news and popular newspapers in the sensationalizing tabloid form.” The growth in media will be discussed further in the chapter titled “Media and Crime,” but for the purpose of this section, the “intense media searchlight,” as Dunning refers to media coverage today is a searchlight that illuminates much violence associated with sports (2000).

HOOLIGANISM

The most important thing to stress about hooliganism, Dunning (2000) contends, is that the label is not so much a social scientific or social psychological concept as a construct of politicians and the media. As such, it lacks precision and is used to cover a 25 variety of forms of behavior, which take place in more or less directly football-related

[soccer] contexts (142). Further, Dunning claims that football hooliganism—although marked as a mainly “English disease,” is a world phenomenon (143).

No matter what the genesis of the terminology is, football hooliganism is a

“widespread and problematic phenomenon in Western Europe, causing an appalling toll of death, injuries, and damage to property” (Russell, 2004).

Dunning & Murphy (1992) conducted a study in which they examined a range of

English newspapers and recorded references to football-related violence, involving fans rather than players, which were reported as having occurred outside Great Britain. In the course of their research, they came across reports of 101 incidents of football-related violence involving spectators or fans, which occurred in 37 countries between 1908 and

1983. Dunning & Murphy report that 16 of the 17 countries (17, if one includes the former USSR) were European and this was the highest geographical concentration of reported incidents. Central and South America, with hooliganism reported as having occurred in five countries, came in second. The United States and Canada show one incident for each country. The country with the most incidents in what Dunning calls the

European “division of dishonor,” however, is Germany, which Dunning suggests contrasts with the dominant stereotype of the English hooligan (1992).

Two other researchers with considerable work on hooliganism—Giulianotti and

Armstrong—say that in the past thirty years, “few issues have attracted the breadth of explanation and intensity of debate as that of football hooliganism” (2002, p.211). They mention that the main “protagonists” are those working from the Marxist, social psychological, and figurational perspectives, but others have come from the overlapping 26 fields of cultural studies, anthropology, and post-structuralist sociology. They make the case for exploring the nexus of urban landscape and sport. Meanwhile, Dunning recaps the five main popular explanations of football hooliganism that have been espoused by the media, politicians, and members of the general public. These five explanations are 1) that football hooliganism is “caused by excessive alcohol consumption,” 2) violent incidents on the field of play or biased and incompetent refereeing, 3) unemployment, 4) affluence, and 5) permissiveness. Dunning (2000) then claims “none of them is supported by the available evidence” (151).

For purposes of this dissertation, explanations 1 and 2 shall be examined. First, alcohol consumption cannot be said to be a “cause” of football hooliganism, because not every fan who drinks in a football context fights, not even those who drink heavily. The converse is also true—not all hooligans drink before fighting because they need a clear head in order to direct operations and avoid being caught unaware by rivals or the police

(Dunning et al. 1988). Next, Dunning (2000) says “violence on the field of play and refereeing that is or is perceived as biased, can similarly be dismissed as lying at the roots of football hooliganism” (151). Dunning says this is because incidents take place before and after as well as during matches, often at considerable distances from the grounds.

Although there is little agreement among British researchers, a study on hooliganism from Belgium looks at social identity as a possible explanation. This is in accord with the American studies on [American] football, basketball, and baseball.

Van Heil et al. (2007) set out to investigate the personality basis of violent behavior, as well as the intervening role of deindividuation in the genesis of hooliganism

(169). Based on Reicher’s (2001) “Elaborated Social Identity Model” (ESIM) of crowd 27 behavior, Van Heil et al. (2007) look to test the assumption that the loss of self-awareness does not automatically result in dehumanization. Instead, the ESIM posits that depersonalization, as it occurs in anonymous group settings, leads to an increased salience or importance of social categories, leading in turn to a greater adherence to group norms and standards.

So, what did Van Heil et al. find in terms of hooliganism and social identity?

Again, they based their research on Reicher’s work, which showed that people’s behavior in anonymous “ingroup” settings is guided by their social identity, offering a means for organizing their behavior into teleological and ideological coherence (Van Heil et al., p.

173). Further, it could thus be argued that group violence often reflects the operation of specific group norms, rather than being a sign of deregulation of conduct into thoughtless and aimless behavior. It is therefore posited that social identity, rather than loss of private and public self-awareness, is the crucial process variable that explains (violent) group behavior.

The results of their study support Reicher’s earlier studies, but add another element—reduction of private self-awareness showed a strong relationship with social identity, and therefore “both these phenomena appear to be a constitutive element of the global phenomenology of mass violence” (173). This finding has important implications for this dissertation, as will be discussed later in this writing.

Although most of the research on hooliganism focuses on the so-called hooligans, little research exists on the solutions to the problem; for example, the policing of spectator violence (Frosdick, 2005). For the majority of European soccer matches, fans of opposing teams are segregated. In many stadiums across Europe, Asia, and Africa, 28 high metal fences and cages separate these fans (Frosdick, 2005). Interestingly, just as the “hooligan” problem is practically non-existent in the United States—a country with much violent crime—segregation of fans is not utilized.

SPECTATOR VIOLENCE IN NORTH AMERICA

Spectator violence at sporting events “appears to be as old as sport itself” (Simons

& Taylor, 1992). The first reported incident of fan violence took place during a chariot race in Constantinople in 532 B.C. (208). According to written accounts, rioting fans seized the stadium and intervention by Roman soldiers was required to regain control of the situation. By the time the riot was over, an estimated 30,000 people were dead

(Cameron, 1976, cited in Simons & Tayor). In 59 A.D., violence during gladiator fights in Pompeii was so bad that the Roman Senate banned the fights for ten years (208).

In the modern era, the deadliest incidence of fan violence took place in 1964, during a soccer match between Peru and Argentina, when 318 people were killed and over 500 were injured (Yeager, 1979 in Simons & Taylor). Although, as Russell rightly points out, when viewed against history, spectator violence appears to be less severe, it still presents a “universal and ongoing concern” in many nations (Russell, 2003).

SELF-REPORTED SPECTATOR VIOLENCE

Russell contends that the data for frequency of crowd disturbances at major sporting events are generally drawn from sources that under-represent the true incidence of spectator violence (2003). He suggests that an alternate means of estimating potential rioting is to assess spectators’ self-reported likelihood of escalating or being involved in a crowd disturbance. The findings suggest a great variation across time, sports, cultures, and the conditions surrounding the sporting event itself. For example, van der Brug and 29

Meijs (1994) administered questionnaires to a sample of young Dutch soccer fans during the 1990 European championships and the qualifying round of the World Cup.

Respondents indicated that against Germany, 27% “wanted to become involved in incidents.” Likewise, for two later matches against England, those same young men indicated a desire to become involved in incidents at the rates of 22% and 27%. By contrast, only 1% intended to get involved in an incident in a future match against Wales. van der Brug made no conclusion as to whether the Welsh fans were not considered

“incident worthy” or whether there were announced safety measures put into place.

Arms & Russell (1997) conducted a survey of somewhat older Canadian hockey spectators (M=30 years) who were asked to provide estimates of the likelihood they would escalate a disturbance that had erupted nearby in the stands. The percentage of men “extremely likely to join-in” was 13% (Mustonen, Arms, & Russell, 1996). In a similar study with Finnish hockey fans, 9% reported an extreme likelihood of involving themselves in a crowd disturbance. Lewis (1992), looking at American fan violence, presented college students with scenarios of football and hockey riots that involved fatalities. Asked if they would be willing to participate, 2.4% of the men indicated they would join in the football riot, while 6.1% said they would participate in the hockey riot.

In both cases, women were unanimous in declining the opportunity.

THE PROMISE OF VIOLENCE

In an article appearing in The Star-Ledger (March 3, 2009), newly signed free agent linebacker, Bart Scott, told reporter Dave Hutchison, “It’s one thing to be physical and make a tackle. It’s another thing to be violent. Violence makes (opponents) stay on the sidelines when they’re getting hit and are questionable when their ankle is hurt. If 30 they know (if they come back in the game) they’re going to receive violence, they’ll sit that one out.” Contrary to being offended by these and other remarks made by Scott, the sportswriters and editors were thrilled by these statements, going so far as to give the idea a headline: “New Jets LB Scott promises ‘violence.’”

Violence in the stands, violence on the field and on the ice, violence in the bar— does “sports” naturally lend itself to violence? Does fan violence simply mirror the violent action in the games? Is violence just inextricably linked with sports? Ostensibly, fan violence is connected with supporting a team—a team that usually (but not necessarily) represents the geographical location of the fan or the school the fan attends or attended (BIRGing). Does the BIRGing further connect to the individual players?

Further, does the promised, anticipated, and delivered violence add to the fabric of this intricately woven connection? Finally, does off-the-field behavior by the athletes and their ability to often avoid punishment for violence add blood luster to the already enticing spectacle? Is it all an excuse to express one’s violent impulses? One issue at a time must be addressed, but the questions bear some pondering.

SUPERSTARS

Central to all this interest is the athlete himself. The gendered term is used here because few female athletes attain the kind of adoration and influence that male athletes garner. The money and fame that an athlete can command—through a profession--are rivaled only by the money and fame earned by a “rock star” or “movie star.” This puts the athlete in a different category from most “ordinary” people. Not only does the athlete represent the city or state or school from which the fan hails, but the athlete also 31 represents a lifestyle that few others can attain. Simply put, the athlete is a superstar in the eyes of the devoted fan.

If fans bask in the reflected gory of their teams, then they most likely reflect in the glory of the members of those teams. Like the gladiators and heroes that set-off mass spectator violence in Greek and Roman history, heroes of today cultivate a devoted fan base. Unlike the gladiators and heroes of yesteryear, today’s sports idols have mass communication to tout their achievements. Additionally, many athletes of today are paid what would be considered a “royal sum,” putting their “worth” on pedestals that few ancient heroes ever graced.

The salaries and lavish lifestyles of sports heroes only add to the reflected glory, but what about the aggressive behavior of some professional athletes? Does this aggression--which sometimes leads to serious physical violence--influence spectator violence?

OUT OF BOUNDS

In 1994, former NFL star, OJ Simpson led the California Highway Patrol on a 50- mile chase, while the major networks cut into regularly-scheduled programs and 95 million viewers watched (Mydans, 1994). He was accused of killing his ex-wife and her boyfriend and there was considerable evidence against him, yet he was found innocent.

Certainly, athletes have been accused of violent crimes before the OJ Simpson trial, but this case was a media phenomenon. One of the results of this trial was to add to the scholarly interest in examining the relationship between athletes and violence.

The Newark Star-Ledger often includes a “police blotter” in the sports section.

So many players from the NBA’s Portland Trailblazers in the past few years, the team 32 has earned the nickname “Jailblazers.” Lopresti (2007), a sports writer from USA Today, claimed that his research for “player news” for the upcoming college football season led him to pages of crime news, as player after player was charged with various crimes.

Pappas et al. (2004) note that in recent years there has been an increase in documentation of athlete aggression directed toward other males outside the sports arena, as well as aggression directed toward women in both intimate and non-intimate situations.

From a social psychological point of view, aggression is conceptualized as a particular form of social behavior that is both shaped by an individual’s social world and has effects on that social world and its inhabitants (Krahe, 2004). Terry & Jackson

(1985) contend that a powerful socialization process is the primary determinant of sports and sports-related violence. They see sports aggression as behavior learned in a culture that reinforces and models violence. Messner and Sabo (in Pappas et al., 2004) contend that the male tolerance of risk and injury in sports is not a socially passive process, but rather is one through which violence, injury, and disablement become reframed as

“masculinizing” by society at all levels. Demonstration of these behaviors, is therefore, linked to gender legitimacy (1990).

According to West & Zimmerman’s (1987) work on “doing gender,” violent behavior is a way of constructing oneself as masculine and demonstrating one’s place in the masculinity hierarchy. Violence and aggression may be displayed as a way to meet the gender expectations of the peer group (Pappas et al., 2004). Crosset (1999) argues that training for sport in the context of an already patriarchal society may also be training men to be violent toward women. For example, coaches employ images of femininity and castration to chastise players—“You play like a little girl.” Curry (1991, 1998, 2000) 33 found team dynamics that openly express support for violence against women and demonstrate how resistance to these norms is discouraged.

Pappas et al. (2004) say that there appears to be both institutional and community support for violence associated with sport, both within and outside the sports context

(295). Institutional support for alleged perpetrators of violence outside the sport often blames the victims and fails to hold athletes responsible for their actions. Crosset (1999) contends that the inability of institutions to hold athletes accountable also extends to the court system.

Countless athletes have been accused of wrongdoing in the last decade alone; many of who never faced trial. In spite of higher rates of violence within the sport communities, conviction rates present a striking difference that favors the accused athlete

(Benedict & Klein, 1997). Benedict & Klein examined arrest and conviction rates for collegiate and professional athletes accused of felony sexual assaults against women and compared these with national crime data to determine differential patterns of treatment in the criminal justice system (in Pappas et al., 296). Benedict & Klein (1997) found that of

217 athletes who were initially reported to the police for a felonious sex crime, only 24 percent were successfully prosecuted. Additionally, Benedict (1997) found in 150 case studies of reported violence that athletes were convicted in only 28 cases, mainly through plea-bargaining agreements. Only ten cases went to trial and six of those cases resulted in guilty verdicts.

In their work, Pros and Cons: The Criminals Who Play in the NFL (1998),

Benedict and Yaeger conducted a study on the then-current players on NFL rosters. They determined that 21% of those players had been arrested for serious crimes. 34

In 1996, Vermont Congressman Bernard Sanders sent a letter to then-NFL commissioner, Paul Tagliabue (Benedict & Yaeger, 1998). The letter stated:

We are writing to ask in the strongest terms that the NFL join with us and commit to work together to fashion a multi-faceted strategy to deter domestic violence, including counseling, strong disciplinary action when warranted, and a high-profile education and advertising campaign against domestic violence (147).

Of utmost importance to this dissertation, the following was also excerpted from this letter: Surely you recognize the enormous influence that big-time football players at the professional and collegiate levels, as role models, have upon our society. …Undoubtedly when instances of domestic violence receive little more than a slap on the wrists in court and go unpunished by the NFL…that sends an insidious and harmful message to many Americans. …the current message being sent seems to be that domestic violence is not to be taken too seriously and this it is not the indefensible and serious crime that it is (147).

The NFL reacted by sending Congressman Sanders an accusatory letter, saying that any attempts to single out the NFL on the issue of domestic violence would be treated as racist.

CHAPTER ONE—SUMMARY

Sports and crime is an under-developed segment of criminological study, yet the two intersect in many ways—illegal betting, “doping” among professional athletes, cheating in sporting events, hooliganism, and athletes who commit crimes. The most thoroughly researched topic in the area of sports and crime is hooliganism or stadium violence. Hooliganism may not be an exact term, but it actually encompasses the behavior better than stadium violence, because some of the violence associated with sports fans takes place at bars near the stadiums or even in the streets surrounding the stadiums. 35

Americans do not commit stadium violence as often as fans from Europe, Asia, and South America; most of the sports fan aggression studies emanate from Europe because of this. While what Americans call “soccer” is the favored sport in the rest of the world, in the United States, the number one sport for spectators and fans is what

Americans refer to as football.

In sports, “war talk” is common. Researchers also agree that there is a spots- specific vocabulary, which is referred to as “sportugese.” This is another example of how sports is a culture within a culture.

While females may enjoy sports, males both enjoy and derive an important social identity from sports. Research overwhelmingly shows that some of these fans are highly- identified with their favorite sports teams.

Sports leagues in the United States alone earn approximately $17 billion in annual revenue and football is the most lucrative. Football is also considered one of the two

“violent combative” sports out of the “Big 4” in the United States; hockey is the other sport categorized as such.

Broadcast media is the most influential outlet for sports. Because of the money garnered by television contracts, the leagues are wealthy and the players are wealthy individuals. Sports heroes have an extremely high cultural status—not just in the United

States, but all over the planet. A high percentage of players who play in the National

Football League have been arrested for serious crimes; in 1998, that number was 21%. 36

CHAPTER II--MEDIA AND CRIME

“Culture is simply the ensemble of stories we tell ourselves about ourselves,” Clifford Geertz, Professor of Social Science at Princeton University (Inglis, 2000)

What is media? If culture is simply the stories we construct about ourselves, then the media is simply the way we disseminate those stories. The stories provide an interpretive framework through which we are encouraged to understand various aspects of culture (McCullagh, 2002). These stories, then, both reflect and shape our culture and for the most part, these stories are told on television (Cavender & Deutsch, 2007).

How influential are television and other forms of media on our behavior—specifically, violent behavior?

STUDIES ON EFFECTS OF VIOLENT MEDIA--TELEVISION

Television is the central and most pervasive mass medium in American culture

(Signorielli, 1987). Television was introduced at the World’s Fair in 1939. Since 1985, household television ownership has been about 98%. More recent types of electronic media have become ubiquitous instruments in modern society. About 97% of homes with children have a VCR, 90% have a CD player, and 89% have either a personal computer or other video-game capable equipment (Federal Trade Commission, 2000).

The American public has consumed media as if they were ambrosia (Bushman &

Anderson, 2001).

Americans get a heavy dose of media violence (Bushman & Anderson, 2001). By the time the average American child graduates from elementary school, he or she will have seen more than 8,000 murders and more than 100,000 other acts of violence on 37 network television. The numbers are higher if the child has access to cable television or a videocassette player, as most do (Bushman & Anderson, 2001).

Most of our knowledge about television violence comes from studies conducted during the past 35 years as part of the Cultural Indicators project and the research conducted in the mid-1990s in the National Television Violence Study (NTVS).

Sixty percent of television programs contain violence. Provenzo (1991) found that 85% of the most popular video games were violent. One plausible explanation for the media emphasis on violent materials is that violent media are easier to export to foreign markets, perhaps because they lose less in the translation. Comedies, for example, usually require some knowledge of the popular culture. In time, violent media might become America’s most exportable commodity (Hamilton, 1998).

EFFECTS ON CHILDREN

In his now famous defense of fairy tales, The Uses of Enchantment (1976), noted child psychiatrist, Bruno Bettelheim, urged parents to retell their children the traditional stories in their original forms, without censoring the violence. He argues that the tales’ violence, especially the endings, should not be taken literally. These tales were metaphors that worked through universal questions young people had about growing up and coming into their own as distinct, valuable human beings. The symbolic nature of the final, violent acts in the tales, Bettelheim stressed, often served an important psychological function for both the teller and listener: that of restoring a sense of justice and order to the imaginary world the child has entered and vicariously lived through in the stories (Bettelheim, 1976). Since Bettelheim’s widely publicized defense of the tales, the subject of violence has hardly come up for discussion (Cech in Dowd, 2006). 38

Cech (2006) says that putting aside the theories concerning violent nursery rhymes and fairytales, society must consider the new unmediated reality of today’s abundance of media offerings. Adding to these established literary forms the newer digital genres of video games and the Internet, the reenergized comic industry, and electronic media like television, movies, and popular music, Cech claims that children have returned to a new, immediately accessible Mother Goose world in which anything and everything is produced and available, almost instantly, for an audience that crosses generations and societal strata (2006).

MAKING THE CASE FOR MEDIA AND AGGRESSION

Modern society—as a whole--is exposed to a massive dose of violence. In the

20th century, two major explosions occurred: a mass media explosion and a violent crime explosion. Zimring & Hawkins (1997) report that among industrialized countries, the

United States is one of the most violent. Scholars have been investigating media violence as a potential contributor to societal violence in the United States since the early 1960s.

One possible reason for the early interest in a link between media violence and societal violence is that violence in the U.S. began to increase fairly dramatically in 1965, exactly when the first generation of children raised on TV began to reach the prime ages for committing violent crimes. In fact, studies of violent crime rates before and after the introduction of television have shown similar effects in several countries (Centerwall,

1989, 1992).

In 2003, Huesmann et al found that even after controlling for parental SES, children’s academic skills, and childhood aggression, childhood TV violence viewing significantly predicted adolescent and adult aggression. Similar findings were reported 39 by Eron et al. (1972), Huesmann (1986), Viemero (1996), Christakis and Zimmerman

(2007)(in Boxer et al., 2009). Even the U.S. Surgeon General has acknowledged formally the causal influence of violent media on youth violence (U.S. Surgeon General,

2001). Yet, the developmental and clinical child/adolescent literature is missing the recognition that exposure to violent media is a salient and robust risk factor for aggressive behavior (Boxer et al., 2009).

To that end, Boxer et al. (2009) investigated the integration of violent media exposure into the broader matrix of risk for violent and nonviolent antisocial behavior.

Interviewing over 800 adolescents, they hypothesized that including violent media exposure into cumulative risk computations would yield significant improvement to predicting antisocial behavior from the cumulative risk total. They found that violent media preferences accounted for small, but significant proportions of violence in outcomes.

The television and motion picture industries often claim that violent media have no influence on aggressive behavior. The same industry, however, makes all if its money from commercials, charging hundreds of thousands of dollars for a few minutes of commercial airtime (Bushman & Anderson, 2001). As former Federal Communications

Commission Chairman Reed Hundt said, “If a sitcom can sell soap, salsa, and cereal, then who could argue that TV violence cannot affect to some degree some viewers, particularly impressionable children?” (Eggerton, 1994). Sometimes, the entertainment industry goes one step further and claims that violent media influence behavior in a beneficial way (Bushman & Anderson, 2001). 40

According to Bushman & Anderson (2001), the first recorded description of this

“catharsis hypothesis” occurred more than one thousand years ago, in Aristotle’s Poetics.

He taught that viewing tragic plays gave people emotional release (catharsis) from negative feelings such as pity and fear. By watching the characters in the play experience tragic events, the viewer’s own negative feelings were presumably purged and cleansed.

This emotional cleansing was believed to benefit both the individual and society.

This ancient notion of catharsis was revived by Sigmund Freud and his associates. For example, A.A. Brill, the psychiatrist who introduced Freud’s psychoanalytic techniques to the U.S., prescribed that his patients watch a prizefight once-a-month to purge their angry, aggressive feelings into harmless channels (Feshbach & Price, 1984). When leading psychiatrists such as Bettelheim and Brill espouse an idea, the media “industry” has more fodder by which to feed its money-making machine. Bushman & Anderson

(2001) contend, however, that the literature proves the catharsis effect is far less than the deleterious effect that violence in the media produces.

One common industry response to the conclusions of such literature reviews is to deny the findings. Another is to claim that the effects of media violence on aggression are so small or they affect so few people that the risks to society are negligible and can and should be ignored. The scientific evidence, however, shows otherwise (Bushman &

Anderson, 2001).

Both qualitative and quantitative studies reveal that viewing violence increases aggression. In July 2000, six major professional societies signed a joint statement on the hazards of exposing children to media violence, noting that “at this time, well over 1,000 41 studies…point overwhelmingly to a causal connection between media violence and aggressive behavior in some children” (Joint Statement, 2000, p.1 in Dowd).

Bushman & Anderson (2001) further contend that since 1975, the scientific confidence and statistical magnitude of the link between media violence and aggression have been clearly positive and have consistently increased over time. Reasons for this discontinuity between media and the actual state of scientific knowledge include the vested interests of the media, a misapplied fairness doctrine in news reporting, and the failure of the research community to effectively argue the scientific case (Bushman,

2001).

MORE VIOLENT VISUALS

Film is one of the primary sources through which people get their ideas about the nature of crime (Rafter, 2007). Yet, Rafter points out that “crime-film study” is still in its amorphous stages; lacking the coherence of the closely-related literature on law films.

While Rafter seeks to encourage new study and the furtherance of this field within criminology, the issue in this research is whether film is dangerous to those who observe it or to victims of those who are criminally affected by them.

One particular branch of the film industry has been well-studied—pornography.

The use of pornography by sexual offenders has been a much-disputed topic. Langevin

& Curnoe (2004), acknowledging that there is little convincing evidence that pornography has a major role to play in the commission of sexual offenses, set out to conduct a more-encompassing study. Their results showed that pornography plays only a minor role in the commission of sexual offenses, in terms of the number of offenders using it immediately prior to, or during the offense. Their findings do, however, show a 42 major concern that pornography use in the commission of sexual crimes primarily involved child victims. The authors caution that this result is unclear—because of the random nature of assault in their sample, it was difficult for the victims to ascertain what their attackers were doing previous to the assault. On the other hand, the children involved in these attacks were lured into places and held for longer periods of time and therefore, experienced more time with their attackers.

Likewise, Seto and Eke (2005) found that the habitual use of child pornography alone did not predict subsequent offending, but that those child pornography offenders with prior criminal records were significantly more likely to offend.

The results of studies on women are slightly different, perhaps because the children have less ability to describe their ordeals. Two schools of thought have emerged about the effects of pornography and whether or not there is a causal connection between pornography and violence against women (Bergen and Bogle, 2000). On one side of the debate are those who argue that pornography has no harmful effects. In fact, some early research on pornography found that it produces a “cathartic effect” and thereby to reduce the amount of sexual assault (Ben-Veniste, 1971; Kutchinsky, 1971). As a result, laws restricting the production, sale, and distribution of pornography were relaxed and pornography became a more prevalent part of American culture (Russell, 1993). On the other side of the debate, many feminists have argued that pornography is associated with violence against women and contributes to the high incidence of rape in this country

(Russell, 1993).

Bergen & Bogle (2000) reject much of the early research reporting a cathartic effect because this research was essentially done in a laboratory and lacked the “real- 43 world environment in which male aggression is often encouraged and sanctioned.” Other research found the strongest correlation between exposure to hard-core violent and rape pornography and self-reported likelihood of using force (Boeringer, 1994). Overall,

Bergen & Bogle (2000) found support that there is a relationship between pornography and violence against women.

This finding gives even more importance to the article by Boyle (2008), which states that the increase of “docu-porn” serves to “normalize’ both pornography and prostitution. Docu-porn is what Boyle refers to as the “late-night” television programming, seen in both the U.S. and U.K., which has become increasingly popular since the 1990s. This normalization of pornography and prostitution, she posits, is a way of legitimating commercial sex and exploitation. Further, acceptability of pornography and commercial sex is heralded by everyday media references.

VIDEO GAMES

Media violence has repeatedly been blamed for horrific acts of social aggression, usually involving murders that have shocked the societies in which they occurred

(Gunter, 2008). In 1993, two 10-year-old boys were being tried in England for the murder of 2-year-old James Bulger. The court considered that the murder was inspired by a video game. Child’s Play 3 was cited as a possible trigger, even though it contained no depictions that appeared to have the most remote relevance to the actual murder that took place (Barker & Petley, 1997). On the other hand, on June 24, 2008, six teenagers from Long Island, New York, launched a two-hour long crime spree, during which they committed a violent mugging and several break-ins and thefts, before finally being caught after a carjacking attempt (Crowley, 2008). According to the authorities 44 investigating the crimes, the teenagers had determined to replicate the actions of Niko

Belic, the thuggish protagonist from the new video game ‘‘Grand Theft Auto IV’’ (Boxer et al., 2009).

Anderson et al. (2007) in their research on “violent video games,” first and foremost, define what aggression means to them for their studies. This is meant to alleviate some of the confusion and “artificial debate” on how many studies of

“aggression” are in the literature (p.13). They state that social psychologists and most human aggression researchers have adopted a much more precise definition of human aggression:

(a) a behavior that is intended to harm another individual, (b) the behavior is expected by the perpetrator to have some chance of actually harming the individual, and (c) the perpetrator believe the target individual is motivated to avoid the harm.

Anderson et al. (2007) point out that in prior violent video game research--from the first comprehensive narrative review of the literature through more recent meta- analyses--exposure to violent video games was significantly associated with increases in aggressive behavior.

Although in recent years, the research on negative effects of violent video games on children has become more persuasive, attempts by various educational entities have yielded little improvement. While several states and municipalities have passed legislation designed to provide parents with information and to restrict sales to children, the video industry has worked against these laws. The video industry has repeatedly gone to court to block enforcement of such laws and so far, has succeeded in all attempts.

To support their claims that playing violent videogames has no effect, Anderson et al. (2007) say that the video industry often cite critics of media violence research. 45

Anderson et al. (2007) claim that many of these critics have never conducted any original empirical scientific studies on video games and have sometimes been paid by the media industries to write critiques or to testify in court (Huesmann & Taylor, 2003).

Sports and video games are closely tied. EA Sports creates and sells video games called, “Madden: NFL 11,” “NCAA Footbal 11,” “NHL 11,” “NHL Slapshot,” “Fight

Night,” and countless more. The pictures on the covers of these games show aggressive- looking men in macho poses. The “2K11” website, which is rated “E” for “Everyone,” immediately launches into a promo for a hockey game, during which there are 12 instances of hockey players crashing into each other in the course of 56 seconds. ESPN has a website devoted to video games. A videogame player can “become” one of his heroes, through these games. Finally, it is common for professional athletes to talk about their favorite video games during interviews.

CHAPTER TWO--SUMMARY

Television is the most pervasive mass medium in American culture. This medium provides American children with a heavy dose of violent media. By the time the average child graduates from elementary school, he or she will have seen more than 8,000 murders and more than 100,000 other acts of violence on network television. Those figures increase if the home has a VCR.

In the last four decades, many researchers have found that childhood TV violence-viewing significantly predicted adolescent and adult aggression. Even the surgeon general has acknowledged the causal influence of violent media on violent youth. Researchers contend that scientific confidence and the statistical magnitude of the link between media violence and aggression have been clearly positive and have 46 consistently increased over time. They claim the reasons that this information is not generally known is because of a media with vested interests, a misapplied fairness doctrine, and a failure of the scientific community to make the case.

A recent phenomenon in this area of media and crime is the copycat behavior of young people after watching violent video games. In these same years, the research on negative effects of violent video games on children has become more persuasive. While several states and municipalities have passed legislation designed to provide parents with information and to restrict sales to children, the video industry has repeatedly gone to court to block the enforcement of such laws.

To support their claims that violent video games have no effect, the video industry often cites critics of media violence research, many of whom have never conducted any original empirical studies.

Finally, sports and video games are closely tied. EA Sports produces and sells video games. The 2K11 website, which is rated “E” for “Everyone,” immediately launches into a promo for a hockey video, during which there are 12 instances of players crashing into each other in the course of 56 seconds.

47

CHAPTER III—DOMESTIC VIOLENCE

WHAT IS DOMESTIC VIOLENCE?

Jones (1994) claims that the phrase “domestic violence” is a euphemistic abstraction that keeps us at a dispassionate distance; that it is a bureaucratic designation that gives people a way of talking about a topic without really addressing the reality of human beings in pain. Even the heading “family violence” softens the blow, as it is an oxymoronic term. Jones says we formerly called it “wife beating,” but it was probably changed to reach a gender-neutral “objective” term (81-82). In the language of aggression studies, courtship and marital violence can be defined as “the perpetration or threat of an act of physical violence by at least one member of a dyad on the other within the context of a dating/marital relationship” (Sugarman & Htaling, 1989 in Krahe, 2001, p. 165). Whatever it is called, domestic violence—like rape—is an extremely under- reported crime. In a national sample of 6002 households, Strauss & Gelles (1988) found that one of every six couples has experienced a physical assault—meaning that 8.7 million couple experienced an assault that year. They also found that although men and women both perpetrated acts of violence, the consequences of their acts differed. By more often using guns, knives, or fists, men inflicted more pain and injury than did women.

Another term IPV (Intimate Partner Violence) was the preferred term in the

Senate Judiciary Committee’s 1992 report, “Violence Against Women: A Week in the

Life of American Women (in Iyengar et al., 2008). Ivengar et al. contend that, although this report graphically described 200 incidents of violence in one week alone and federal efforts have increased awareness of domestic violence as a serious crime, there has been 48

“only limited willingness to treat domestic violence as a public health issue” (1). They suggest that because the criminal justice response is lacking, most research largely comes from medical settings such as emergency rooms or community health programs.

Intimate Partner Violence does illustrate the kind of violence that women most experience. As opposed to the perpetrators of violence against men, who are only 16.2% known to their victims, 64% of women who reported being raped, physically assaulted, and/or stalked since the age of 18 were victimized by a current or former husband, cohabitating partner, boyfriend, or date (Tjaden & Thoennes, 2000). Further, the risk of injury increases among female rape and physical assault victims when their assailant is a current or former partner. In fact, the United States Centers for Disease Control (CDC) and the American Medical Association have recognized domestic violence as a major health problem affecting more than 32 million Americans (Tjaden & Thoennes, 2000).

Whatever name is applied, the damage is real. Domestic violence is the leading cause of injury to women in the United States. “According to the National Clearinghouse on Domestic Violence more women are treated in emergency rooms for battering injuries than for (nonmarital) rapes, muggings, and traffic accidents combined.” (Jones, 1984, p.87)

Studies that looked for risk factors of domestic violence note other demographic variables than gender (Krahe, 2001). Low socio-economic status has also been linked to an increased risk of partner abuse, “reflecting the impact of external stress” (p. 167).

Krahe (2001) also points out that clearly partner abuse is a complex phenomenon and that it cannot be attributed to single risk factors. Based on an examination of previous 49 typologies, Holtzworth-Munroe & Stuart (1994, in Krahe, p. 168) proposed an integrative typology that distinguishes between three types of male batterers:

• Family-only batterers, whose violent behavior is restricted to members of their

own family, who do not show signs of psychopathological disorders, and whose

violence is generally less severe. This group is estimated to account for 50% of

male batterers.

• Dysphoric/borderline batterers, whose violent behavior is rooted in emotional

instability and psychiatric disorders, whose aggression is concentrated on their

family, but extrafamilial violence and criminal behavior occur occasionally.

About 25% of men abusing their partners are estimated to fall into this group.

• Generally violent/antisocial batterers, who show violent behavior both within and

outside their family and who engage in sexual and psychological aggression in

addition to physical violence. Their general tendency towards violent behavior

makes them likely to have a criminal record. This group accounts for the

remaining 25% of batterers.

While these typologies provide a description of the batterer breakdown, it is unclear how media violence would factor into this breakdown. While some media violence studies show that the media effect of violence is stronger on those with a proclivity toward violence, sports’ fan aggression may operate differently. To this point, Bandura et al.

(1963) found an absence of any relationships between rating of children’s predisposition to aggression and their aggressive behavior in an experimental setting. This could be the case in both the hooligan setting (stadium violence) and in copycat violence. This 50 typology is included to provide a picture of the batterer, but further study on the “media- generated hooligan” could address this typology.

PROS AND CONS

Jones (1994) contends that the system is set-up so that men expect not to suffer consequences from the law. Every Sunday, there are clear examples of football players who have “gotten away with it.” Benedict & Yaeger (1998) showed that 21% of the players in the NFL have been charged with a serious crime. Even so, there they are, wearing those uniforms and having their close-up pictures displayed—position by position, player by player--on the television at the beginning of each game…as heroes.

Average sports fans identify not only with their favorite teams, but with individual players as well. This is evidenced by team jerseys sold across the United

States (and the rest of the world) with names of sports heroes on the back of the jersey.

Highly-identified sports fans do it even more so.

In 2003, NBA superstar, Kobe Bryant, was accused of rape by a 19-year-old hotel employee. Bryant was formally charged with sexual assault, but the charges were dropped. Even so, Bryant issued an apology to his accuser and settled out-of-court with an undisclosed sum (MSNBC, 2004). The incident did nothing to taint his name, because a year after the allegations, Bryant was re-signed by the Los Angeles Lakers for seven years and $136 million. He also regained several of his endorsement contracts from

Nike, Spalding, and Coca-Cola (Badenhausen, 2004). Further, his fan base is stronger than ever—his jersey is not only the top selling NBA jersey in the United States, but also in China, where the sales have surpassed even those of China’s own NBA star, Yao Ming

(NBA, 2007). 51

The Bryant story is included to illustrate that being accused of a crime or having a criminal record appears to have little effect on fans’ affection, when the player is of superstar stature or at the very least, a strong contributor to his team’s success. Ray

Lewis, a linebacker for the Baltimore Ravens of the NFL was accused of murder, but those charges were also dropped. Lewis was charged with obstruction of justice and sentences to one year’s probation. He was also fined $250,000 by the NFL (Goldberg,

2000). In 2010, however, the city of Baltimore renamed its North Avenue to “Ray Lewis

Way,” in honor of their fierce football hero and his contribution to both charity work and the team’s success (Hensley, 2010).

These sports heroes are frequently involved in domestic violence cases. During the time Benedict & Yaeger conducted their research, Jimmy Johnson was the head coach of the Miami Dolphins. Johnson signed running back Lawrence Phillips to a contract, even though Phillips had just been released by the St. Louis Rams for violating team rules

“fifty-six times” (100). During his nineteen months with the Rams, Phillips had been arrested three times and had served a jail sentence for domestic violence. When asked by the media about Phillips’s past, Coach Johnson said “…things that you hear are highly, highly exaggerated.” (101)

Even though Phillips had been accused and convicted of three instances of domestic violence, these crimes paled in comparison to those of some of his teammates-- one of whom had been investigated for murder, another admitted to being a member of the Swan Bloods. Also, Phillips was in good company because on this very same team, the other running back, Irving Spikes, had plead no contest to battery for besting his wife 52 in 1996 and wide receiver Lamar Thomas had been arrested multiple times for domestic violence in 1996 and 1997.

Previous to joining the Dolphins, Lamar Thomas battered his pregnant girlfriend in front of witnesses. He choked, scratched, and beat her on the arms. He also caused

$700 worth of damage at the house where he and his girlfriend were guests. He was released by Tampa Bay, but then later given that second chance by Jimmy Johnson.

Three weeks after signing a contract with the Dolphins, Metro Dade Police (113) were dispatched to his girlfriend’s house. He had beaten her while she cared for their six- week-old son. There were no reported disciplinary measures taken by the team.

While not every accusation or arrest makes the national news, certainly local news reports would carry news on their local sports heroes. Fans would be aware of domestic violence charges against the players on their favorite teams. Fans would also be aware that the players had either not suffered any consequences or had felt little repercussion from the accusations or the arrests. Of the 150 domestic violence complaints made against professional athletes between 1990 and 1996, only 28 brought convictions—mostly resulting from plea bargains. Just as with non-athlete domestic violence cases, the overwhelming majority went unprosecuted because of the wishes of the victims. Only ten of the 150 were resolved by a criminal trial, six of which led to a guilty verdict. Out of those six guilty verdicts, four involved a case in which the victim was either killed or threatened with death (Benedict, 1997). While this is not an unusual clearance rate--according to the Uniform Crime Report, violent crime clearance rates are

44% (Surette, 1998)—its importance lies in the fact that the players did not face team sanctions. It makes the priorities of the teams very clear—winning is everything. 53

“GO O.J. GO!”

As previously noted in chapter one, the most famous case of domestic violence as allegedly committed by a football player is the O.J. Simpson case. New York Magazine ran a picture of O.J. Simpson that was doctored to show him winking and giving a

“thumb’s up” (O’Brien, 1995). The caption next to the picture read, “Getting Away

With It.” Simpson was found innocent of the murder of his former wife, but this does not negate the history of domestic violence calls.

On New Year’s Day in 1989, the Brentwood (California) Police Department received a 911 call from the Simpson estate. The wife of Simpson came running toward police, saying, “He’s going to kill me, he’s going to kill me” (Gibbs et al, 1994).

Simpson—dressed in a bathrobe—yelled at the police, “The police have been here eight times before and now you’re going to arrest me for it?” The city attorney of Los Angeles charged Simpson with spousal battery, but NBC Sports still signed him to a broadcast contract three months later.

The message is clear—sports heroes are often above the law. Police are often hesitant to arrest these heroes and fans are willing to accept their behavior. When

Simpson was leading the Los Angeles Police Department in the low-speed chase that was watched by millions of Americans as it took place, fans were seen on the overpasses with signs that read, “Go O.J. Go!” Simpson was running from police, yet he was being treated as though he were running from an opposing defense.

54

DOMESTIC VIOLENCE IN PHILADELPHIA

The year chosen for this dissertation—2009—saw a decrease in crime from the previous year in the city of Philadelphia. The aggregated numbers for aggravated assault, rape, and homicide all showed a decrease by 10.2%, 13.4%, and 8.4% respectively. The aggregated numbers for domestic violence are comprised of “domestic violence arrests.”

The numbers used for this dissertation research are “domestic violence arrests.” Overall, in the year 2009, there were 75, 752 domestic crime incidents.

Looking at the grand total of incidents, the greatest number of incidents occurs on

Sundays. One could surmise that this number is inflated because the early morning numbers would count on Sunday, but the behaviors leading to the police call could have begun on Saturday night. Saturday holds the second highest number of incidents. The hour between midnight and 1:00 am is the hour with the highest average number of incidents (778), but the second highest number of incidents occurs between 4:00 and 5:00 pm.

CHAPTER THREE--SUMMARY

Domestic violence is the term used now to describe the physical abuse experienced by family members perpetrated by family members—it is the perpetration or threat of an act of physical violence. It is an extremely under-reported crime. Both men and women perpetrate acts of physical violence, but by using guns, knives, or fists, men inflicted more pain and injury than do women. Domestic violence is the leading cause of injury to women in the United States.

Many so-called sports heroes have been accused of domestic violence. Some of the battering incidents took place in front of witnesses, yet these National Football 55

Players in question were not convicted as batterers. Football “heroes” have been accused or domestic violence, rape, and even murder with highly publicized cases and tend not to lose their popularity among highly-identified sports fans.

In the city of Philadelphia, there were 75, 752 domestic crime incidents in total.

For the five categories of domestic violence arrest in this study, the highest number of police calls-for-service in an average week occurred on Sunday, in the early hours of the day. The second most dangerous time of the week is Sunday afternoon, between 4:00 and 5:00. 56

CHAPTER IV--PREVIOUS STUDIES

FOOTBALL AND FAN-AGGRESSION STUDIES

Three similar studies on football fans and domestic violence have been conducted.

Two of these three studies employ a methodology based on the theoretical framework of the copycat/mass media violence model. This dissertation will also be based on the copycat/mass media model. The differences and similarities among the studies and this dissertation will be discussed in detail.

In their journal article, “The Impact of Professional Football Games Upon

Violent Assaults on Women,” White, Katz, and Scarborough (1992) postulate “the viewing of successful use of violent acts may give the identifying fan a sense of license to dominate his surroundings.” They found—as did Sachs & Chu (2000) in their similar study—a relationship between victories by the home team and battering of females.

The study by Sachs & Chu, “The Association Between Professional Football

Games and Domestic Violence in Los Angeles County,” (2000) looked at the viewing of

Los Angeles Raiders’ and Los Angeles Rams’ games. As they note, while Super Bowl

Sunday is often mentioned in “street lore” as the biggest day of the year for domestic violence, few scientific studies support this claim. Sachs & Chu point to White, Katz, and Scarborough’s study as the only one previously addressing the relationship of pro football games to domestic violence.

Most recently, supported by a grant from the National Institute of Child Health and Human Development, two economists looked at the problem with another approach.

David Card and Gordon B. Dahl (2009) contend that negative emotional cues— 57 benchmarked relative to a rationally expected reference point—make a breakdown of control more likely. In other words, the unexpected emotional cues of watching a

“favorite football team” lose could trigger violence in violence-prone families. While

Card & Dahl (2009) showed findings that support their theory, the methodology differs from the methodology in this dissertation, which will be based on the mass media violence/copycat model adapted by both the Sachs (2000) and White (1992) studies.

Even though their theoretical frameworks have the same origins, the Sachs and

White studies, while tackling the same subject, differ slightly in methodology. Sachs &

Chu conducted an exploratory ecological analysis, examining three years of computerized data that measured arrests. For the Los Angeles County Sheriff

Department (LASD), arrests are known as “RAPS,” which stands for Regional Allocation of Police Services. All calls for help with a domestic dispute to the LASD generate a dispatch (Sachs & Chu, 2000).

Sachs et al. (1998) showed that in a previous analysis of LASD dispatches for domestic violence calls, there was an increase of approximately 40% over the time period studied and showed a seasonal trend. To control for the increase and the weekly and seasonal variations, the authors examined the percentage change in domestic violence dispatches from Wednesdays to Sundays, during weeks when professional football games were played. They then compared the results to “reference” weeks, during which no football games were played. Sachs & Chu (2000) used a Wilcoxon Rank-Sum test to determine any association between football season weeks and nonfootball season weeks.

(They note that sample size for playoff weeks and Super Bowl weeks were insufficient for statistical testing.) 58

Their results showed inconsistencies. During the first season (1993-1994) football Sundays increased an average of 100% from previous Wednesdays, compared to an average of 68% during nonfootball Sundays (1195). This result bordered on statistical significance. Overall, however, their analysis failed to show any statistical increase in

RAPS during selected days of professional football games for the entire study period.

In their discussion, Sachs & Chu (2000) acknowledge that while increases in playoff weeks, the Super Bowl week, and during the first season were high, but the second season clearly negated the effect, because the 1995-1995 season showed a decrease. They propose that one possible explanation for the conflicting results is “the impending loss of two local football teams” during the second year. As they indicate, a necessary part of the hypothesis is watching football. If the teams were considering a move, local interest would naturally wane (as witnessed in New Jersey Nets’ attendance after the announcement of their impending move to Brooklyn).

For the second possible explanation of their findings, Sachs & Chu (2000) hark back to the aforementioned hypothesis of White et al. (1992), that domestic violence occurs more often when the male perpetrator’s teams wins. During the 1993-1994 season, when there was an increase observed in RAPS, the Los Angeles Raiders had a winning season and advanced to postseason play. The following year, neither Los

Angeles team had a winning season.

In their discussion of this article, Sachs & Chu (2000) have omitted two major factors that could have skewed their results. This key explanation must be suggested here: the connection between waning fan interest and lack of media coverage. The

National Football League has a black-out rule, which prevents the local broadcast of 59 home games that are not sold-out. With many non-sellouts, the Los Angeles Rams were frequently not broadcast locally during both seasons, but more often in the second season.

The study should not have included Rams game-days because so few people were even watching. Further, if the Rams’ games were not broadcast, then the only local fans who would have witnessed the games were those in attendance. The RAPS numbers in the study were for Los Angeles County. The Los Angeles Rams, although they kept the “Los

Angeles” in their names, had played their home games in Anaheim since 1980. The study considers the arrests for Los Angeles County, but Anaheim is in Orange County.

One is hard-pressed, therefore, to see any relation between the Rams and the area of study.

In their section on “Limitations,” Sachs & Chu (2000) state, “As with any ecological analysis, causation cannot be proven, and any association between the timing of professional football games and domestic violence dispatches may be due to other unmeasured factors.” This is true, but Sachs & Chu would have had a stronger study if they simply better understood media consumption and sports. Even with the flaws, they did find near-statistical significance during the first season, when in fact, the Raiders were winning. Perhaps without the cloudiness of the Rams’ game-days and looking at these numbers during all winning seasons, their findings would be more in line with the findings of White et al (1992).

One last point on the Los Angeles study: both professional football teams left southern California after 1995. The National Football League has attempted to bring professional football back to the area since then, without success. Los Angeles fans have made no outcry for a team and the local government has not tried to appease the NFL by 60 building or even investigating the possibility of building a suitable new stadium. It is quite possible that—for whatever cultural reason--the identification with professional football in the southern California area is weaker than in other regions of the United

States. The Washington Redskins, for example, provide a better case study because they are popular and they are the only pro football team that plays in the Washington, D.C. television market.

As previously mentioned, there has been one other study examining the relationship between professional football games and violent assaults upon women. This dissertation by White, Katz, & Scarborough (1992) looked at the association between the timing of Washington Redskins’ football games and the frequency of emergency room admissions in northern Virginia. As in this dissertation, White et al. (1992) suggest that

“one immediate contributor to assault may be presentations of violence in the media

(television and motion pictures). Violence displayed on television may suggest that violence can be rewarding” (159). White et al. (1992) propose “If exposure to violence produces violent behavior in the viewer, then the broadcast of professional football may lead to an increase in violence, especially in geographical areas which have the greatest interest in the events.”

The research measured emergency room visits as an indicator of assaults on women, citing a study that showed 21% of women using emergency surgical services were victims of assaultive acts by male partners (Frieze & Browne, 1989). Additionally, the authors stated that anecdotal studies from battered women’s shelter workers “report a perceived increase in assaults by partners after professional football games” (160).

White et al. hypothesized: 61

…media presentations of sports-related violence such as football games may acts as triggers for violent activities among violence-prone men, stimulating aggression against convenient targets, in many cases their spouses and women companions (1992).

White et al. list four advantages of their study (160). Given the similarities between the

Redskins study and this dissertation, it is important to list the advantages and equally important to list the limitations.

ADVANTAGES AND LIMITATIONS

White et al. list four advantages of their study (160). Given the similarities between the Redskins study and this dissertation, it is important to list and contrast the advantages and equally important to list and contrast all the limitations.

ADVANTAGES

1) A) White et al. point out that by examining emergency room admissions, it is not

dependent on self-identification as a victim of abuse (Warshaw, 1989; Stanko,

1985; Stark & Flitcraft, 1988). The most salient advantage here, therefore, is that

it removes the onus from the victims to label their injuries as abuse.

B) In this study, the dependent variable is a domestic violence arrest. The onus

may or may not have been on the victim to call the police. The police could have

been called by a neighbor, friend, or relative. Pennsylvania does not have

mandatory arrest for domestic violence—arrest is at the discretion of the police

officer—so at some point, it is likely that the victim self-identified.

2) A) The authors say the study is not dependent on interpretation of events by

either the victim or the offender (160). This proves to be advantageous because

research on battering has often used the victim as an informant. This has proven

disadvantageous because women may minimize the frequency or seriousness of 62

attacks or “may blame themselves, or factors outside the offender’s control (e.g.

alcohol) rather than locate the cause of the assault in their husbands or lovers”

(161).

B) This advantage does not hold true for this dissertation. The study is dependent

on the interpretation of either the victim or the arresting police officer.

3) A) White et al. assert that studies that focus on unique interactions between

intimate partners (Strauss, Gelles, & Steinmetz, 1980) have the danger of holding

the victim at least partially responsible as she is part of the interaction which

eventually erupts in violence. White et al. assume the opposite (161).

B) Again, that advantage would not hold true for this dissertation—in order for

the incident to have been recorded by the police, the victim has to be questioned.

Further, White el al. assume that the victim is not held at least partially

responsible for the violence, but they have no way of knowing what happened at

the hospital or on the way to or even from the hospital. Finally, the domestic

violent incident as described by the police report is far more detailed and directly

labeled as such.

4) A) The authors say that their study applies research performed on criminal

violence to family violence (Fagan, 1989).

B) This dissertation looks solely at domestic violence arrests perpetrated by a

male offender on a female victim, living in the same domicile.

63

LIMITATIONS

1) A) White et al. (1992) acknowledge that by examining trauma admissions, they

are also detecting traumas produced by other kinds of assaults or those caused by

someone who has no knowledge or identification with football games.

B) This limitation could very well be true of this dissertation—these domestic

violence incidents could have absolutely nothing to do with televised football

games. This, of course, is always a problem in social science research. In this

dissertation, however, the limitation is not quite as great as that of the White

study. By examining domestic incidents—as defined by the police—the assaults

are probably not caused by someone falling down or being hit by a car, etc.

“Arrests for domestic incidents” is a much stronger dependent variable than

trauma admissions for unknown causes.

2) A) The authors note that battering can include a variety of activities including

physical assaults, emotional abuse, destruction of property, sexual assault, and

repetitive actions. In essence, the study is limited to those physical assaults

serious enough “to force the victim to seek medical attention” (1992).

B) Likewise, in this dissertation, the information is limited to only those cases in

which the police have been involved. Unlike the White et al study, however,

there is more of the emotional abuse measured in this dissertation. Two of the

categories name violations of protection from abuse orders as domestic incidents.

Further, the category of simple assault may or may not involve a wound that 64

would be serious enough for medical attention. This dissertation is likely to

capture more of those incidents.

3) A) The final limitation listed states that emergency rooms are not the only place

one can seek medical care. Because private doctors are not included in the study,

White et al. (1992) assert that there is the possibility of a class bias in the sample.

With any study of domestic violence, there is the chance that women with greater

socio-economic resources will turn elsewhere for help and not rely on public

services like emergency rooms or the police.

B) Ostensibly, this limitation would not be present in this dissertation, because

police services are equally available. If, however, the assertion of White et al.

(1992) is correct, that women with greater socio-economic resources will turn

elsewhere for help, again we would not be capturing all the domestic violence

incidents that could be occurring.

ADDITIONAL LIMITATIONS AND ADVANTAGES

As opposed to the White et al. (1992) study and the Sachs & Chu (2000) study,

the domestic arrests numbers are limited. In both of those studies, the domestic

violence measures spanned a greater area. The Philadelphia Police Department

serves only a portion of the area where the Eagles’ fans live. The Philadelphia

television market reaches far into New Jersey, so thousands of homes would not be

measured.

Even with this limitation, the dependent variable is this dissertation is, in fact, stronger than that of the two previous studies. The advantage of being able to pin-down a time—to the hour--for the incident makes it much more reliable than just looking at the 65 aggregated numbers for an entire day (Sachs & Chu, 2000) or an entire day’s worth of hospital admissions (White et al. 1992).

CHAPTER FOUR--SUMMARY

At the time this research began, two previous studies had examined the relationship between professional football and domestic violence. One study used police data to assess the number of domestic violence calls-for-service in the Los Angeles area on a weekly basis—comparing “football” weeks to “non-football” weeks. The researchers found results that were close to significance, but they had design flaws that they did not realize.

The other study examined trauma admissions in local hospitals in the television viewer area of the Washington Redskins. Here, they found statistical significance, but their dependent variable was not strong. It was impossible to discern why these women had been admitted for trauma—whether or not it was domestic violence was not known.

Both of these studies utilized the copycat/media framework developed by Phillips.

Some of the limitations of this design include: a) the domestic violence could have been the result of another factor and had nothing to do with football (which is always an issue in social science research), b) the results are limited to only what has been reported to the police or come from hospital data that cannot be desegregated. 66

CHAPTER V--THEORETICAL FRAMEWORK

For White et al. (1992), the incidence of trauma was determined by the number of appearances in emergency rooms in the northern region of Virginia (161). Admissions were coded for mechanism of injury, gender of victim, race of victim, and for the date of arrival; the data were then consolidated into daily counts to form time series sets over two-year periods.

This dissertation draws on elements of both the study from northern Virginia and from the Los Angeles study. Additionally, the design has been influenced by the “Mass

Media Violence and Aggression” (1986) studies conducted by David P. Phillips and by

“Clustering of Teenage Suicides After Television News Stories About Suicide,” (1983) by Phillips & Carstensen. Phillips’s work has been influential in the arena of media and violence. One of the misunderstandings that criminologists may have regarding his work is that it is focused on suicides and therefore does not seem to fit within the purview of criminal justice studies. On the contrary, Phillips explains that he examines media’s effect on suicide as opposed to homicide solely because suicide is much more common than homicide in all industrialized countries (1986). Even in a country with as much violence as the United States, suicides are much more common each year than are homicides. Phillips’s work deals with fatal antisocial behavior with media as a trigger.

For the purpose of this dissertation, media provides the trigger, but the violence is domestic violence.

Phillips (1986) asserts that while rigorous laboratory testing offers “an unparalleled technique for precisely controlling the effects of extraneous variables,” the 67 artificial setting comes with a high cost (260). In an earlier work (1983), Phillips makes the excellent summation of this issue regarding mass media studies:

Typically, the sorts of aggression studies in a laboratory (like hitting plastic dolls or inflicting electric shocks) have not been representative of serious, real-life violence, such as murder or rape. In almost all of these studies, the laboratory subjects have been nursery school children or college students and thus not representative of the U.S. television audience. Typically, the laboratory subject is presented with a brief, violent excerpt of a television program. In contrast, the “real-life” viewer may watch several hours of television at a sitting, and the violence may be interspersed with humor, commercials, and trips to the bathroom. In contrast to the laboratory subject, who watches television alone, the real- life viewer may be surrounded by family or friends. Their comments may distract from the television or shape the perception of its many messages (p.567).

This common sense approach clearly expresses the problem with the laboratory. One might take this concept further and speak of how the interspersion of humor or bathroom breaks or general socialization further normalizes the experience, thereby also normalizing the images being broadcast from the screen.

Phillips (1986) then examines the usefulness of the field experiment to study mass media and aggression. He concedes that although field experiments are “indeed more

‘natural’ than their laboratory counterparts, they nonetheless retain a strongly artificial flavor; this is because the circumstances studied in field experiments are not typical of real life” (1986). Phillips sees four key problems with the field experiment for measuring mass media aggression:

1) With very few exceptions, these studies examine children in institutional contexts,

typically a boys’ home, a reform school, or a nursery school. Phillips states that

Feshbach & Singer (1971) reason that the results from experiments with these

children cannot be generalized to typical children in a typical home. Phillips says 68

the problem goes even further than that, because these results cannot be

generalized to a normative adult either.

2) In the field experiment, the viewing diet is generally imposed on the subject,

whereas in the real world, the subject chooses what he or she views. [Author’s

note: this may show a proclivity toward violence in and of itself, if the viewer

consistently watches violent media.]

3) In the field experiment, the subject generally knows he or she is under observation

by [adult] monitors.

4) In the field experiment, the institutional setting and the ubiquitous presence of

adult monitors discourages many extreme forms of violent behavior, such as rape

or murder. Thus, “the field experiment cannot be used to study those types of

violence which are the greatest concern to policymakers in the real world”

(p.262).

Phillips believes that it is possible to avoid many of the aforementioned methodological problems with a “found experiment,” (also known as a naturalistic experiment) suggesting that this type of experiment is well-suited for the examination of a) adults rather than children, b) noninstitutional behavior, c) fatal violence, and d) response to media diets which are freely chosen by the audience, not arbitrarily imposed by the experimenter (1982a).

Phillips asserts that the found experiment and the laboratory are similar in that one can assess the impact of a mass media event by measuring behavior before and after the event occurs—in the real world, after correcting for the influence of extraneous variables, one can determine whether a heavily-publicized murder story is followed by a 69 real-world rise in the homicides in the United States. If, for example, the rise in homicides occurs only after the murder story and not before, and if the rise persists after one controls for other variables, “one then has some evidence suggesting that mass media violence can trigger additional, fatal violence in the real world” (p.262). In conclusion, the found experiment allows the researcher to conduct an unobtrusive examination of the natural impact of mass media stories in the real world. Phillips (1986) acknowledges that the found experiment has weaknesses, but lays out five steps to create a “paradigm for investigating the real-world impact of mass media stories” (p.262).

The five steps of this paradigm are:

1) Generating an exhaustive list of publicized stories concerned with a particular

type of antisocial behavior (Phillips, 1986). In the case of this dissertation, the

“media story” is a considerably different type of media exposure, but a media

event nonetheless. In this dissertation, an exhaustive list should be made of the

broadcasts of professional football games in the region and from the time

period in question.

2) Identifying a data set that provides information on antisocial behavior of this type

in the real world. For the Los Angeles study, arrests filled this requirement; for

the northern Virginia study, emergency room visits filled this requirement; for

this dissertation, domestic incidents will be the antisocial behavior examined.

While it is not a one-to-one relationship as in Phillips’s studies regarding

homicide data sets after homicide stories, the relationship here is watching

successful violence on the field and then measuring off the field violence. 70

3) Developing a technique for controlling for the influence of extraneous variables.

Phillips says that generally, two basic techniques have been used, sometimes

alone, sometimes in combination. The first technique compares an experimental

period with matched controls; the second technique used regression analysis to

correct for the effects of extraneous variables. In this dissertation, matched

controls will be used, i.e. domestic violence arrests from other, “non-football”

days..

4) Generating and testing predictions, which should hold if publicized antisocial

behavior triggers imitative activity. For example, if such imitative activity exists,

one would predict (a) a rise in antisocial behavior just after the story (but not

before); (b) a particularly large rise if the story is heavily publicized; and (c) no

rise in antisocial behavior in those geographical areas where the story is not

publicized. For this dissertation, the prediction would be for an increase in

domestic violence arrests within 8 hours after the broadcast of a specified

professional football game. The game will be heavily publicized, so there is a

slight digression from the paradigm here and for the third requirement, the

geographical aspect is removed and the comparison goes to non-game-days and

further, wins and losses.

5) Generating and testing alternative hypotheses which may be capable of

accounting for the observed findings. Obviously, if several sets of competing

hypotheses are all consistent with the data, confidence in any of these hypotheses

will be diminished. A possible bias chart and the intended remedies will be

listed in the design section of this dissertation. 71

COPYCAT CRIME/MEDIA VIOLENCE FRAMEWORK

With the Phillips framework for copycat theory, there needs to be a theoretical mechanism, a “trigger.” Numerous theories explain why the study of television violence is important and how it may affect viewers, especially children. Two of these theories are: Desensitization (Potter, 1999) which posits that watching violence leads to insensitivity and callousness and Cultivation theory (Gerbner et al., 2002) looks at viewing violence from a cumulative, long-term perspective. It posits that television violence illustrates and provides lessons about power, which in turn contribute to viewers’ perceptions of the world as a mean and scary place and their own chances of being a victim or perpetrator of violence.

The theory most applicable as a trigger for the copycat/media violence framework of this dissertation is: Social learning-cognitive theory (Bandura, 2002). This theory predicts that viewing violence provides viewers with potential scripts or models of violent behaviors or reactions to them and may teach viewers to behave aggressively.

Social learning-cognitive theory provides the “trigger” for copycat theory. The scripts or learned behaviors are emulated.

Although children, in particular, are likely to be affected by messages of violence, copycat theory applies to adults as well. For children, these messages may be particularly salient if those depicted in the violent images are children or adolescents. Similarly to these findings with children, highly-identified sports fans could react to the violent actions of their heroes, captured—live--on television.

Like the youths from Long Island who attributed their behavior to emulating the

“protagonist” from Grand Theft Auto IV, a 16-year-old California boy, who killed his 72 mother, admitted to investigators that he got the idea from the movie Scream. A

Kentucky high school student killed three students and wounded five others based on a scene from the movie Basketball Diaries (Boxer et al, 2009). The film Menace II Society has been cited by a trial judge for providing a script for two youths accused of robbing and killing a motorist; the same movie motivated four teen boys to steal a car, wound one man, and kill another, according to what they told authorities (Surette, 2002).

The first person to offer a theoretical discussion of copycat crime was Gabriel

Tarde in the late nineteenth century (Surette, 2007). He coined the term “suggesto- imitative assaults” to describe the observation that sensational violent crime appeared to prompt similar incidents (Tarde, 1912). Tarde concluded, “Epidemics of crime follow the line of the telegraph.”

Social scientists, however, came to largely ignore Tarde’s writings, as they saw imitation as too simple or less cognitively demanding (Surette, 2007). It was not until the

1970s that criminologists began to reconsider the theory when a surge of copycat crimes involving airline hijackings and media interest (Akers, 1998). Bandura referred directly back to Tarde’s writings and attributed copycat crime to a process of simple and direct imitation based on social learning principles (Bandura, 1973).

Even with this resurge of interest in Tarde’s theory, imitation—in and of itself-- was criticized as too simplistic to fully explain copycat crime; for example, it failed to explain why most children imitate aggression within socially acceptable limits and only a few imitate aggression with a real gun (Surette, 2007). Critics also noted that imitation theory focuses on the copycat criminal and tends to downplay other social factors. The primary flaw in imitation theory is that it generally implies that the copycat behavior 73 must physically resemble the portrayed behavior and therefore, falls short in explaining any generalized effects or innovative applications (Surette, 2007).

COPYCAT RESEARCH

Surette says that anecdotal reports of copycat crimes regularly appear in the news, but that public concern over criminogenic effects of the media exists within a sparse and empirically weak research environment (2002). He claims that copycat research is complicated by the fact that individuals at risk for copycat influences have been difficult to identify, isolate, and study. He also acknowledges that the “slowly growing” file of anecdotal reports does, in fact, indicate that criminal events that are rare in real life are sometimes committed soon after similar events are shown in the entertainment or news media. Further, within the academic literature about terrorism, for example, there are no doubts about the media’s ability to motivate copycat terrorist acts (e.g. see Poland, 1988).

Surette—one of the few researchers in the field of criminology to study copycat crimes—states that the anecdotal cases in combination with research on media-copied suicides and studies of the effects of news coverage “establish reasonable grounds that copycat crimes occur, but at an unknown rate” (2002).

In the copycat crime literature, Wilson and Herrnstein (1985) implicated media consumption with low academic achievement, as related to media-induced juvenile criminality. Heller & Polsky (1976) and Pease & Love (1984a, 1984b) suggested that

“offenders who held attitudes toward the media as useful and influential would be associated with copycat behaviors.”

In the fields of psychology, sociology, and cultural studies, copycat behavior is generally better known. David P. Phillips has conducted much research over the years on 74 the “clustering of suicides” after news stories and other televised programs. (The work of

Phillips will be further discussed in a later section.) Sociologist Donna Gaines says that-- clearly—the cluster effect of teenage suicide can be linked to copycat behavior. Soon after a successfully carried-out “suicide pact” made national news (Bergenfield, NJ,

1987), more suicide pacts followed—both across the country and in Bergenfield--until finally the Bergen County Prosecutor’s office refused to allow the release of any more information to the media. She contends that—through media depictions:

Death has taken on new meaning in the last 20 years. To the post-modern imagination, suicide is titillating. It is the last great taboo. Having exhausted sex, death by suicide or homicide becomes the final frontier of sensate experiences; new pleasures (Gaines in Spina, 2000).

Although, as Surette suggests, that those individuals at risk for copycat influences may be difficult to isolate, they exist. With the mechanism being social learning, the emergence of an effect depends on the interaction between each individual, the content of the media, and the setting in which exposure occurs (Surette, 2002).

MECHANISM

As mentioned in the preceding section, the bulk of other relevant but noncopycat crime and media research focuses on media and aggression and on the effects of the visual media (Surette, 1998). Relevant for copycat crime, however, this media and aggression research has posited a stimulating effect and has explored a number of mechanisms through which the media can cause aggression (Wilson & Herrnstein, 1985).

The most commonly advanced mechanism, however, involves social learning, imitation, and modeling processes (also, “scripts”) by which viewers learn values and norms supportive of aggression and violence, techniques to be aggressive and violent, and/or 75 acceptable social situations and targets for aggression and violence (National Institute of

Mental Health, 1982, pp.38-39, Bandura, 1994 and 2003).

There are multiple cognitive paths between the media and criminality that copycat criminals can take. Social cognition theory provides two paths: 1) a systematic central path that requires a copycat offender to evaluate information and is likely related to instrumental planned copycat crimes such as bank robbery; and 2) a heuristic peripheral path that is quickly traveled with little information evaluation and likely leads to emotional spontaneous copycat crime such as an impulsive assault or hate crime (Shrum,

2002). A third path may be narrative persuasion from entertainment media content

(Green and Brock, 2000). This path is qualitatively different from the first two paths and involves an absorption of media interaction. The theoretical framework of this dissertation focuses on the social cognition theory, but the narrative path does include the

“empathy or identification” aspect that comes from the narrative path (highly-identified sports fans).

An important step in this process comes from “priming,” (Dijksterhaus and

Bargh, 2001) which holds that portrayals of certain behaviors in the media activate a cluster of associated ideas within the potential copycat offender that increase the likelihood that he or she will behave similarly but not necessarily identically.

Finally, to expand on the concept of scripts—cognitive scripts serve as a guide for behavior by laying out the sequence of events that one believes are likely to happen and the behaviors that one believes are appropriate in particular situations (Huesmann, 1998).

According to Surette, the following flowchart represents how media/copycat crime occurs: 76

TABLE 1—MEDIA GENERATED CRIME

MEDIA GENERATED CRIME

leads to 3 paths…

PATH 1—Systematic Central Processing Instrumental Copycat Crime

PATH 2—Heuristic Peripheral Processing Emotive Copycat Crime

PATH 3—Narrative Persuasion Transportation and

EngagementEmpathy or Identification

All of these paths lead to:

Priming and Script ActivationCopycat Crime

PerformanceConsequences: Rewards or PunishmentSocial Effects

(Surette, 2010) 77

HYPOTHESES

HypothesisA: During the 8-hour period following “kick-off” on a televised Philadelphia Eagles game, arrests for domestic violence will be greater than the average call for day of the week and time of day, for the calendar year of 2009.

HypothesisB: Domestic violence arrests will be equal following Eagles home games and away games.

HypothesisC: Domestic violence arrests will be greater following wins than losses.

HypothesisD: Domestic violence arrests will be greater following games vs. rivals than following games vs. average opponents.

HypothesisE: Domestic violence arrests will be greater following playoff games than following regular-season games.

HypothesisF: Domestic violence arrests will be equal to the number of arrests on a holiday associated with socializing and the drinking of alcoholic beverages.

HypothesisG: Domestic violence arrests will be greater following football games than following hockey, basketball, and baseball games.

The flow chart of the following page attempts to include some innovative applications—innovations that Surette has suggested have been missing by viewing copycat theory as simply a theory of imitation (2010). This chart integrates the theories from the literature review of this research and the copycat/media framework and it includes the mechanism. While all the branches of this flowchart are important to this dissertation research, the shaded portions represent the main areas of study for this ecological time trend analysis, which attempts to find an association between televised, professional footballs games and domestic violence in the city of Philadelphia. 78

SOCIAL IDENTITY = FAN (Shank & Beasley , 1968)

HIGHLY IDENTIFIED CASUAL FAN FAN

BIRG or CORG BIRG or cannot CORF or CORF

ELABORATED SOCIAL IDENTITY MODEL (Reicher , 2001)

o t e T c e n s p l e d r e r r o v a a v is e d id h n e a e d d t v a s i Im r d o e n l a t a e g a n e re s t s s G rm c r o ip n p ts u ro G

HOOLIGANISM MASS MEDIA OR OR SPECTATOR VIOLENCE COPYCAT VIOLENCE (Philips, 1986)

SOCIAL T A N T E S IDENTITY V P E O D E AND G E V R N S E T I I e N I T V iv N REDUCTION E it T G R L n O E OF P g S T o -C ) PRIVATE SELF g 2 in y 0 r 0 r n o 2 AWARENESS a e , h e T r a L u l d ia c n o a BOTH S (B INCLUDED “SCRIPTS ,” BUT SCRIPTS VARY FOR EACH SITUATION THEORETICAL CONSTRUCT 79

CHAPTER SUMMARY

Participation in exclusively male subcultures and male-oriented recreational activities correlates with violence toward wives (Fagan, 1989). Although females can and do participate in observation of professional football games, clearly, the focused audience for these games is men. The question then becomes: Does successfully-perpetrated violence, as depicted in a professional football game, produce copycat behavior in the viewers, specifically against the wives and girlfriends of the football fans?

Phillips developed his copycat framework initially with suicide studies. Surette has become the researcher in the field of criminal justice who has devoted his time to media-oriented violence. For both Phillips and Surette, there needs to be a theoretical mechanism or a trigger. Surette espouses Bandura’s social learning-cognitive theory, which predicts that viewing violence provides viewers with potential scripts or models of violent behavior.

Surette says that while the growing file of copycat cases is growing slowly, the studies that show the effects of news coverage establish reasonable grounds that copycat crimes occur. In the fields of sociology, psychology, and cultural studies this media/copycat behavior is generally better known.

The theoretical framework indicated by the flowchart in this chapter links hooligan studies to media/copycat studies through ESIM (Elaborated Social Identity

Model). The underlying behavior (team-identity) leads to violence but by different scripts. This theoretical framework is a large part of what was tested in this research. 80

CHAPTER VI--METHODS

RESEARCH DESIGN

For this dissertation, the study site is Philadelphia and the professional football team whose broadcasts were the object of examination was the Philadelphia

Eagles. Unlike Los Angeles (at the time of the study by Sachs & Chu, 2000), there is only one pro football team playing within that media market. Also unlike Los Angeles at that time, Philadelphia has a dedicated fan base with sold-out home games, thereby insuring that the games will be broadcast under the NFL’s blackout rules. Like the northern Virginia study, the geographical relationship under study coordinates with a portion of the television-viewing area of the Eagles. Like the Los Angeles study, however, this dissertation examined law enforcement data, specifically five categories of domestic violence arrests, as defined by the Philadelphia Police department, for specific, theory-driven days in 2009 (Philadelphia P.D. 2011). This time span will incorporate portions of the 2008-09 and 2009-10 Eagles’ seasons.

As with the Sachs (2000) and White (1992) studies, this research does not have any personal information on the offenders, nor on the victims’ relationships to the offenders; thus the investigation is of the timing of the games and the linkage of their outcomes to the number of domestic violence arrests. Following the Phillips paradigm for investigating the real-world impact of mass media stories (1986), these matching factors varied for each hypothesis.

The dependent variable--domestic violence--was operationalized by the hourly arrest rates for the five categories of domestic violence arrest. The study compared the 81 means of several independent samples, with the data source for all the samples being the police reports of domestic violence arrests on 69 days in the year 2009, as recorded by the Philadelphia Police Department. The Philadelphia Police divide their domestic incidents into five categories (it is actually six, but the sixth category, “domestic homicide” is not common enough to be a part of the working data). All five categories were totaled during the 8-hour time period from the start of the football games. For the comparison independent samples, the 8-hour time period was recorded beginning at various theoretically driven times.

If individual level data has been available, other factors could have been considered for this dissertation, such as whether or not other men were present during the broadcast, whether the game was watched at home, how much alcohol was consumed, etc. This information, because of both privacy issues and simple because the police cannot keep all of that information in a central location was not available. What is available is the hourly-arrest rates for those domestic violence categories on selected days in 2009.

Although this matching strategy is designed to limit bias, there are always possible biases to consider. Also as Phillips exhorts, alternative hypotheses must be constructed that could be capable of accounting for the observed findings. These alternative hypotheses can address some of the questions of bias. Some possible biases include:

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TABLE 2. DESIGNING OUT BIASES POSSIBLE BIAS HOW DESIGN ATTEMPTS TO ADDRESS BIAS 1) What sets off the violence may be 1) This is why “football days” was compared socializing and drinking alcohol with with non-football days, during which men also other men. socialize and perhaps imbibe alcohol (i.e., holidays). 2) Spectators attending games may be 2) If the home vs. away games produce no the reason for the increased abuse. difference, then the spectator hypothesis is unlikely. 3) Other sports could produce the 3) “Football days” were compared to baseball, same spike in domestic violence hockey, and basketball days—with day of week events. comparisons and “at-stake” comparisons (games against rivals and playoff games constitute “at- stake” games). 4) The possibility that other games 4) Unless a customer buys the “NFL Package,” a would produce the same result as viewer would not be able to watch more than watching an Eagles game, which three total games on a Sunday afternoon (one would lessen the impact of theory of game competing with the other in a timeslot) and copycat theory, based on high- one game at night. Additionally, the other three identification. teams besides the home team would not be the same each week, so it is unlikely that there would be identification with these teams. If there is a noticeable spike from the proposed Eagles’ kick-off and not the other game times, then it could mean it is not a bias.

SAMPLE

The aggregate data comes from the 22 districts that the Philadelphia Police

Department serves. The Philadelphia Police Department is the fourth largest police department in the nation. It is the primary law enforcement agency responsible for

Philadelphia County, extending over 140-square miles, in which approximately 1.5 million people reside (Phila. P.D., 2010). 83

The racial composition of Philadelphia is 42% black and 39% white, with the remaining population of “various races.” In 2009, 18% of the families in the city were living below the poverty level. Fifty-three percent of the population is female.

SAMPLE LIMITATIONS

While the Philadelphia television market is also the fourth largest in the country, as mentioned in the “limitations and advantages section,” there is not a mirror relationship between the geographic area from which the police data were aggregated and the number of people able to watch the Eagles play on television. In order to measure the true number of Eagles’ fans as media consumers of the Greater Philadelphia-South Jersey region, the boundaries for the Philadelphia television market would have to be included.

Television markets are established by the FCC and are defined as areas that receive the same television offerings (Neilsen Media Research, 2010) and in this case, the market certainly is larger than Philadelphia County. The counties that comprise this area are: (in

Pennsylvania) Philadelphia, Montgomery, Monroe, Berks, and Schuykill and (in New

Jersey) Atlantic, Camden, Mercer, and Burlington. Additionally, there are some other small sections of Delaware and Middlesex County included in this D.M.A. (Neilsen,

2010). The data for all of the arrests for domestic violence in this television market were not available for this dissertation, but certainly would bear further investigation.

The lack of data for all of suburban Philadelphia could bias the data in the opposite direction from the proposed hypotheses, perhaps weakening the results. A follow-up study of much greater magnitude would perhaps produce a better picture of the relationship. 84

It is important to note that, although all the possible viewers could not be counted in the collected data, all the viewers in the study would have access to the Eagles games.

As previously mentioned, because the Eagles are sold-out, the broadcasts of their games are not subject to the NFL’s blackout rules.

While the aggregate data of total crimes by day of the week were available to the public, the police records for the 75, 752 “domestics” were not. Permission was obtained through the chief of police for the breakdown of aggregate domestic events and for individual days. The police would not release the domestics for every, individual day in

2009. The days, therefore, had to be chosen judiciously and the 69 particular days were chosen by theory for this dissertation.

DATA

Statistical tests were run that include either apportioned subsets of the following data sets or the full data set, depending on the hypothesis being tested. Data Set I—also called “Football Game Days” included all of the Eagles games and both the Super Bowl and the Pro Bowl (n=20). Data Set II or “Holidays” included major holidays except

Thanksgiving (n=8). On Thanksgiving Day, it is now part of American tradition to show two NFL games—always at least one of which involves the Dallas Cowboys or

“America’s Team.” It would be too difficult to assess whether any domestic violence arrests were influenced by the holiday or the football. Data Set III included Sunday or

Monday games or “big” games or playoff games for the remaining three professional teams in Philadelphia—the Sixers of the NBA, the Flyers of the NHL, and the Phillies of

MLB (n=19). Data Set IV included all the remaining Sundays in the year that were not holidays or a day on which major sporting events were played (n=22). Data Set I-A 85 included all the Eagles’ home games played in calendar year 2009. Data Set I-B included all the Eagles’ away games played in calendar year 2009. Data Set I-C included all the games that the Eagles won in calendar year 2009. Data Set I-D included all the games that the Eagles lost in calendar year 2009. Data Set I-E included all of the games versus the Eagles’ rivals. Data Set I-F included all the games against non-rival opponents in the calendar year 2009. Data Set I-G includes all of the playoff games played by the Eagles in 2009. Data Set I-H includes all of the regular season games played by the Eagles in calendar year 2009.

DATA SETS

I. Domestic violence arrests for the 8-hour period from the start of game time, for the 18 games the Eagles played in 2009. During the 2009 calendar year, the Eagles played three playoff games in January and then played 15 games during the regular season in the fall. “Football Gamedays” also include the Super Bowl and the Pro Bowl DATES: January 4th—Wild Card Game—4:30—W 26-14 January 11th—Divisional Playoffs—1:00—W 23-11 January 18th—NFC Championship Game—3:00—L 32-25 September 13th--@Panthers--1:00--W, 38-10 September 20th—Saints—1:00—L 22-48 September 27th—Chiefs—1:00—W 34-14 October 11th—Buccaneers—1:00—W 33-14 October 18th--@Raiders--4:05--L 9-13 October 26th--@Redskins--8:30--W 27-17 November 1st—Giants—1:00—W 40-17 November 8th—Cowboys—8:20—L 16-20 November 15th--@Chargers--4:15--L 23-31 November 22nd--@Bears--8:20--W 24-20 November 29th—Redskins—1:00—W 27-24 December 6th--@Falcons--1:00--W 34-7 December 13th--@Giants--8:20--W 45-38 December 20th—49ers—4:15—W 27-13 December 27th—Broncos—4:15—W 30-27

II. Domestic violence arrests for the 8-hour period beginning at either 1:00 pm or 6:00 pm (depending on holiday) for Valentine’s Day, St. Patrick’s Day, Easter 86

Sunday, Memorial Day, the Fourth of July, Labor Day, Christmas, and New Year’s Eve. DATES: Holidays February 14th—Valentine’s Day March 17th—St. Patrick’s Day April 12th—Easter Sunday May 25th—Monday of Memorial Day Weekend July 4th—Independence Day September 7th—Labor Day December 25th—Christmas December 31st—New Year’s Eve

III. Domestic violence arrests for the 8-hour period beginning at game time for “big” games for the other three professional sports teams playing in Philadelphia. DATES: Monday, February 9th—Sixers vs. Phoenix—W 108-91 Monday, March 23rd—Flyers vs. Devils—W 4-2 Sunday, April 5th—Phillies vs. Braves—L 4-1 (Home Opener) Sunday, April 12th—Rangers vs. Flyers—(5:00)—L, 4-3 (Last game before playoffs) Wednesday, April 15th—Flyers@Penguins--L 4-1 Friday, April 17th—Flyers@Penguins--L 3-2 OT Sunday, April 19th—Sixers@Magic--W 100-98, First round of NBA playoffs (Flyers also played at home, W over Penguins, Game 3 of First Round of of NHL playoffs) Wednesday, April 22nd—Sixers@Magic--L 87-96 Friday, April 24th—Sixers vs. Magic—W 96-94 Saturday, April 25th—Flyers vs. Penguins—3:00—L 5-3 (Flyers lose series) Thursday, April 30th—Sixers vs. Magic—L 89-114 (Sixers lose series) Sunday, September 13th—Phillies D/N DH vs. Mets, W 5-4 and 1-0 Sunday, October 11th—Phillies@Rockies--NLDS Game 3—W 6-5 Monday, October 12th—Phillies@Rockies--NLDS Game 4—W 5-4 (Phillies win series) Monday, October 19th—Phillies vs. Dodgers—NLCS Game 4—W 5-4 Wednesday, October 28th—Phillies@Yankees--Wolrd Series Game 1—W 6-1 Saturday, October 31st—Phillies vs. Yankees—Game 3—L 5-8 Monday, November 2nd—Phillies vs. Yankees—Game 5—W 8-6 Wednesday, November 4th—Phillies@Yankees--Game 6—L 3-7 (Phillies lose World Series)

IV Domestic violence arrests for the remaining, non-holiday, non-major sporting event Sundays. The 8-hour time period was randomly selected to reflect the variation in time periods of the football gamedays. Sunday, February 15th Sunday, March 15th 87

Sunday, July 19th Sunday, August 16th Sunday, February 22nd Sunday, March 1st Sunday, March 8th Sunday, March 22nd Sunday, March 29th Sunday, May 3rd Sunday, May 10th Sunday, May 17th Sunday, May 31st Sunday, June 7th Sunday, June 14th Sunday June 21st Sunday, June 28th Sunday, July 5th Sunday, July 12th Sunday, July 26th Sunday, August 2nd Sunday, August 9th

MEASURES

The independent variables of this dissertation include the previously listed data sets and subsets.

Independent Variables Data Set I Football Gamedays Data Set II Holidays Data Set III Other Sports Gamedays Data Set IV Comparison Sundays Independent Variables from Intra Data Set I Data Set I-A Eagles Home Data Set I-B Eagles Away Data Set I-C Eagles Wins Data Set I-D Eagles Lose Data Set I-E Eagles’ Rivals Data Set I-F Eagles’ Non-rivals Data Set I-G Eagles’ playoff games Data Set I-H Eagles” regular-season games

The dependent variable is the hourly arrest rates for five domestic violence arrest categories on the days that comprise the data sets in 2009 reported by the Philadelphia 88

Police Department—nonpublic agency data. The arrest rates for this study were recorded for an eight-hour time period on each of the days in each of the data sets. The rationale behind this critical window of eight hours is the timing of the game and then leaving enough time for the domestic incident and police involvement. The theoretical timing asserts that the game begins and ends after a three-and-a-half hour period, a domestic violence incident could take some time to become serious enough for police involvement, and then police involvement led to arrest. In the case of “parole officer arrest,” there would certainly be more time required. Eight hours was decided upon as the best theoretical fit.

These are domestic violence events that were reported to, responded by, and arrests were made by the police; there could be many more unreported cases of domestic violence. The victims in this particular data set are female; the offenders are male. There are no child victims in this data.

Information from domestic violence hotlines would be helpful to triangulate the data (as would the inclusion of the suburban areas’ police calls), but all of that information is not available. In fact, the Women’s Law Project, which keeps track of the hotline calls cannot share its information and has expressed an interest in the data obtained for this dissertation.

The data for the dependent variable are reliable in that they emanate from police data—meaning the police responded to these calls and any “phony” calls would not appear in the data. Pennsylvania law leaves domestic violence arrest to the discretion of the police officers, so these events were serious enough for the police to make an arrest. 89

As to the validity of the data, again, police data are only the cases reported to officials. This raises a question as to the validity of the aggregate numbers, which actually works against the hypotheses in this dissertation. On the other hand, Sherman et al. (1989:36) proposed that “calls to the police provide the most extensive and faithful account of what the public tells the police about crime, with the specific errors and biases that entails.”

ANALYSIS PLAN

The statistical analyses for this dissertation are essentially the “differences in means tests”—which is a t-test for the seven hypotheses. Because some of the samples are considerably small and normal distribution could not be assumed, the Mann-Whitney

U test, which is a nonparametric t-test for two independent samples was run. The mann-

Whitney U test assesses whether these two samples have equal values.

The following breaks down the sample size for each of the comparisons:

The data were comprised of four independent samples and each sample’s associated number of domestic violence arrests for an 8-hour period on that day.

• DATA SET I: n=20

• DATA SET II: n=8

• DATA SET III: n=19

• DATA SET IV: n=22

All the data sets in the preceding group are football gameday and non-football gameday comparisons. Additionally eight data sets were formed from Data Set I, in order to explore several of the research questions.

• DATA SET I-A: n=8 90

• DATA SET I-B: n=7

• DATA SET I-C: n=14

• DATA SET I-D: n=4

• DATA SET I-E: n=7

• DATA SET I-F: n=9

• DATA SET I-G: n=3

• DATA SET I-H: n=15

All the data sets in the preceding group are football gameday subsets.

Using the Mann-Whitney U test, the null hypothesis assumes the distributions of both groups are equal. Under the alternative hypothesis the probability of an observation of one population exceeding the other is not equal to 0.5. Essentially, the test is a difference of means test. Because it compares the sum of ranks, the Mann-Whitney test is less likely than the t-test to spuriously indicate differences because of the presence of outliers—Mann-Whitney is more robust (Motulsky, 2007).

CHAPTER SUMMARY

For this dissertation, the city chosen for study is Philadelphia. The NFL team is the Eagles and the main comparison group to be tested begins with the days on which the

Eagles played in the calendar year 2009. Additionally, the day of the Super Bowl and the

Pro Bowl were included in the football gamedays dataset, also known as Data Set I. The dependent variable is the number of domestic violence arrests made on those days, during an eight-hour period, beginning with kick-off of the respective football games.

The independent samples are comprised of other theoretically relevant days in the calendar year 2009 and the domestic violence arrests on those days. The other 91 comparison groups consist of holidays (Data Set II), games on which the other three professional sports teams played their games (Data Set III), and the remaining non-sports, non-holiday Sundays in the calendar year (Data Set IV).

The arrest data is non-published and was therefore limited. The 69 days chosen are a purposive sampling, chosen for their relevance to the research questions.

Some of the weaknesses of the data are: only one year was available, only 69 days of that year were available, and only the arrest rates for the city of Philadelphia were available—whereas the Eagles’ television market is considerably larger.

A comparison of means test was used to compare the various independent groups—mostly using the nonparametric Mann-Whitney U test and when the groups were assumed to be normally distributed, a t-test. 92

CHAPTER VII--RESULTS

FINDINGS

Using the Philadelphia Incident Classification Listing (Philadelphia Police

Department, 2003), the data obtained from the Statistical Section of the Police Research and Planning Unit were sorted into five categories of domestic violence arrests. The police statistics for all 69 days were comprised of five categories of domestic arrests.

The following table is the result of decoding the data and categorizing the results— including totaling all five types of domestic arrest—of the main comparison group called

“Data Set I” and consisting of the results of the football gameday totals.

The five types of domestic arrests—as defined by the Philadelphia Police—are:

1) Violation of Abuse Order, 2) Violation of Abuse Order Parole Officer Arrest, 3)

Simple Assault, 4) Aggravated Assault, and 5) Domestic Rape (Philadelphia Police,

2010). The codes included for these data sets include only those domestic incidents in which the victim was female. These numbers do not include incidents involving children. Domestic homicide is a rare enough event that the police made separate notations when the homicide occurred during the designated hours. In the following chart, domestic homicides are indicated with an asterisk after the day. 93

TABLE 3.

PHILADELPHIA FOOTBALL GAME DAYS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 19 12/13 1 0 6 3 0 10 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 2/1 1 0 10 10 2 23 2/8 3 0 14 3 0 20 TOTAL 41 10 187 74 10 322 *Domestic homicide

This table represents the main set of comparison to the non-football data sets and contains the information for the football game to football game comparisons.

94

The following chart lists the descriptive statistics for the domestic violence arrests. These are the domestic violence arrests for all of the 69 days from the test Data Sets—I through

IV.

TABLE 4.

DESCRIPTIVE STATISTICS FOR DOMESTIC VIOLENCE ARRESTS

N Minimum Maximum Mean Standard Deviation VIOLATION OF ABUSE 69 0 7 1.71 1.573 ORDER VIOLATION OF ABUSE ORDER— 69 0 2 .36 .664 PAROLE OFFICE ARREST AGGRAVATED 69 0 10 3.22 2.182 ASSAULT DOMESTIC 69 0 3 .17 .541 RAPE SIMPLE 69 2 14 7.17 3.029 ASSAULT TOTAL 69 5 27 12.64 4.929 ARRESTS

95

TABLE 5.

DESCRIPTIVE STATISTICS FOR ARRESTS BY COMPARISON GROUPS N Minimum Maximum Mean Standard (Number of (Number of (Number of Deviation Days in Domestic Domestic Study) Violence Violence Arrests— Arrests— Single Day) Single Day) FOOTBALL GAMEDAYS 20 10 27 16.10 5.098

HOLIDAYS 8 9 24 15.50 5.555

OTHER 19 6 20 12.47 2.970 SPORT GAMEDAYS COMPARISON 22 5 13 8.59 2.364 SUNDAYS HOCKEY 7 11 20 14.14 3.024 GAMEDAYS BASEBALL 12 6 16 11.50 2.576 AND BASKETBALL GAMEDAYS

96

HypothesisA: During the 8-hour period following “kick-off” on a televised Philadelphia Eagles game, domestic violence arrests will be greater than the average number of arrests for day of the week and time of day, for the calendar year of 2009.

The preceding numbers for football gamedays (Table 3) were aggregated and the Mann- Whitney U test was run comparing it to the following data set:

TABLE 6. PHILADELPHIA GAME DAY COMPARISON SUNDAYS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 2/15 1 1 4 1 0 7 3/15 0 0 5 3 0 8 7/19 3 0 5 3 0 11 8/17 0 0 6 5 0 11 2/22 4 0 2 0 0 6 3/1 2 1 3 2 0 8 3/8 2 0 6 2 1 11 3/22 1 0 9 3 0 13 3/29 0 0 8 2 0 10 5/3 1 0 6 1 0 8 5/10 2 0 5 3 0 10 5/17 0 0 4 2 0 6 5/31 1 0 4 7 0 12 6/7 1 0 5 2 0 8 6/14 1 0 4 0 0 5 6/21 0 0 3 3 0 6 6/28 0 0 2 3 0 5 7/5 1 0 4 2 0 7 7/12 0 0 4 4 0 8 7/26 0 0 4 4 0 8 8/2 0 0 3 6 0 9 8/9 1 0 11 0 0 12 TOTAL 21 2 107 58 1 189 97

The following is the result of the Mann-Whitney U test:

TABLE 7.

TOTAL DOMESTIC VIOLENCE ARRESTS IN PHILADELPHIA ON FOOTBALL GAME DAYS AND COMPARISON SUNDAYS

EVENT N Mean Rank U Sig. FOOTBALL 20 30.83 (TOTAL ARRESTS) COMPARISON 22 13.02 SUNDAYS (TOTAL ARRESTS) TOTAL 42 33.500 .000* p<.001 (2-tailed)

The distributions in the two groups differed significantly (p<.001), confirming HypothesisA.

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HypothesisB: Domestic violence arrests will be equal following Eagles home games and away games.

TABLE 8.

PHILADELPHIA EAGLES’ HOME GAMES IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 9 4 1 17 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/29 3 0 9 2 0 14 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 TOTAL 14 5 75 20 1 95 *Domestic Homicide

TABLE 9.

EAGLES’ AWAY GAMES IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 9/13 4 2 13 4 2 25 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 12/6 3 0 9 5 1 18 12/13 1 0 6 3 0 10 TOTAL 15 2 60 27 5 109 99

The preceding two data sets—comprised of aggregated arrest numbers from the five domestic violence categories—were compared, using the Mann-Whitney U test.

TABLE 10.

EVENT N Mean Rank U Sig. HOME 8 7.88 GAMES (TOTAL ARRESTS) AWAY 7 8.14 GAMES (TOTAL ARRESTS) TOTAL 15 27.000 .907 The mean difference was not significant

Additionally, a parametric t-test was run comparing these two samples are the results were the same.

TABLE 11.

PHILADELPHIA EAGLES’ HOME GAMES VERSUS AWAY GAMES

EVENT N Mean SD Sig. REGULAR 8 14.375 3.292 SEASON PLAYOFFS 7 15.571 5798 TOTAL 15 .625 The mean difference between these two groups is not statistically significant

The statistical tests for HypothesisB failed to reject the null hypothesis.

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HypothesisC: Domestic violence arrests will be greater following wins than losses.

TABLE 12.

PHILADELPHIA EAGLES WINS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 19

TABLE 13.

EAGLES LOSSES IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/18 1 0 11 2 0 14 10/18 3 0 9 4 1 17 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19

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The preceding two data sets—comprised of aggregated arrest numbers from the five domestic violence categories—were compared, using the Mann-Whitney U test.

TABLE 14.

EVENT N Mean Rank U Sig. EAGLES’ 14 9.18 WINS (TOTAL ARRESTS) EAGLES’ 4 10.63 LOSSES (TOTAL ARRESTS) TOTAL 18 23.500 .630 The mean difference was not significant

Additionally, a parametric t-test was run comparing these two samples are the results were the same.

TABLE 15.

PHILADELPHIA EAGLES WINS VS. LOSSES IN 2009

EVENT N Mean SD Sig. EAGLES WINS 14 15.43 5.557 EAGLES 4 15.75 2.754 LOSSES TOTAL 18 .914 The mean difference between these two groups is not statistically significant

The statistical tests for HypothesisC failed to reject the null hypothesis 102

HypothesisD: Domestic violence arrests will be greater following games vs. rivals than following games vs. average opponents.

TABLE 16.

PHILADELPHIA EAGLES’ GAMES AGAINST RIVALS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14 11/1 7 0 9 2 0 18 11/8 0 2 8 3 0 13 11/29 3 0 9 2 0 14 12/13 1 0 6 3 0 10 TOTAL 19 5 57 26 3 110

TABLE 17.

PHILADELPHIA EAGLES’ GAMES AGAINST NON-RIVALS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 11/15* 1 0 11 6 1 13 11/29 3 0 9 2 0 14 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 9/13 4 2 13 4 2 25 TOTAL 14 5 78 18 2 145 103

The preceding two data sets—comprised of aggregated arrest numbers from the five domestic violence categories—were compared, using the Mann-Whitney U test.

TABLE 18.

EVENT N Mean Rank U Sig. EAGLES’ 7 9.64 RIVALS (TOTAL ARRESTS) EAGLES’ 11 9.41 NON-RIVALS (TOTAL ARRESTS) TOTAL 18 37.500 .927 The mean difference was not significant

Additionally, a parametric t-test was run comparing these two samples are the results were the same.

TABLE 19.

PHILADELPHIA EAGLES’ GAMES VERSUS RIVALS OR NON-RIVALS EVENT N Mean SD Sig. RIVALS 7 15.714 5.498 NON RIVALS 11 15.363 4,924 TOTAL 18 .890 The mean difference between these two groups is not statistically significant

The statistical test for HypothesisD failed to reject the null hypothesis. 104

HypothesisE: Domestic violence arrests will be greater following playoff games than following regular-season games.

TABLE 20.

PHILADELPHIA EAGLES’ REGULAR SEASON GAMES IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 18 12/13 1 0 6 3 0 10 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13

TABLE 21.

PHILADELPHIA EAGLES’ PLAYOFF GAMES IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14 105

The preceding two data sets—comprised of aggregated arrest numbers from the five domestic violence categories—were compared, using the Mann-Whitney U test.

TABLE 22.

EVENT N Mean Rank U Sig. EAGLES’ 3 12.0 REGULAR SEASON GAMES (TOTAL ARRESTS) EAGLES’ 15 9.00 PLAYOFF GAMES (TOTAL ARRESTS) TOTAL 18 15.000 .370 The mean difference was not significant

Additionally, a parametric t-test was run comparing these two samples are the results were the same.

TABLE 23.

PHILADELPHIA EAGLES’ REGULAR SEASON GAMES VERSUS PLAYOFF GAMES

EVENT N Mean SD Sig. REGULAR 15 14.933 4.495 SEASON PLAYOFFS 3 18.333 7.505 TOTAL 18 .296 The mean difference between these two groups is not statistically significant

Statistical tests for HypothesisE failed to reject the null hypothesis

106

HypothesisF: Domestic violence arrests will be equal to the number of arrests on a holiday associated with socializing and the drinking of alcoholic beverages.

For the purposes of clarity, Table 3 is again inserted. TABLE 3.

PHILADELPHIA FOOTBALL GAME DAYS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 19 12/13 1 0 6 3 0 10 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 2/1 1 0 10 10 2 23 2/8 3 0 14 3 0 20 TOTAL 41 10 187 74 10 322 *Domestic homicide

107

TABLE 24.

HOLIDAYS ASSOCIATED WITH ALCOHOL CONSUMPTION IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 2/14 4 1 10 4 0 19 3/17 2 1 6 2 0 11 4/12 2 1 7 1 0 11 5/25 0 2 14 8 0 24 7/4 3 1 14 4 0 22 9/7 2 0 6 7 0 15 12/25 1 0 6 1 1 9 12/31 2 1 8 2 0 13 TOTAL 16 7 71 29 1 124

The preceding two data sets—comprised of aggregated arrest numbers from the five domestic violence categories—were compared, using the Mann-Whitney U test.

TABLE 25.

EVENT N Mean Rank U Sig. FOOTBALL 20 14.75 GAMEDAYS (TOTAL ARRESTS) HOLIDAYS 8 111.00 (TOTAL ARRESTS) TOTAL 28 75.000 .799 The mean difference was not significant

Additionally, a parametric t-test was run comparing these two samples are the results were the same.

108

TABLE 26.

TOTAL DOMESTIC VIOLENCE ARRESTS IN PHILADELPHIA ON FOOTBALL GAME DAYS AND HOLIDAYS

EVENT N Mean SD Sig. FOOTBALL 20 14.75 (TOTAL ARRESTS) HOLIDAYS 8 13.88 (TOTAL ARRESTS) TOTAL 28 75.00 .799 The two groups did not differ significantly

This result confirms HypothesisF 109

HypothesisG: Domestic violence arrests will be greater following football games than following hockey, basketball, and baseball games.

For the purposes of clarity, Table 3 is again inserted.

TABLE 3.

PHILADELPHIA FOOTBALL GAME DAYS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 19 12/13 1 0 6 3 0 10 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 2/1 1 0 10 10 2 23 2/8 3 0 14 3 0 20 TOTAL 41 10 187 74 10 322 *Domestic homicide

110

TABLE 27.

PHILADELPHIA BASKETBALL, BASEBALL, AND HOCKEY “BIG GAMES” IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 2/9 0 2 7 7 0 16 3/23 2 0 6 6 0 14 4/12 2 1 9 1 0 13 4/15 7 0 8 5 0 20 4/17 3 0 6 2 0 11 4/19 3 0 8 2 0 13 4/25 3 0 5 4 0 12 2/9 0 2 7 7 0 16 4/5 4 0 5 4 0 13 4/19 3 0 7 2 0 12 4/22 2 0 4 5 0 11 4/24 1 0 11 0 0 12 4/30 0 0 7 2 0 9 10/12 3 0 7 0 0 10 10/19* 1 1 9 3 0 14 10/28 2 0 3 1 0 6 10/31 0 0 8 5 0 13 11/2 3 0 6 3 0 12 11/4 1 0 7 2 0 10 TOTAL 40 6 130 59 0 235 *Domestic Homicide

111

The preceding two data sets—comprised of aggregated arrest numbers from the five domestic violence categories—were compared, using a t-test. The rationale for the t-test is the almost equal number in each sample.

Domestic violence arrests after during the eight-hour period beginning with kick-off during football games (M=16.1, SD=5.09) were higher than the number of arrests (M=12.4, SD=2.9, p=.01) beginning with the start of the games and during an eight-hour period of the other major sports in Philadelphia.

HypothesisG is confirmed.

TABLE 28.

FOOTBALL GAMESDAYS VERSUS ALL OTHER SPORTS GAMEDAYS

EVENT N Mean SD Sig. FOOTBALL 20 16.10 5.098 NON 19 12.47 2.970 FOOTBALL TOTAL 39 .010* p=.01

112

ADDITIONAL FINDINGS

As the raw data was sorted through, it became apparent that there were patterns that were unexpected at the start of the research. Statistical tests were run to examine these patterns, to determine whether future research was warranted. These tests will be explained in detail in the “Discussions” section of this chapter.

Table 27 represents the parceling out of hockey gamedays from the “other sports” data set (Data Set IV). The patterns gleaned from the data were striking, although it is a small subset.

TABLE 29.

PHILADELPHIA HOCKEY GAME DAYS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS (DATA SET V)

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER— ARREST 2/9 0 2 7 7 0 16 3/23 2 0 6 6 0 14 4/12 2 1 9 1 0 13 4/15 7 0 8 5 0 20 4/17 3 0 6 2 0 11 4/19 3 0 8 2 0 13 4/25 3 0 5 4 0 12 TOTAL 20 3 49 27 0 99

113

A Mann-Whitney U test was run comparing this hockey gameday data set, which can now be referred to as Data Set V, with the football gameday data set (Data Set I).

TABLE 30.

TOTAL DOMESTIC VIOLENCE ARRESTS IN PHILADELPHIA ON FOOTBALL GAME DAYS AND HOCKEY GAME DAYS

EVENT N Mean Rank U Sig. FOOTBALL 20 14.68 (TOTAL ARRESTS) HOCKEY 7 12.07 (TOTAL ARRESTS) TOTAL 27 56.500 .453 These two groups did not differ significantly

Additionally, because the hockey game days were originally part of Data Set IV, which differed significantly from Data Set I, an additional statistical test was run to determine the relationship between football and a data set of basketball and baseball game days.

This new data set is referred to as Data Set VI.

114

TABLE 31.

PHILADELPHIA BASKETBALL & BASEBALL GAME DAYS IN 2009 AND THE FIVE CATEGORIES OF DOMESTIC VIOLENCE ARRESTS

DAY VIOLATION VIOLATION SIMPLE AGGRAVATED DOMESTIC TOTAL OF ABUSE OF ABUSE ASSAULT ASSAULT RAPE ORDER ORDER PAROLE OFFICER-- ARREST 2/9 0 2 7 7 0 16 4/5 4 0 5 4 0 13 4/19 3 0 7 2 0 12 4/22 2 0 4 5 0 11 4/24 1 0 11 0 0 12 4/30 0 0 7 2 0 9 10/12 3 0 7 0 0 10 10/19* 1 1 9 3 0 14 10/28 2 0 3 1 0 6 10/31 0 0 8 5 0 13 11/2 3 0 6 3 0 12 11/4 1 0 7 2 0 10 TOTAL 20 3 81 32 0 136

A Mann-Whitney U test was run comparing this basketball and baseball gameday data set, which can now be referred to as Data Set VI, with the football gameday data set

(Data Set I).

115

TABLE 32. TOTAL DOMESTIC VIOLENCE ARRESTS ON FOOTBALL GAME DAYS AND BASEBALL/BASKETBALL GAME DAYS

EVENT N Mean Rank U Sig. FOOTBALL (TOTAL 20 19.80 ARRESTS) BASEBALL/BASKETBALL 12 11.00 (TOTAL ARRESTS) TOTAL 32 54.000 .010* p<.05

With or without the hockey game days in the equation, basketball and baseball game days differed significantly from football game days.

Finally, as will be discussed further in the next section, another test was run that parceled out one of the domestic violence categories—domestic rape. Although is a rare reported occurrence, it is included in the Philadelphia Police Department’s definition

(2003). There appeared to be a clear difference in the number of domestic violence rapes in the football game days set then in any other set. Statistical tests were run to see if these differences were statistically significant—the confirmation is below.

TABLE 33. DOMESTIC RAPE ARRESTS ON FOOTBALL GAME DAYS AND COMPARISON SUNDAYS IN PHILADELPHIA

EVENT N Mean Rank U Sig. FOOTBALL 20 30.83 (TOTAL ARRESTS) COMPARISON 22 13.02 SUNDAYS (TOTAL ARRESTS) TOTAL 42 33.500 .000* p<.00 116

CHAPTER SEVEN SUMMARY

Using the Philadelphia Incident Classification Listing (Philadelphia Police

Department, 2003), the data obtained from the Statistical Section of the Police Research and Planning Unit were sorted into five categories of domestic violence arrests. The police statistics for all 69 days were comprised of five categories of domestic arrests.

The following table is the result of decoding the data and categorizing the results— including totaling all five types of domestic arrest—of the main comparison group called

“Data Set I” and consisting of the results of the football gameday totals.

The five types of domestic arrests—as defined by the Philadelphia Police—are: 1)

Violation of Abuse Order, 2) Violation of Abuse Order Parole Officer Arrest, 3) Simple

Assault, 4) Aggravated Assault, and 5) Domestic Rape.

Statistical tests were run comparing the various inter-football and intra-football data sets. Three of the hypotheses were not confirmed, four of the hypotheses were confirmed. Additionally, other exploratory tests were run because of noticeable patterns in the raw police data. 117

CHAPTER VIII--DISCUSSION

INTRODUCTION

The following is a review of the research questions explored in this study.

HypothesisA: During the 8-hour period following “kick-off” on a televised Philadelphia Eagles game, domestic violence arrests will be greater than the average number of arrests for day of the week and time of day, for the calendar year of2009.

HypothesisB: Domestic violence arrests will be equal following Eagles home games and away games.

HypothesisC: Domestic violence arrests will be greater following wins than losses.

HypothesisD: Domestic violence arrests will be greater following games vs. rivals than following games vs. average opponents.

HypothesisE: Domestic violence arrests will be greater following playoff games than following regular-season games.

HypothesisF: Domestic violence arrests will be equal to the number of arrests on a holiday associated with socializing and the drinking of alcoholic beverages.

HypothesisG: Domestic violence arrests will be greater following football games than followinghockey, basketball, and baseball games.

These relationships were tested using comparison of means tests—both a parametric t- test and the nonparametric Mann-Whitney U tests. Hypotheses C, D, and E were not confirmed. Hypotheses A, B, F, and G were confirmed—the most important result being

Hypothesis A, which is that football gamedays would produce higher numbers of domestic violence arrests than the comparable, non-sports Sundays (n=22). This was the largest comparison set and the most significant, because it does rule out some confounding factors. This will be discussed further in the following sections, which break down the results by individual hypothesis. 118

Although Hypotheses C, D, and E were not confirmed, it is not theoretically troublesome. When those hypotheses were conceived of, there were certain assumptions in play about sports fan aggressive behavior that have evolved since the study began.

After careful consideration, it became clearer that if this dissertation linked stadium violence or “hooliganism” to media violence, then similar behaviors would be exhibited after watching football on television. Stadium violence occurs no matter who wins, where the game is played, whether it is a rival team or whether it is a regular season game. Further, the idea that domestic violence would increase after wins came from the two pervious studies (White et al. 1992, Sach & Chu, 2000), but was counter-intuitive to the author of this dissertation. Again—as previously noted—hooligans riot on both sides of the fence—literally.

As previously mentioned and further witnessed by the number and content of the tables in the “results” section of this dissertation, more comparisons and statistical tests were run than were indicated by the hypotheses. The reason for this is that many intriguing patterns and results became obvious after the sorting of the data began. This discussion will begin with the hypotheses that included intra-football gameday studies.

WINS VS. LOSSES

Four of the seven hypotheses involve these intra-football gameday subsets. Not any of the four rejected the null hypothesis. For the hypothesis that wins would produce more domestic violence arrests than losses, this is in contrast to the results found in the

Los Angeles study (Sachs & Chu, 2000) or the northern Virginia study (White et al.

1992). There could be a number of reasons why these results differ. 119

First, neither the Los Angeles study nor the northern Virginia study had the more narrowed dependent variable. Also, the overall results for these studies were mixed and there were—as previously explained—design flaws in the Los Angeles study. One advantage that those studies held over this dissertation research is the length of the study.

Both of these studies looked at two seasons worth of football games. Of course in the

Los Angeles study, there were also two teams in the area, further muddying the outcomes. Finally, however, the Eagles lost only four games in all of 2009, which includes losing the NFC championship and narrowly missing the Super Bowl.

The study by White et al. (1992), which so heavily influenced the design of this dissertation research, assumed that the copycat mechanism was triggered by the win and the successfully-executed violence. Looking at the results of this dissertation, it would seem that the “event,” the “hype” of the game with its constant, on-field violence presents the violent script.

RIVALS AND PLAYOFFS

Neither statistical test showed support for the hypothesis of difference between either the “rivals/non-rivals” games or the “playoff/regular season” games. Perhaps a longer study would yield a different result or perhaps, again, as is evidenced by the stadium violence or hooligan research, it is the event of the game itself that is the mechanism.

HOME VS. AWAY

The final intra-football gameday hypothesis is the most important for this study.

This is the test that separates the results of stadium violence from media-generated or copycat violence. The hypothesis stated that there would be no difference and indeed, the 120 test of means was not statistically significant. This test was directly designed to address the possible bias that fans may be going to the games and then going home and committing acts of violence. If this were the case, then the media/copycat framework would be weakened.

The result gives support to the hypothesis of no difference, thereby strengthening the media/copycat framework. Further, although the comparison of means test was not statistically significant, the higher number of incidents occurred after away games.

Clearly, this result points more toward a media response than a stadium influenced or

“hooligan” behavior.

HOLIDAYS

This was another test designed to examine possible biases. With no way to determine how much of a factor alcohol played in the commission of these crimes, comparing the means of the football gamedays to the holidays was one way to assess the relationship. The comparison of means test was not statistically significant, thereby supporting the hypothesis of no difference. Granted, the sample of holidays was small and perhaps a multi-year study would show a different result, but looking at the raw data, the summer holidays had higher rates of domestic violence arrests than the winter holidays. Examining the raw data, it is the three holidays that take place over the summer that skew the numbers—Memorial Day, Fourth of July, and Labor Day have exceedingly high numbers, while the five other holidays and most importantly, those that occur during the football season, have far fewer arrests than football gamedays. According to a 2007 report from the Home Office, while property crime goes up in winter, violent assault and sexual assaults peak over the summer--in particular, crimes against females. In this 121 study, indecent assaults rise 21% over the trend in the summer and rapes rise 14% over the trend (Hird & Ruparel, 2007). It may be fortuitous that both football and hockey are played during the winter months, thus eliminating another aggravating factor in the mix

(Hird & Ruparel, 2007).

Another point of comparison harkens back to the hooligan studies. General

“party atmospheres” at rock concerts do not regularly produce the kind of violence in a soccer stadium. The results seem to indicate the alcohol as being one factor and requiring another aggravating factor to produce violence.

Interestingly, Valentine’s Day (obviously a winter holiday) showed a higher number of incidents than either Christmas, New Year’s, or even St. Patrick’s Day— holidays more known for drinking than Valentine’s Day. What is present may be a kind of tension between men and women similar to what happens during football games—a gendered kind of expectation that may be met or unmet. This could provide fodder for future study.

FOOTBALL COMPARED TO THE OTHER MAJOR SPORTS

The hypothesis proposed that the average number of domestic violence arrests during and following football games would be greater than those of all the other major sports. The statistical analysis showed support for this hypothesis. This outcome is key to the idea that viewers see and imitate violent scripts. As defined on page 22 of this dissertation, football and ice hockey are considered “violent combative” sports

(McDaniel et al., 2007). Even to the non-scientific observer, one can note a difference in football and hockey compared to basketball and baseball, just by knowing the rules of the games. Violent physical contact is not allowed in either basketball or baseball and is part 122 of the game for both football and hockey. Even so, the hypothesis that football would be greater than the other three was supported. An unexpected result, however, came out of this research.

While decoding and charting the raw data for this research, it was discovered that the hockey portion of the “other sports” data set showed high numbers of incidents beginning “when the puck drops” through a three-hour period. Because of this, a subset of “hockey” games was created and tested against football gamedays. The Mann

Whitney U test showed no statistical difference between the football gamedays and hockey gamedays.

While this result was not anticipated, it is certainly not a surprise. Given its status as a violent combative sport (McDaniel et al., 2007), it seems plausible that hockey games could produce a similar copycat result as football games. Theoretically, the hockey games that were chosen were “big games”—there were six playoff games and one regular season game against the Devils, a perennial rival of the Philadelphia Flyers.

But, the gamedays for baseball and basketball were “big games,” too and they did not show the same results. The days chosen for basketball and baseball were either home openers or playoff games and included the World Series and still did not rival hockey.

Given the length of the hockey season (82 regular season games and two months of playoffs), having a data set that includes only seven games is a poor snapshot of the season. This unexpected result, however, does point toward future studies in which hockey is the main sport being investigated.

123

FOOTBALL GAMEDAYS VS. THE AVERAGE SUNDAY

The test comparing the means of football gamedays to other Sundays in the year showed a statistically significant (p=<.001) difference between the two groups. The previous studies by Sachs & Chu (2000) and Whit et al. (1992), while finding some significance in certain areas or close to significance in other areas, failed to find such a persuasive relationship. Twenty-two Sundays were measured and compared to twenty football gamedays and the difference in the number of domestic violence arrests on those days for an 8-hour time period showed an average of almost twice the number of arrests.

Looking back to the limitations already listed for this study, a one-year study may have produced an anomaly. A longer study could perhaps provide an even more persuasive argument or could show that 2009 was an exception. Replication of this study in another city, with a longer time period would strengthen the theory that violent sports on television produce violent copycat behavior. Chicago would be an ideal city to replicate this study. Originally, during the forming of this research, Chicago seemed less than ideal because of the two Major League Baseball teams in one city. Before this research, it was unclear whether baseball results would cloud the picture, but given the low number of incidents during baseball games (on average), Chicago would be the next city in which to try replication. Also, given the geographical and cultural differences between the East Coast and the Midwest, finding the same result would give much credence to the theory.

124

DOMESTIC RAPE

One final unanticipated result was found in the domestic violence category— domestic rape. In the “holidays” and comparison Sunday data sets, there was one incident of domestic rape. For the other sports data set, there was not a single incident of domestic rape. For the football gamedays data set, there were 10 incidents of domestic rape. Running a statistical test on football game days to the comparison Sundays, there was a statistically significant difference between domestic rape incidents during the football gameday time periods and the comparison Sundays.

What is different about the football broadcasts that produce such a difference in this one category? Is it perhaps that combination of violence on television, alcohol consumption, women appearing as nuisances on football-related commercials, and the presence of scantily-clad cheerleaders that creates a toxic brew of influences? Here, again, is a topic for future scientific study.

CHAPTER EIGHT--SUMMARY

These relationships were tested using comparison of means tests—both a parametric t-test and the nonparametric Mann-Whitney U tests. Hypotheses C, D, and E were not confirmed. Hypotheses A, B, F, and G were confirmed—the most important result being Hypothesis A, which is that football gamedays would produce higher numbers of domestic violence arrests than the comparable, non-sports Sundays (n=22).

This was the largest comparison set and the most significant, because it does rule out 125 some confounding factors. This will be discussed further in the following sections, which break down the results by individual hypothesis.

Although Hypotheses C, D, and E were not confirmed, it is not theoretically troublesome. When those hypotheses were conceived of, there were certain assumptions in play about sports fan aggressive behavior that have evolved since the study began.

After careful consideration, it became clearer that if this dissertation linked stadium violence or “hooliganism” to media violence, then similar behaviors would be exhibited after watching football on television. Stadium violence occurs no matter who wins, where the game is played, whether it is a rival team or whether it is a regular season game. Further, the idea that domestic violence would increase after wins came from the two previous studies (White et al. 1992, Sach & Chu, 2000), but was counter-intuitive to the author of this dissertation. Again—as previously noted—hooligans riot on both sides of the fence—literally.

126

CHAPTER IX--CONCLUSION

SUMMARY OF FINDINGS

HypothesisA: During the 8-hour period following “kick-off” on a televised Philadelphia Eagles game, domestic violence arrests will be greater than the average number of arrests for day of the week and time of day, for the calendar year of2009.

HypothesisB: Domestic violence arrests will be equal following Eagles home games and away games.

HypothesisC: Domestic violence arrests will be greater following wins than losses.

HypothesisD: Domestic violence arrests will be greater following games vs. rivals than following games vs. average opponents.

HypothesisE: Domestic violence arrests will be greater following playoff games than following regular-season games.

HypothesisF: Domestic violence arrests will be equal to the number of arrests on a holiday associated with socializing and the drinking of alcoholic beverages.

HypothesisG: Domestic violence arrests will be greater following football games than followinghockey, basketball, and baseball games.

These relationships were tested using comparison of means tests—both a parametric t- test and the nonparametric Mann-Whitney U tests. Hypotheses C, D, and E were not confirmed. Hypotheses A, B, F, and G were confirmed—the most important result being

Hypothesis A, which is that football gamedays would produce higher numbers of domestic violence arrests than the comparable, non-sports Sundays (n=22). This was the largest comparison set and the most significant, because it does rule out some confounding factors. This will be discussed further in the following sections, which break down the results by individual hypothesis. 127

Although Hypotheses C, D, and E were not confirmed, it is not theoretically troublesome. When those hypotheses were conceived of, there were certain assumptions in play about sports fan aggressive behavior that have evolved since the study began.

After careful consideration, it became clearer that if this dissertation linked stadium violence or “hooliganism” to media violence, then similar behaviors would be exhibited after watching football on television. Stadium violence occurs no matter who wins, where the game is played, whether it is a rival team or whether it is a regular season game. Further, the idea that domestic violence would increase after wins came from the two pervious studies (White et al. 1992, Sach & Chu, 2000), but was counter-intuitive to the author of this dissertation. Again—as previously noted—hooligans riot on both sides of the fence—literally.

THEORETICAL IMPLICATIONS

While previous studies seem to indicate that violence hinged on wins or losses or

“important” games and these previous studies informed and influenced the formation of this dissertation, this author began to develop a different theory as the study unfolded.

Just like with soccer hooliganism, the outlook may or may not spark a riot. It appears that the highly identified nature of this particular sports fan, the “hype” around the event, and then the observation of the violence on television combine to provide a copycat script that leads to domestic violence during this time period from kick-off of any game of the home team, in this case, the Philadelphia Eagles.

The theoretical framework for this study is the result of combining both theory and research from different disciplines—psychology, sociology, and criminology. It is 128 the first study to link hooligan studies to media/copycat research with the idea of the highly-identified sports fan as one who is susceptible to copycat behavior. The violent behavior here is theorized to grow out of copycat behavior the same way that Philips theorized it—this violent behavior does not follow the same trajectory as “typical” domestic violence. It is worth including the theoretical framework from an earlier chapter, in order to review each “branch” and assess the theoretical implications. 129

SOCIAL IDENTITY = FAN (Shank & Beasley , 1968)

HIGHLY IDENTIFIED CASUAL FAN FAN

BIRG or CORG BIRG or cannot CORF or CORF

ELABORATED SOCIAL IDENTITY MODEL (Reicher , 2001)

o t e T c e n s p l e d r e r r o v a a v is e d id h n e a e d d t v a s i Im r d o e n l a t a e g a n e re s t s s G rm c r o ip n p ts u ro G

HOOLIGANISM MASS MEDIA OR OR SPECTATOR VIOLENCE COPYCAT VIOLENCE (Philips, 1986)

SOCIAL T A N T E S IDENTITY V P E O D E AND G E V R N S E T I I e N I T V iv N REDUCTION E ti T G R L n O E OF P g S T o -C ) PRIVATE SELF g 2 in y 0 r 0 r n o 2 AWARENESS a e , h e T r a L u l d ia c n o a BOTH S (B INCLUDED “SCRIPTS ,” BUT SCRIPTS VARY FOR EACH SITUATION THEORETICAL CONSTRUCT 130

FINDINGS AND THEORY

The path that winds from the highly-identified sports fan who is at home watching the game on television—as opposed to being part of a stadium crowd—and ends with watching violent action on a football field and imitation of this violence, is supported by the findings of this study. In fact, the phases of this theoretical framework are supported more than was anticipated at the beginning of this research.

BRANCHES OF THE FLOWCHART

At the top of the framework or the basis of the behavior is the concept of fandom as social identity. People derive their identities from a complicated mix of culture, family, and experience—at the very least—but the source of interest for this research is the connection to sports teams.

While many sports fans will bask in the glory of their favorite teams’ achievements and cut off the reflected failure of their teams’ disappointing showings, the highly-identified fan takes this identity to a new level. The findings of this dissertation only support this part of the theory and do not conflict with its suppositions.

For example, the hooligan studies indicate how highly-identified sports fans commit violent and/or deviant acts in and around sports stadiums. When it does occur, the fans exhibit this behavior before, during, and after a soccer game. The impetus appears to be the game itself, because rioting takes place between fans of both opponents—the fans who are happy to have their team win do not walk away from the fight. This idea shows that highly-identified fans do not differentiate between wins and 131 losses, home and away, playoff or non-playoff, rival or nonrival—hooligan studies show that soccer fans will fight under any circumstances.

When the hypotheses for this dissertation were formed, reliance on previous studies clouded this concept. As the study unfolded, it was clear that the hooligan studies pointed to the games themselves as the events and not necessarily the outcomes or the varying nature (home, rival, playoff, etc.) of the game. The theoretical framework here remains solid, but the suppositions of previous studies do not.

Reicher’s Elaborated Social Identity Model (2001) is supported clearly for the hooligan studies—the social identity and reduction of private self-awareness leads to this greater adherence to group norms and standards. When the violence is spectator violence, the scripts call for rioting with fellow fans. In the theoretical framework for this dissertation, the scripts are provided by the real violence transmitted by television.

The violent hits of a football game are not fictionalized hits—the essence of the game is to take the ball from the other team by physically stopping them. The blood and the injuries broadcast in living color are actual injuries and actual blood. These televised images provide the violent scripts that Bandura (2002) says teach through social learning theory. There is nothing in the findings to indicate that this is not true.

The possible biases that were discussed in chapter five were statistically ruled out.

Most importantly for the media violence component is that there was no statistical difference between the number of domestic violence arrests for the Sundays of home or away games. The numbers for away games were actually slightly higher, indication that these games were watched on television and the domestic violence arrests were not a result of stadium violence. 132

It is the contention here that this theoretical framework should be used for further sports fan, media, and crime studies. It methodically bridges the hooligan research with media and violence studies.

POLICY IMPLICATIONS

As it often the case with social science research, one faces the problem of how to legislate behavior. Can men be told not to drink while watching football on television?

Can women be told to stay away from their homes on the twenty-plus days a year that professional football games are broadcast? Should cheerleaders be banned from the

NFL? (Note: Not every team has cheerleaders.) Obviously, these are not viable answers, but there may be some policies or programs that do not attempt to legislate private behavior and still have a meaningful effect.

Armed with a fact sheet on previous research and the idea for this dissertation, this student-researcher met with then-Governor Ed Rendell on November 1, 2009.

Governor Rendell was the chief executive of a state with two NFL teams (the Eagles and the Pittsburgh Steelers), is a confidante of NFL Commissioner Roger Goodell, and hosts an Eagles pre-game, half-time, and wrap-up show on a local Philadelphia television channel. The meeting had many purposes—to make the governor aware that the study was being conducted on the Eagles, to speak about both the myths surrounding domestic violence and football and the empirical studies, to show the governor that the research was not being conducted by “radical, feminist researchers” who hate men and sports, to develop a connection with someone who could help push through programs with the help 133 of the NFL, and finally, to help make some policy changes (through education) with the help of a governor, who was also the former mayor of Philadelphia.

The governor had originally granted a fifteen-minute interview, but the meeting ended-up taking over two hours. Not only did the governor pledge support in helping to obtain the needed data, he came up with an idea of how to ameliorate the problem.

Governor Rendell suggested that the players on the Eagles could do Public Service

Announcements or PSAs. If, indeed, violent scripts produce copycat behavior, then perhaps seeing these “heroes” speak about off-field violence it could influence fans in a positive way. Impressively, the governor came up with an effective slogan on the spot—

“If you hurt your woman, you’re not a man, and you’re not a fan” (E. G. Rendell, personal communication, November 1, 2009).

While Rendell is no longer governor of Pennsylvania, he is a political commentator for MSNBC. With the outcomes of this research showing statistical support for the hypotheses and the additional findings, it is possible that Rendell will aid in some policy changes that could help reduce the number of football-related domestic violence arrests.

Public Service Announcements are just the first step, but they would represent an effort and an acknowledgment by and from the National Football League that there is a problem. This legitimatization of the issue could spur policymakers to find creative ways to educate the public to take safety measures.

When White et al. presented their findings, they were not able to impact policy in any way. With the help of Ed Rendell, at the very least, the PSAs could be taped in time 134 for the 2011-2012 season. An evaluation could be conducted to see if the PSAs had any effect.

The results of this study will be presented to the NFL commissioner’s office with the purpose of finding an overreaching educational program and with hopes that the NFL could provide some funding for replication of the study.

Holding media outlets to a higher standard could change the scripts of violence.

For example, the networks that have NFL contracts (at this time all four major networks show at least one “game of the week,” because ABC owns ESPN) all could agree to put an embargo on excessively violent hits, on constant replays of such hits, and on sending them to their affiliates for local newscasts.

Considering that the same networks insist that violence has no effect on children

(Bushman & Andersen, 2001), it is unlikely that un-policed networks would make these changes. If, however, the NFL insisted on such embargos, the networks would have no choice. Roger Goodell has shown an interest in the lessening of violent hits since taking over as NFL commissioner. It is possible that the information from this research could influence a decision of this kind. It is also likely that a replication of this study would have to be produced before NFL or network policies could be changed on a larger scale.

In addition to the limiting of instant replays of violent hits or the embargo of replays on all media outlets, producers of commercials could be held accountable.

Tamburro et al. (2004) conducted a study on violent behavior in commercials aired during televised, major sporting events and found football games to have the highest percentage. In contrast, The Masters Golf Tournament showed no violent commercials.

Certainly, “The Masters” is one of the most popular sporting events on television and it 135 manages to be shown and watched each year without violent commercials. The results of this study should be replicated and then presented to the networks that air these violent commercials and the example of The Masters would be an excellent one.

ALTERNATIVE EXPLANATIONS/FUTURE STUDIES

During the course of this study, assumptions were made, hypotheses were tested, and mistaken ideas were illuminated. The statistical results for this dissertation confirmed four of the seven hypotheses. The most important finding of these confirmed research questions is the comparison between the football gamedays and the comparison Sundays, as this was the largest comparison group to football days. Additionally, because Sunday is the day with the highest number of domestic violence incidents in Philadelphia, this number becomes more meaningful. There is, however, a major caveat to these findings.

The most threatening error to this statistical finding—and to all the findings in this study—is the Type 1 error, which rejects the null hypothesis, when the null hypothesis is true. The way to safeguard against this Type 1 error is to increase the sample size, which increases the statistical power and lessens the chance of this error. A larger sample size—in other words more years worth of football gamedays, comparison

Sundays, holidays, and other sports gamedays—may produce the same finding as this study or my correct the error. It is the most obvious and necessary follow-up study for this research.

The next issue is the reliability of these findings—does Philadelphia provide a good representation of the average sports fan? Is a finding in one city generalizable to the rest of the country? Philadelphia fans are known for aggressive behavior in the stands; indeed, in the sports world they are known as the most aggressive fans in the 136

United States. This may have skewed the results of the study. A study in another region of the country, in a city with both an NHL and NFL team, over a three-year period may produce more reliable results.

The next potential confound to the findings is the idea that it is media/copycat crime, influenced by the violent sports on television. The study clearly indicated that football gamedays produced higher numbers of arrests than basketball, baseball, and hockey combined, but when hockey was removed and studied alone, hockey showed no difference in mean numbers of arrests. As was discussed in the “findings” section of this dissertation, the small, purposive sample for hockey may have skewed the result. Unlike the football gamedays—which included all the football gamedays in 2009—this hockey sample is only a small portion of the games played in 2009 by the Philadelphia Flyers.

Furthermore, the games chosen were highly important games—games against bitter rivals or playoff games. Although the playoff game or rival game hypothesis showed no difference for the intra-football statistical tests, “non-important” hockey gamedays should be included in a future study.

Since, however, the same caliber of game was picked for both basketball and baseball gamedays, this may prove not to be a confound in a future study. The gamedays chosen for the Sixers and the Phillies had an even higher proportion of “important” games—the Phillies playing in the most “important” games of all four sports teams. The

Phillies went furthest in the playoffs that year, facing the Yankees for six games and finally losing in the World Series. Even the World Series games did not produce the number of domestic violence arrests that were recorded on football and hockey gamedays. 137

Another point of comparison for future studies would be the viewer size for the various sports’ gamedays. While it is known that NFL games are the most widely- viewed of all sporting events in the United States, a future study could also address the issue of television ratings—to gauge how high the viewership is for the different sporting events in the study. If viewership is relatively low for hockey games (hockey is the fourth most popular sport out of the “Big 4”), does that mean that there is an internal validity threat—that there is simply another cause for the higher number of domestic violence arrests during hockey games? Perhaps viewership in Philadelphia for hockey is unusually high compared to hockey viewership in other NHL markets? Replication of this study, combined with average number of viewers for the four major sports in the replication city or cities may indicate whether there is a causal relationship or a third variable affecting arrest rates.

The key ambiguity in this study is alcohol use. Alcohol is a possible confound that often occurs in aggression studies. If alcohol use had been indicated in the arrest statistics from the Philadelphia Police Department, regression analysis could have been conducted that would control for alcohol use. Because, however, there is no way to know conclusively whether alcohol was involved or not, there must be a reliance on the idea that alcohol is “always” involved.

In a subsequent study, there may be this kind of information available—perhaps other police departments would include this in their arrest reports—and this particular confound could be ruled out or confirmed. There is a strong indication, however, that alcohol does not produce the causal relationship. Alcohol is consumed at all four sporting events in this study and is traditionally consumed at the watching of all four 138 sporting events; yet there is a clear difference between the mean arrest rates during football, hockey, basketball, and baseball games. The previous studies on football and domestic violence did not compare football gamedays (or weeks, as was the unit of analysis in those previous studies, White et al. 1992, Sachs & Chu, 2000) to other sports or holidays. The most recent study (Card & Dahl, 2011) examining the relationship between football and domestic violence also did not include either alcohol in the statistical equation, nor did it examine the domestic violence incidents or arrests on

“other sports days.” Although further studies could attempt to quantify alcohol use, the question remains, if alcohol is the true cause, why does it not effect the arrest rates on basketball and baseball gamedays? Finally, the length of the game could produce longer periods during which to consume alcohol, but again, the other sports address this, because baseball games are slow and are not subject to “timing” as the other three sports are; yet baseball—again—did not have statistically equal arrest rates to football or hockey.

There are two “confounds” that possibly work against the theory in this dissertation—domestic violence being an under-reported crime and the inability to capture the entire viewing audience of the television market. In a future study, it would be difficult to ascertain the number of unreported cases of domestic violence, but perhaps a triangulation of data could include trauma admissions along with police data, in order to produce a clearer picture of abuse.

The issue of matching market viewership to police data is not as difficult; it would just require a bigger study with increased police cooperation. Along with replication in another city and looking at an increased number of years, a study that encompassed an entire viewer area would present a better picture. Sachs & Chu had the entire Los 139

Angeles County domestic violence calls-for-service in their study, but they had design flaws. Additionally, this hourly arrest rate that was available for Philadelphia was far more reliable than the weekly data that was available in the Los Angeles study.

Time of day, day of the week, or even time of the year would not be factors for further study—these are all included in this dissertation research. The time of day for the sporting events was theoretically chosen to allow for the sporting event to take place, the domestic violence incident to occur, and for an arrest to be made. The eight-hour time period coincided with the beginning of each sporting event. The day of the week was valid for two reasons—19 out of 20 football gamedays took place on a Sunday and the modal group of domestic violence arrests in Philadelphia in 2009 was comprised of

Sunday arrests. The time of the year was not a factor that confounded these hypotheses—in fact, it may have worked against the theory here. As mentioned in the discussion section, while the holiday comparison group showed no statistical difference in mean arrest rates, the summer holidays had much higher rates than winter rates. Also mentioned in the discussion was the study issued by the Home Office in 2007, showing summer months correlate with a 21% increase in assaults against women and a 14% increase in sexual assault against women. In the United States, studies show similar patterns, with an average of 90-degrees as the threshold at which violent crime increases

(Anderson, 2001).

For the comparison groups in this dissertation research, time of year seemed to affect the holiday group. The only sport truly played in warm temperatures did not correlate to higher numbers of domestic violence arrests (baseball). The football games 140 in this study had the following game-time temperatures for the games played in

Philadelphia and the one game played in New Jersey:

September 20th--68 degrees September 27th--69 degrees October 11th--62 degrees November 1st--56 degrees November 8th--61 degrees November 29th--56 degrees December 20th--32 degrees December 27th--45 degrees

Another possible explanation for the results of this study could be something called The Challenge Hypothesis—the theory that testosterone levels increase when a person wins at something (Archer, 2006). This dissertation study indicates the opposite—that it is not the winning that leads to a spike in testosterone, because there was no statistically significant difference between the arrest rates after wins or losses, but in a larger study, this idea of wins and losses should be retained. Even though no relationship was present in this study, because both of the previous studies discussed in this dissertation and the Challenge Hypothesis may say otherwise, it should be part of any subsequent study.

Finally, an issue that needs to be explored is one related to routine activity— perhaps women are simply home at the time that football games are being played.

According to the NFL, approximately 45 million women watch football on television very week (Brown, 1997). Professional football was the favorite sport of 30% of the women asked in a Harris Poll, 14% said it was baseball. Are women home on Sunday afternoon or evening because children do not have extra-curricular activities then? Is there something about football that appeals to women more than other sports or is it because football is more popular in general that is appealing? Is it more popular to 141 women because the schedule is limited compared to the other three American sports and requires less of a time commitment? Is this increased interest in football putting women in harm’s way?

One way to approach this theory would be to triangulate police data with a survey in a dedicated television market. Asking women if they watch football with their husbands, if they are more likely to be home during a football game than during other sporting events, and if they enjoy football because of the sport or because they want to spend time with their husbands would begin to explain this relationship. Further, the issues of violence and alcohol could be addressed with such a survey. One way to disseminate such a survey would be through a local news affiliate’s morning show.

These often have high numbers of female viewers and could include an online aspect to the survey. The local morning show may be willing to conduct this for both interest and to encourage viewers to go to their websites. It may show results that indicate the numbers are high during football games because women are home during football games.

Even so, because of the hockey results in this study, hockey would have to be included in such a study, because a similar finding to this dissertation would detract from the theory that “women are simply home watching football with their husbands or boyfriends.”

CONCLUSION

Possibly because of the media-hype surrounding the study done by White et al.,

(1992), the idea that football games might affect domestic violence has crept into the murky world of urban legend. While overnight television producers and police officers may have the feeling that it is the case, there have only been those two previously examined studies; yet, the Internet is rife with entries on the subject. The majority of 142 these Internet “hits” present the “debunking” of the myth that football does, indeed, have a relationship with an increase in domestic violence. Given the vicious attacks that White et al. (1992) endured, it is not surprising that the “debunking” seems to be the final word—at least on the streets that are the Internet highway.

This particular study—although borne out of newsroom experience and inductive reasoning—benefited greatly from the experiences of the two earlier research groups and from the help of the Philadelphia Police Department. The northern Virginia study looked at aggregated hospital data for trauma admissions, which may or may not have been a result of domestic violence. The Los Angeles study compared weekly averages of domestic violence calls-for-service during football season compared to the same averages during non-football season. Thanks to the Philadelphia Police Department, this study was able to pin down specific domestic violence arrests on the exact day of the football games, looking at the coordinating times of day.

What was found is that football gamedays produce higher numbers of domestic violence arrests than the comparable, non-sports Sundays (n=22). This was the largest comparison set and the most significant, because it ruled out some confounding factors.

Additionally, the study found that football gamedays produced higher numbers of domestic violence arrests than the other three major professional sports. The average football gameday is more dangerous to women—as victims of domestic violence—than the other days of the year.

While this study includes only one year and only one city, it does provide a direction for further study. In fact, the findings point toward a few follow-up studies— both replication and corollary studies. 143

To assess the generalizability of this research, a follow-up study--using the same methodology--could be conducted in another NFL city. It is crucial that the hour-by-hour domestic violence incident data is available. One such city is Denver. Denver is also home to one team in each of the major sports, but is obviously located in a western state and a city with a smaller population, but a larger geographical location. Unlike the Los

Angeles situation, where the fans had lost interest and the teams left the area, the Denver

Broncos have been a successful franchise and have a dedicated fan base. Denver would provide an excellent contrast to Philadelphia, if the same kind of data were available.

The unexpected but unsurprising hockey result should be further explored. Given the much longer NHL season, the hockey study design would have to be adjusted. In comparison to basketball and baseball in this dissertation, hockey games were clearly associated with more domestic violence arrests. While it is true that the number of hockey gamedays was very small, the basketball and baseball gamedays were not much greater. Additionally, in order to compete with the “hyped” football gameday, only ‘big games” were chosen, but that is also the case for the basketball and baseball gamedays.

Further, the concentration of domestic violence arrests within the three hours of the actual hockey game time was striking and certainly bears investigation.

Finally, the unsettling finding that domestic rape was more significantly related to football gamedays than any other sports’ gamedays, than the comparison Sundays, and than the holidays associated with drinking deserves examination.

Sports and violence has clearly found a place in the European journals of psychology and criminology, in Canada there are studies of hockey fans, and here in the

United States, in the “sociology of sport.” In the European research, the focus is on 144 hooliganism and rightly so, but in the United States, sports fan aggression does not take the same form. While the United States certainly has many highly-identified sports fans

(as witnessed by the sheer billions of dollars spent by sports fans each year), there are not the incidents of hooliganism found in Europe, Asia, and South America. Something is different about the way sports fans express their aggression in North America from the rest of the world.

This dissertation does not attempt to address that larger question, but does suggest that American criminology needs to embrace sports and crime the way other countries’ criminologists do. And if the findings in this dissertation are replicated, the possibility of the media/copycat framework must be considered. The home games versus away games part of this dissertation—with no statistical difference between the two groups and with the actual number of domestic violence arrests being higher during away games—lends support to this copycat framework and may very well be the key to the difference between North American fans and their counterparts in the rest of the world.

For criminology to grow, new areas of study must be subsumed by the field. The intersect of sports and crime has been primarily left to the practitioners—police and the court system. While this puts the emphasis on the punitive aspect of the criminal justice system, understanding its nature is the strength of the research aspect. Informing policy is the most effective use of this strength and it is hoped that the work of this study will further that goal. 145

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APPENDIX

TABLE. BASKETBALL, BASEBALL, AND HOCKEY—“BIG GAMES” DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 2/9 0 2 7 7 0 16 3/23 2 0 6 6 0 14 4/12 2 1 9 1 0 13 4/15 7 0 8 5 0 20 4/17 3 0 6 2 0 11 4/19 3 0 8 2 0 13 4/25 3 0 5 4 0 12 2/9 0 2 7 7 0 16 4/5 4 0 5 4 0 13 4/19 3 0 7 2 0 12 4/22 2 0 4 5 0 11 4/24 1 0 11 0 0 12 4/30 0 0 7 2 0 9 10/12 3 0 7 0 0 10 10/19* 1 1 9 3 0 14 10/28 2 0 3 1 0 6 10/31 0 0 8 5 0 13 11/2 3 0 6 3 0 12 11/4 1 0 7 2 0 10 TOT 40 6 130 59 0 235 158

HOCKEY DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 2/9 0 2 7 7 0 16 3/23 2 0 6 6 0 14 4/12 2 1 9 1 0 13 4/15 7 0 8 5 0 20 4/17 3 0 6 2 0 11 4/19 3 0 8 2 0 13 4/25 3 0 5 4 0 12 TOT 20 3 49 27 0 99

BASKETBALL & BASEBALL DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 2/9 0 2 7 7 0 16 4/5 4 0 5 4 0 13 4/19 3 0 7 2 0 12 4/22 2 0 4 5 0 11 4/24 1 0 11 0 0 12 4/30 0 0 7 2 0 9 10/12 3 0 7 0 0 10 10/19* 1 1 9 3 0 14 10/28 2 0 3 1 0 6 10/31 0 0 8 5 0 13 11/2 3 0 6 3 0 12 11/4 1 0 7 2 0 10 TOT 20 3 81 32 0 136

159

COMPARISON SUNDAYS DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 2/15 1 1 4 1 0 7 3/15 0 0 5 3 0 8 7/19 3 0 5 3 0 11 8/17 0 0 6 5 0 11 2/22 4 0 2 0 0 6 3/1 2 1 3 2 0 8 3/8 2 0 6 2 1 11 3/22 1 0 9 3 0 13 3/29 0 0 8 2 0 10 5/3 1 0 6 1 0 8 5/10 2 0 5 3 0 10 5/17 0 0 4 2 0 6 5/31 1 0 4 7 0 12 6/7 1 0 5 2 0 8 6/14 1 0 4 0 0 5 6/21 0 0 3 3 0 6 6/28 0 0 2 3 0 5 7/5 1 0 4 2 0 7 7/12 0 0 4 4 0 8 7/26 0 0 4 4 0 8 8/2 0 0 3 6 0 9 8/9 1 0 11 0 0 12 TOT 21 2 107 58 1 189

TABLE . EAGLES’ HOME GAMES DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 9 4 1 17 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/29 3 0 9 2 0 14 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 TOT 14 5 75 20 1 95

160

TABLE. EAGLES’ AWAY GAMES DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 9/13 4 2 13 4 2 25 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 12/6 3 0 9 5 1 18 12/13 1 0 6 3 0 10 TOT 15 2 60 27 5 109

TABLE. GAMES AGAINST RIVALS DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14 11/1 7 0 9 2 0 18 11/8 0 2 8 3 0 13 11/29 3 0 9 2 0 14 12/13 1 0 6 3 0 10 TOT 19 5 57 26 3 110

TABLE. GAMES AGAINST NON-RIVALS DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 11/15* 1 0 11 6 1 13 11/29 3 0 9 2 0 14 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 9/13 4 2 13 4 2 25 TOT 14 5 78 18 2 145

161

TABLE. EAGLES WINS DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 19

TABLE. EAGLES LOSSES DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 1/18 1 0 11 2 0 14 10/18 3 0 9 4 1 17 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19

TABLE. EAGLES’ REGULAR SEASON GAMES DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 9/13 4 2 13 4 2 25 9/20 0 1 14 4 0 19 9/27 0 0 8 2 0 10 10/11 3 0 12 2 0 17 10/18 3 0 9 4 1 17 10/26 1 0 7 2 0 10 11/1 7 0 9 2 0 18 11/8* 0 2 8 3 0 13 11/15* 1 0 11 6 1 19 11/22 2 0 5 3 0 10 11/29 3 0 9 2 0 14 12/6 3 0 9 5 1 18 12/13 1 0 6 3 0 10 12/20 0 2 8 1 0 11 12/27 1 0 10 2 0 13 162

TABLE. EAGLES’ PLAYOFF GAMES DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 1/4* 4 1 4 5 0 14 1/11 3 2 10 9 3 27 1/18 1 0 11 2 0 14

HOLIDAYS DAY VIOLATION VIOLATIONPO SIMPLE AGGRAV DOMRAPE TOT 2/14 4 1 10 4 0 19 3/17 2 1 6 2 0 11 4/12 2 1 7 1 0 11 5/25 0 2 14 8 0 24 7/4 3 1 14 4 0 22 9/7 2 0 6 7 0 15 12/15 1 0 6 1 1 9 12/31 2 1 8 2 0 13 TOT 16 7 71 29 1 124

163

164 165

NPAR 166 167 168

TESTS /M-W= TOTAL BY EVENT(1 2) /MISSING ANALYSIS.

NPar Tests

Notes

Output Created 18-Feb-2011 18:17:48

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= TOTAL BY EVENT(1 2) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.015

0:00:00.031

112347

a.Based on availability of workspace memory.

[DataSet1] G:\Mydata.sav

169

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

TOTALDVINCIDEN FOOTBALL 20 14.75 295.00

TS 8 13.88 111.00

28

Test Statisticsb

TOTALDVINCIDENTS

Mann-Whitney U 75.000 Wilcoxon W 111.000 Z -.255 Asymp. Sig. (2-tailed) .799 Exact Sig. [2*(1-tailed Sig.)] .823a

a. Not corrected for ties.

b. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= TOTAL BY EVENT(1 2) /MISSING ANALYSIS.

170

NPar Tests

Notes

Output Created 18-Feb-2011 18:18:47

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= TOTAL BY EVENT(1 2) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.015 171

0:00:00.016 Elapsed Time 112347

a.Based on availability of workspace memory.

[DataSet1] G:\Mydata.sav

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

TOTALDVINCIDEN FOOTBALL 20 14.75 295.00

TS 8 13.88 111.00

28

Test Statisticsb

TOTALDVINCIDENTS

Mann-Whitney U 75.000 Wilcoxon W 111.000 Z -.255 Asymp. Sig. (2-tailed) .799 Exact Sig. [2*(1-tailed Sig.)] .823a

a. Not corrected for ties. 172

b. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= TOTAL BY EVENT(1 3) /MISSING ANALYSIS.

NPar Tests

Notes

Output Created 18-Feb-2011 18:20:02

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= TOTAL BY EVENT(1 3) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.016

0:00:00.014

112347

a.Based on availability of workspace memory.

173

[DataSet1] G:\Mydata.sav

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

TOTALDVINCIDEN FOOTBALL 20 14.68 293.50

TS 7 12.07 84.50

27

Test Statisticsb

TOTALDVINCIDENTS

Mann-Whitney U 56.500 Wilcoxon W 84.500 Z -.751 Asymp. Sig. (2-tailed) .453 Exact Sig. [2*(1-tailed Sig.)] .464a

a. Not corrected for ties.

b. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= TOTAL BY EVENT(1 4) /MISSING ANALYSIS.

174

NPar Tests

Notes

Output Created 18-Feb-2011 18:20:57

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= TOTAL BY EVENT(1 4) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.016

0:00:00.032

112347

a.Based on availability of workspace memory.

175

[DataSet1] G:\Mydata.sav

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

TOTALDVINCIDEN FOOTBALL 20 19.80 396.00

TS 12 11.00 132.00

32

Test Statisticsb

TOTALDVINCIDENTS

Mann-Whitney U 54.000 Wilcoxon W 132.000 Z -2.584 Asymp. Sig. (2-tailed) .010 Exact Sig. [2*(1-tailed Sig.)] .009a

a. Not corrected for ties.

b. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= TOTAL BY EVENT(1 5) /MISSING ANALYSIS.

176

NPar Tests

Notes

Output Created 18-Feb-2011 18:21:47

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= TOTAL BY EVENT(1 5) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.000

0:00:00.000

112347

a.Based on availability of workspace memory.

177

[DataSet1] G:\Mydata.sav

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

TOTALDVINCIDEN FOOTBALL 20 30.83 616.50

TS 22 13.02 286.50

42

Test Statisticsa

TOTALDVINCIDENTS

Mann-Whitney U 33.500 Wilcoxon W 286.500 Z -4.716 Asymp. Sig. (2-tailed) .000

a. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= DOMRAPE BY EVENT(1 5) /MISSING ANALYSIS.

178

NPar Tests

Notes

Output Created 18-Feb-2011 18:23:31

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= DOMRAPE BY EVENT(1 5) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.000

0:00:00.000

112347

a.Based on availability of workspace memory.

[DataSet1] G:\Mydata.sav

179

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

DOMESTIC RAPE FOOTBALL 20 24.38 487.50

22 18.89 415.50

42

Test Statisticsa

DOMESTIC RAPE

Mann-Whitney U 162.500 Wilcoxon W 415.500 Z -2.233 Asymp. Sig. (2-tailed) .026

a. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= DOMRAPE BY EVENT(1 2) /MISSING ANALYSIS.

NPar Tests

180

Notes

Output Created 18-Feb-2011 18:24:20

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= DOMRAPE BY EVENT(1 2) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.000 0:00:00.033

112347

a.Based on availability of workspace memory.

[DataSet1] G:\Mydata.sav

181

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

DOMESTIC RAPE FOOTBALL 20 15.28 305.50

8 12.56 100.50

28

Test Statisticsb

DOMESTIC RAPE

Mann-Whitney U 64.500 Wilcoxon W 100.500 Z -1.039 Asymp. Sig. (2-tailed) .299 Exact Sig. [2*(1-tailed Sig.)] .438a

a. Not corrected for ties.

b. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= DOMRAPE BY EVENT(1 3) /MISSING ANALYSIS.

NPar Tests

182

Notes

Output Created 18-Feb-2011 18:25:19

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= DOMRAPE BY EVENT(1 3) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.000 0:00:00.000

112347

a.Based on availability of workspace memory.

[DataSet1] G:\Mydata.sav

183

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

DOMESTIC RAPE FOOTBALL 20 15.05 301.00

7 11.00 77.00

27

Test Statisticsb

DOMESTIC RAPE

Mann-Whitney U 49.000 Wilcoxon W 77.000 Z -1.598 Asymp. Sig. (2-tailed) .110 Exact Sig. [2*(1-tailed Sig.)] .263a

a. Not corrected for ties.

b. Grouping Variable: TYPE OF HOLIDAY

NPAR TESTS /M-W= DOMRAPE BY EVENT(1 4) /MISSING ANALYSIS.

NPar Tests

184

Notes

Output Created 18-Feb-2011 18:26:21

Comments

Input Data G:\Mydata.sav DataSet1 Filter Weight Split File N of Rows in Working Data File 69 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Statistics for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /M-W= DOMRAPE BY EVENT(1 4) /MISSING ANALYSIS.

Resources Processor Time 0:00:00.000 0:00:00.000

112347

a.Based on availability of workspace memory.

[DataSet1] G:\Mydata.sav

185

Mann-Whitney Test

Ranks

TYPE OF HOLIDAY N Mean Rank Sum of Ranks

DOMESTIC RAPE FOOTBALL 20 18.30 366.00

12 13.50 162.00

32

Test Statisticsb

DOMESTIC RAPE

Mann-Whitney U 84.000 Wilcoxon W 162.000 Z -2.059 Asymp. Sig. (2-tailed) .039 Exact Sig. [2*(1-tailed Sig.)] .170a

a. Not corrected for ties.

b. Grouping Variable: TYPE OF HOLIDAY

GET FILE='E:\Mydata.sav'. DATASET NAME DataSet1 WINDOW=FRONT. SAVE OUTFILE='E:\Mydata.sav' /COMPRESSED. SAVE OUTFILE='E:\Mydata.sav' /COMPRESSED.

186

FACT SHEET FOR GOVERNOR RENDELL There have been two previous studies that looked at the relationship between watching televised professional football games and domestic violence. • The first one, conducted in northern Virginia and involving the Redskins showed statistical significance between Redskins wins and an increase in female emergency room visits. After this study was published in a “mainstream” news article, there were a great many misconceptions proliferated. The researchers were social scientists and not media savvy—their words were twisted and the findings of their study were then relegated to “feminist exaggeration.” This will not happen with my study because I have years of media experience and because I have notified the NFL of my study in advance. • The second study was conducted in Los Angeles with the dependent variable bring “domestic violence calls- for-service in LA County.” The study showed a relationship during the first year of the study, but not the second. There was a design flaw that no one noticed because they did not factor in the NFL black-out rule. Additionally, it is difficult to parse out the data when there are two independent variables in the hypothesis; for example, Rams and Raiders. This is why Philadelphia is a good choice for my study as opposed to the Jets or Giants. Given that both studies showed a statistical significance (when there was no flaw in the design), it is reasonable to think there may be a relationship in this study. In order to achieve better results, the present study will measure two dependent variables—looking at both the calls-for-service in Philadelphia and the hospital admissions of women. Of key importance here is what happens next—what are the policy implications from the study and how can they be creatively 187 and effectively applied? Can the sport of football be more recognized for athleticism and less associated with violence? 188

00:00 TO 12:59 AM 12:59 TO 00:00 1:59AM TO 1:00 AM 2:59 TO 2:00 AM 3:59 TO 3:00 4:59AM TO 4:00 5:59AM TO 5:00 6:59AM TO 6:00 AM 7:59 TO 7:00 8:59AM TO 8:00 9:59AM TO 9:00 AM 10:59 TO 10:00 11:59AM TO 11:00 PM 12:59 TO PM 12:00 PM 1:59 TO 1:00 2:59PM TO 2:00 3:59PM TO 3:00 PM 4:49 TO 4;00 PM 5:59 TO 5:00 PM 6:59 TO 6:00 PM 7:59 TO 7:00 8:59PM TO 8:00 9:59 TO 9:00 10:59PM TO 10:00 PM 11:59 TO 11:00 Total Grand

PM

TIME MONDAY 0111 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0112 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0212 0 4 0 0 0 2 1 0 0 0 0 0 3 2 1 1 0 2 2 0 2 0 0 1 21 0232 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 2 0407 0 1 1 0 1 1 0 0 0 1 3 1 3 4 2 1 4 0 5 4 3 0 2 2 39 0408 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 3 0409 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 2 0410 11 6 2 4 2 1 2 3 4 4 6 7 2 2 3 3 1 5 5 6 5 6 16 2 108 0417 9 8 3 6 2 1 1 2 2 5 9 8 6 3 10 1 9 4 15 9 8 9 5 7 142 0418 4 2 3 1 3 1 0 1 1 2 0 0 3 3 3 3 5 0 3 5 2 3 4 2 54 0815 50 36 22 29 18 11 8 12 27 44 36 38 41 47 38 31 35 59 52 48 58 47 36 32 855 2676 2 0 2 1 0 5 1 2 2 3 1 2 5 3 1 3 4 5 10 9 2 2 2 3 70 2686 14 3 8 3 2 1 6 3 18 13 8 19 6 15 21 14 27 22 33 18 24 17 14 11 320 3303 558 343 280 188 127 96 83 108 274 314 327 345 338 318 317 236 479 456 497 524 511 508 462 345 8034 3305 28 6 6 7 9 9 1 18 30 20 23 25 24 38 46 29 112 118 95 97 81 85 54 31 992 MONDAY TOTAL 409 328 239 164 129 103 149 358 406 413 446 432 435 442 324 677 671 718 720 697 677 596 436 10645

TUESDAY 0111 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0114 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0212 0 2 0 0 0 1 1 1 0 0 0 1 2 1 2 1 2 4 4 1 0 0 0 1 24 0232 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0407 4 1 3 1 0 2 0 1 0 1 1 1 1 0 4 1 2 3 0 3 2 3 3 4 41 0409 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 2 0410 8 8 1 1 3 1 0 1 2 1 4 3 4 4 1 2 5 5 2 6 6 4 5 5 82 0417 8 6 2 2 2 2 0 0 4 5 15 2 3 7 3 3 16 10 11 4 7 13 10 6 141 0418 3 0 0 0 1 1 0 0 1 4 1 0 2 0 2 1 3 2 2 3 4 1 4 3 38 0815 48 36 25 9 17 9 4 8 25 29 32 34 43 33 38 25 44 49 39 45 39 49 43 44 767 2676 10 8 4 5 1 0 2 1 7 0 2 4 8 5 1 5 3 6 7 5 4 6 5 2 101 2686 14 5 9 7 2 3 3 4 14 13 16 19 13 20 13 8 39 26 28 25 31 21 15 18 366 3303 530 337 255 166 105 101 102 126 313 295 313 301 301 322 292 222 507 473 469 460 450 535 418 334 7727 3305 41 12 11 7 8 9 10 19 28 18 46 50 30 51 45 55 104 101 100 91 68 102 44 25 1075 TUESDAY TOTAL 666 416 310 198 139 129 122 161 395 366 430 415 407 444 401 323 725 679 662 643 611 735 547 443 10367

WEDNESDAY 0111 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 2 0114 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0212 0 0 1 0 2 1 0 0 1 0 1 1 1 3 0 1 1 2 1 3 1 1 0 0 21 0232 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0407 1 5 1 0 0 0 0 0 0 1 0 3 1 0 0 1 0 0 1 2 3 1 1 2 23 0408 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 1 0 4 189

0409 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 3 0410 3 4 6 5 3 1 2 1 4 6 4 4 3 5 0 5 3 4 4 4 5 4 4 3 87 0417 7 4 5 5 2 2 5 2 4 5 5 7 6 3 5 5 9 3 6 8 4 5 7 10 124 0418 4 4 2 3 0 2 0 1 1 1 4 0 3 1 2 2 4 3 3 3 0 5 1 1 50 0815 33 44 26 14 11 9 13 8 32 33 23 32 28 34 20 28 43 45 49 45 40 56 44 32 742 2676 4 4 0 1 1 2 3 2 3 0 2 3 2 2 3 3 7 3 6 5 7 1 1 6 71 2686 20 11 3 1 2 4 1 4 19 11 12 11 11 16 16 9 34 29 23 26 25 17 25 16 346 3303 520 357 232 158 125 106 83 121 289 272 306 285 326 338 259 215 467 443 472 455 493 480 424 330 7556 3305 44 15 10 7 5 8 13 28 30 18 27 42 44 42 39 37 101 81 107 78 80 86 55 36 1033 WEDNESDAY TOTAL 637 448 286 195 151 135 120 168 383 347 384 388 426 445 344 307 669 613 673 631 658 656 565 436 10065

THURSDAY 0111 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 3 0114 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 3 0116 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 212 1 0 0 1 0 1 0 0 0 2 0 2 0 1 0 0 4 1 2 3 0 1 2 0 21 0232 0 0 0 0 0 0 1 0 0 3 0 0 0 0 0 0 0 1 0 0 1 0 1 0 7 0407 5 1 2 0 1 0 0 1 1 0 2 2 2 1 2 0 1 1 2 1 1 2 3 0 31 0408 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0409 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0410 8 2 7 3 3 3 3 3 4 3 3 4 3 3 1 4 3 2 4 4 8 5 6 12 101 0417 15 6 2 1 3 2 1 3 3 6 2 3 4 3 9 2 3 7 5 8 8 5 5 10 116 0418 1 1 1 1 2 2 0 0 1 3 1 1 3 5 3 2 0 3 4 2 2 2 1 5 46 0815 49 35 34 26 14 12 3 13 27 35 26 35 33 44 27 29 49 43 43 50 43 47 39 33 789 2676 5 7 2 4 1 2 0 0 2 3 4 7 4 6 2 4 2 9 4 2 4 8 1 0 83 2686 19 2 7 3 4 2 2 2 7 15 6 10 9 11 11 15 35 18 21 26 14 23 16 12 290 3303 543 367 280 196 142 84 98 113 265 304 307 279 348 335 284 229 436 410 460 427 482 496 432 306 7623 3305 47 14 3 9 7 7 7 22 31 16 30 26 38 33 40 39 88 81 84 91 62 82 53 29 939 THURSDAY TOTAL 694 435 338 244 177 115 115 159 341 390 382 369 445 442 380 324 622 576 629 615 625 672 559 408 10056

FRIDAY 0111 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0114 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0116 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0212 1 1 0 0 1 0 0 0 0 1 1 2 1 1 1 0 3 0 1 0 0 1 1 0 16 0232 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 2 0 0 0 5 0407 2 2 1 1 1 1 0 0 1 2 2 3 0 2 3 2 2 0 3 3 1 3 3 5 43 0408 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0410 7 4 3 3 6 1 1 2 2 3 4 2 3 2 5 4 4 3 2 6 6 7 7 7 94 0417 5 4 7 3 4 5 1 2 7 8 3 7 2 7 8 9 4 6 4 5 6 4 4 8 123 0418 1 3 1 3 0 1 1 1 0 1 2 6 1 3 4 3 3 2 2 0 2 3 3 5 51 0815 51 31 28 29 14 10 6 7 26 32 32 37 40 32 30 37 42 49 49 45 39 45 42 37 790 2676 8 4 5 1 0 0 0 2 4 4 7 4 6 4 5 1 4 5 5 6 3 5 4 3 90 2686 9 15 5 5 0 2 4 2 10 11 7 20 22 17 14 15 23 20 22 16 22 14 13 3 291 3303 543 370 266 205 141 125 102 113 268 298 268 320 302 325 284 239 459 519 520 468 482 509 419 367 7912 3305 39 14 6 4 10 8 8 30 35 18 31 37 30 41 50 36 85 74 69 81 59 72 26 24 887 FRIDAY TOTAL 668 448 322 254 177 153 123 159 353 381 357 438 407 434 405 346 629 678 678 630 622 663 522 459 10306

SATURDAY 0111 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0114 0 0 0 0 0 1 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0116 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 4 0212 0 0 2 0 0 1 1 0 1 2 0 2 1 0 1 0 1 1 3 1 0 1 0 0 18 0232 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 0 0 1 7 190

0407 1 4 2 1 1 1 0 0 0 3 1 4 1 2 1 4 2 1 2 2 4 3 1 3 44 0408 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0410 9 7 15 2 5 6 2 3 0 6 3 5 7 2 3 5 2 6 6 3 5 10 10 10 132 0417 9 5 8 3 4 4 4 2 2 9 3 6 6 8 5 5 6 5 8 9 5 6 11 3 136 0418 5 3 2 1 4 4 2 0 5 0 2 0 4 6 0 2 4 6 1 0 3 5 1 3 63 0815 60 47 47 43 22 26 23 15 28 32 34 39 45 36 49 25 52 49 37 49 47 60 42 40 947 2676 5 6 2 4 3 4 2 1 3 5 8 6 9 3 3 7 5 6 2 4 2 7 5 3 105 2686 24 10 5 7 3 4 1 2 10 14 12 17 17 14 12 16 18 15 20 22 16 14 13 8 294 3303 619 474 420 389 283 184 127 119 280 395 487 454 446 483 395 321 469 421 421 394 437 441 453 397 9309 3305 36 10 9 11 7 5 11 37 31 25 44 53 45 38 28 37 56 36 27 44 34 39 24 30 717 SATURDAY TOTAL 768 566 514 462 333 240 174 179 360 491 596 586 581 593 497 423 616 548 527 529 553 587 561 499 11783

SUNDAY 0111 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 3 0114 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0115 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0116 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0212 0 0 0 0 0 2 1 0 0 2 0 1 1 2 1 1 7 1 0 1 1 0 1 1 23 0232 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0407 2 3 2 0 2 0 1 0 2 0 1 4 4 1 1 4 1 0 3 2 3 1 1 1 39 0409 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2 0410 7 14 5 6 4 7 1 0 0 3 3 6 7 4 2 8 4 4 7 7 8 3 4 8 122 0417 5 9 9 8 6 9 5 2 4 7 11 6 7 4 1 14 9 5 7 6 13 10 4 7 168 0418 2 6 2 4 2 1 1 0 1 6 2 2 3 1 0 3 5 6 1 2 3 3 5 1 62 0815 77 64 50 61 50 25 9 19 21 34 40 36 54 44 51 36 64 46 56 54 45 53 50 40 1079 2676 5 6 2 1 7 3 2 2 6 2 5 4 3 4 2 4 6 2 3 1 3 3 3 1 80 2686 17 6 9 9 2 2 5 3 6 9 13 11 9 24 18 15 26 23 22 21 17 16 16 7 306 3303 636 513 435 350 289 183 142 117 245 310 473 526 441 502 418 352 558 508 548 550 527 519 459 359 9960 3305 27 16 11 7 6 8 4 15 28 20 32 33 31 39 32 40 59 61 37 48 39 42 27 18 680

191

VITA

Beth Adubato

Born: Montclair, New Jersey Graduated: Our Lady of the Valley High School Attended the College of William and Mary B..A., English, Rutgers University, Newark, NJ, 1996 M.A., Criminal Justice, School of Criminal Justice, Rutgers University, Newark, NJ, 2004 M.P.A.P., Public Affairs and Politics, Edward J. Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ 2004 Ph.D., Criminal Justice, School of Criminal Justice, Rutgers University, Newark, NJ, 2011

ACADEMIC AWARDS AND HONORS Recipient, Raimondo Fellowship, Eagleton Institute of Politics, 2001-2002 Recipient, Excellence Fellowship, School of Criminal Justice, Rutgers, 2000-2002 Member of Phi Beta Kappa, Rutgers, 1996 David Diorio Award for Excellence in English, Rutgers, 1996 Graduated with College Honors and Highest Honors, Rutgers, 1996

PUBLICATIONS Grammar for Grownups, 2009 Grammar for Grownups II, 2011 New Jersey Department of Corrections, Analysis of the Budget, prepared backgrounder on New Jersey's female prison population, 2002

PROFESSIONAL WORK EXPERIENCE News Reporter, News 12 New Jersey, Freelance Reporter for News and Sports, Cut-in Anchor, 2005 to Present News Anchor, Court TV, Freelance, 2003-2004 Sports and Feature Reporter, Metro TV, New York, Appeared on “The Sports Section,” “NY Stories,” and “Gotham TV,” 2000-2003 Weekend Sports Anchor, WIAT-TV, CBS Affiliate, Birmingham, Alabama, 1998-2000 Morning News Anchor, WICU-TV, NBC Affiliate, Erie, Pennsylvania, 1997-1998 Evening News Anchor, WBKB-TV, NBC Affiliate, Alpena, Michigan, 1996-1997

PROFESSIONAL AFFILIATIONS Executive Board, PTL-AAUP-AFT (elected position) Executive Board, Women’s Political Caucus of New Jersey Alumni Committee, Eagleton Institute of Politics