Operation Candid Camera: Rialto Police Department’s Body-Worn Camera Experiment

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SOURCE CITED: POLICE CHIEF MAGAZINE

By William Farrar, Chief of Police, Rialto, California, Police Department, Executive Fellow with Police Foundation, Washington, D.C.

Police forces in the 21st century are facing a variety of new problems. Not only are law enforcement officials concerned with the day-to-day functions of municipal policing, they must also be mindful of increasing issues such as officer misconduct, use of force, accountability, community trust, and financial restrictions. In part, this is likely because of greater transparency and increased personal accountability at a time when many people carry smartphones and are constantly connected. It may also be a result of a cultural change within the police community that arguably does not accept misconduct as lightly as before. Either way, police organizations rarely experience community crises for failing to control crime. Instead, it is the failure of police to control police conduct that most often causes community distrust.

Highly publicized incidents of police misconduct can dramatically shake community confidence and one single high-profile event can seriously tarnish the image of an entire police department. The public’s perception of the frequency and appropriateness of force used by police is framed and influenced in large part by the media. The media has become flooded with unrealistic representations of law enforcement and the policing profession. Nightly police dramas and news programs depict officer-involved shootings, high-speed chases, and trips to the morgue to recover microscopic evidence, concepts that are reinforced by novels and films.

 

Key Terms
Control Conditions/Group:
the subjects who do not receive treatment—in this case, those who did not wear cameras
Deterrence Theory:
the idea that the fear of punishment discourages people from breaking rules (both actual and social) by fear of punishment
Dip Sampling:
technique to check that processes are being following properly without having to look at every single camera’s footage by “dipping” into the footage at random to ensure they were worn, etc.
Generalized Linear Model:
a form of linear statistical analysis used to test hypotheses that factors in known data (i.e., number of police-public encounters) and sources of error
Qualitative Data:
any captured data that cannot be expressed numerically
Self-Awareness Theory:
the idea that when people pay attention to themselves, through introspection or some other way (such as being recorded by cameras), they judge themselves according to their values
Standardized Mean Difference:
the difference between the mean (average) values for two groups, divided by the standard deviation (the spread of the data from the mean)
Treatment Conditions/Group:
the subjects who receive the treatment—in this case, wearing the cameras was the “treatment” (also known as the experimental group)

Research and Policing

There is a growing body of literature on how academics can (or rather, should) explore an evidence-based approach to policy testing. For example, a recent issue of the Journal of Experimental Criminology is dedicated to answering some of these questions. The volume deals with a host of problems academics face when trying to conduct research within the “what works” paradigm, which, more often than not, is based on the experimental design. Such work shows quite clearly the need for a valid and reliable “cookbook” of how to run experiments with government agencies in general and police forces more specifically. At the same time, to the best of the author's knowledge, the literature on how treatment providers, and explicitly police leaders, can lead their organizations into an evidence-based world is minimal at best. Can police chiefs introduce, implement, and maintain an experiment? If so, how can this be done, specifically in the context of testing a new initiative to deal with officer complaints and use of force? In order to answer this rather complex question, one particular case study will be explored: The Rialto Police Department’s Body-Worn Video Camera Experiment.

Over the years, the outcomes of this profession’s growing use of videos to record the actions of its personnel have been both good and bad. Until quite recently, this technology has been limited to dash-cams on police units or cameras built into Taser devices. Now, with advancements in technology, body-worn video cameras can be used to document every aspect of a law enforcement officer’s shift. Despite anecdotal coverage of these tools, the literature is very short on evidence. Reliable estimates of how the cam- eras actually work are lacking, and more crucially, whether they are effective and efficient. If they are effective, what impact do they have on the police-citizen encounter? Would they reduce the number of instances of use of force? Would they reduce the number of citizen complaints?

The Rodney King and Kelly Thomas incidents are potent reminders about the enormous power that police officers have and how things can go wrong. Both incidents are far reaching and signify just how disproportionate uses of force could shatter the reputation of the police and lead into a social cataclysm. There are somewhat similar cases taking place currently, despite efforts to stop such behavior through better training and prosecution of over-zealous officers.1 Are these incidents unavoidable?

A voluminous body of research, across various disciplines, has shown that when humans become self-conscious about being watched, they often alter their conduct. Accumulated evidence suggests that individuals who are aware they are being observed often embrace submissive or commonly accepted behavior, depending on the identity of the observer. What is less known, however, is what happens when the observer is not a “real person,” and whether being videotaped can have an effect on aggression and violence. For instance, would either the Rodney King or Kelly Thomas incidents been avoided had the officers known that they were being videotaped? Would frequency of police use of force or complaints be reduced if all interactions between officers and members of the public are under known electronic surveillance?

The Rialto Police Department has tested whether police body-worn cameras would lead to socially desirable behavior of the officers who wore them and/or the citizens these officers may encounter. These were individualized high-definition (HD) cameras that were installed on the officers’ uniforms, and systematically recorded every police-public interaction for 12 months. By randomly assigning 988 shifts into experimental and control shifts within a large randomized controlled field experiment, the department investigated the extent to which cameras affect human behavior and, specifically, reduce the use of force by police or citizen complaints. Broadly, the department put to test the implication of self-awareness to being observed on compliance and deterrence theory in real-life settings and explored the results in the wider context of theory and practice.

Self-Awareness Leading to Socially Desirable Behavior

Several lines of research across many disciplines of science suggest that most forms of species alter their behaviors once they are aware that they are being observed.2 In humans, a rich body of evidence on perceived social surveillance—self-awareness and socially desirable response—proposes that people adhere to social norms and alter their behavior because of the awareness that they are being observed.3 It seems that knowing with sufficient certainty that one’s behavior is observed affects various social cognitive processes. When feeling watched or judged, individuals experience public self-awareness, become more prone to socially acceptable behavior and feel a heightened need to cooperate with rules.4

Being observed doing something morally or socially wrong is often registered as behavior that can potentially lead to negative consequences, which is an outcome rational individuals tend to avoid.5 Several experiments in social psychology have uncovered this propensity to avoid negative outcomes, and the findings generally agree that individuals react compliantly to even the slightest cues indicating that somebody may be watching. For instance, it was found that these cues that signal how we ought to behave range from reputational (shame) to punishment for noncompliance.6These cues are more broadly explored under deterrence theory.

Generally speaking, deterrence theory relies heavily on self-awareness and how being watched would lead to socially desirable behaviors. Its theoretical roots are found in 18th-century enlightenment philosophy, and an extensive body of recent rigorous research across several categories of human behavior has shown that when certainty of apprehension for wrongdoing is high, socially and morally unacceptable acts are dramatically less likely to occur.7 Regarding crime and disorder, when consequences can be bleak (imprisonment, fines, etc.), people simply do not want to get caught. For instance, when meta-analyzing the available data from more than two dozen experiments on policing hot spots of crime, research has shown that police presence in high-crime areas specifically meant to increase the perceived certainty of apprehension can significantly reduce crime incidents at these hot spots compared to control conditions (d=.2, p<.001).

Thus, the physical presence of other people, especially rule-enforcers, either produces cooperative behavior or deters non-cooperative or noncompliant behavior.8 However, evidence further suggests that other less direct cues can also manipulate self-consciousness to socially desirable response. For example, the mere picture of a pair of eyes has been shown to deter people from noncompliance.9 Likewise, the presence of various stimuli such as mirrors can be used to situationally increase self-consciousness and, in turn, generate socially desirable behaviors.10

Far less is known about cameras and video cameras, though they are hypothesized to produce socially desirable behaviors as well. Much like live observers, mirrors, or pictures of eyes, cameras can make people self-conscious not only to the fact that they are being watched, but also to drive them into compliance—arguably to a greater extent than other stimuli tested thus far in research. When individuals become aware that a video camera is recording their actions, they also become self-conscious and aware that unacceptable behaviors are likely to be captured on film, and the perceived certainty of punishment is at its highest. “Getting-away” with rule breaking is far less convincible if you are being videotaped.

Despite this conceptual appeal of cameras and possible social control policies around their use, rigorous research on their effect is minimal. Thus far, the evidence on how cameras can potentially deter against morally and socially undesirable behaviors has been primarily collected on two subtypes of recording devices: closed-circuit televisions (CCTVs) and speed cameras. Both types are meant to trigger that perceptual mechanism of self-awareness: (passive) cameras are placed in public spaces in order to increase the perceived likelihood of being apprehended. The available meta-analysis of the evidence from 44 studies on the use of public-area CCTV has shown that the mechanism “works” in principle, insofar as cameras caused a modest (16 percent) decrease in crime in experimental areas compared with control areas. However, this overall result was largely driven by the effectiveness of CCTV schemes in car parks, which caused a 51 percent decrease in crime and not in more serious or violent crimes.11 Similarly, speed cameras were found to reduce the incidence of speeding, road traffic crashes, injuries, and deaths.12 A meta-analysis of 35 rigorous studies has found that, compared with controls, the relative reduction in proportion of vehicles speeding was up to 65 percent and up to 44 percent for fatal and serious injury crashes.

Yet the most prominent type of cameras, mobile cameras [body-worn], has been virtually ignored in psychology and social sciences. What are their effects on self-awareness? Could they promote socially desirable behavior? Can they be used as a social control mechanism? Although theoretically compelling, direct experimental research on how portable cameras affect human behavior is currently non-existent, let alone how people would behave in social contexts that require them to follow rules.

General Hypothesis

The hypothesis is that portable cameras would go beyond the limited impact that CCTV have had on expressive acts of violence in public spaces. CCTV cameras were found to be weak behavior modifiers not because of a flaw in the self-awareness paradigm or the deterrence theory; rather, the level of certainty of being apprehended necessary for the self-awareness mechanism, which would lead to socially desirable behavior, is not high enough in CCTV. If cameras are expected to influence behavior and to serve as cues that social norms or legal rules must be followed, then the cue “dosage” of awareness must be intense. Body-worn cameras are likely to create this effect.

In passing, it is noted that self-consciousness caused by active body-worn cameras will not necessarily lead people to follow rules, as this largely depends on who is holding the camera. In this research, however, the focus is solely on devices that were operated in the context of law enforcement. Therefore, the hypothesis is that rational beings, including police officers, are unlikely to embrace socially undesirable behavior when videotaped.

The specific questions examined by this experiment are (1) will wearing body-worn video cameras reduce the number (instances) of use of force by officers compared to the control group? and (2) will wearing body-worn video cameras reduce the number of complaints against officers compared to the control group?

Methods—Research Settings

The Rialto (California) Police Department tested these questions in a large field experiment by measuring the magnitude of the effect of wearing highly visible portable HD cameras by frontline officers on incidents of use of force. Rialto Police Department is a mid-sized agency that has jurisdiction over 28.5 square miles and services a population of 100,000 residents. The department employs 115 sworn police officers and 42 non-sworn personnel.

Participants

The department’s frontline officers participated in the experiment (n=54), but each patrol shift (team) was considered to be the unit of analysis. Frontline officers work seven days per week, in six shifts of 12 hours per day for a total 2,038 officer shift-hours per week. Each shift consists of approximately 10 officers who patrol the streets of Rialto and interact with offenders, victims, witnesses, and members of the public. When officers were assigned to the experimental group, they were instructed to wear HD cameras, which would then record all of these interactions.

 

 

Procedure and Random Allocation

The experiment began on February 13, 2012, and ran for 12 months. The experimental procedure included random assignment of all police shifts (teams) to either experimental or control conditions. “Experimental shifts” consisted of shifts in which officers were assigned to wear HD audio-visual recording apparatus that captured all police-public encounters during these shifts. “Control shifts” consisted of shifts in which officers were instructed not to wear the HD cameras. Integrity of assignment was maintained by both measuring the number of “footage-hours” against the assigned shifts as well as dip sampling dates of footage to ascertain that officers wore cameras as assigned.

The experimental procedure is illustrated in Table 1. As shown, there are 19 shifts during any given week and 54 frontline officers conducted patrols in six teams: Two teams work day shifts, three teams work nights, and two teams are cover shifts.

 

Table 1: Team Assignments During Experiment
  Mon Tues Wed Thurs Fri Sat Sun
Day Shift Team 2 Team 1 Team 1 Team 1 Team 3 Team 2 Team 2
Night Shift Team 5 Team 5 Team 5 Team 4 Team 4 Team 4 Team 3
Cover   Team 6 Team 6 Team 6 Team 6 Team 3  

Additionally, as shown in Table 2, shifts were randomly allocated to treatment and control conditions using the Cambridge Randomizer on a weekly basis. In total, the department assigned 988 (12 months) into 489 treatment and 499 control conditions. Using G*Power 3.1.3, the department estimated that this sample size can detect small effects of standardized mean difference of 0.2, in which the statistical significance level is 5 percent and estimated statistical power of 80 percent.13

Table 2: Allocation of Shifts to Experimental and Control Groups
  Mon Tues Wed Thurs Fri Sat Sun
Day Shift Exp't Exp't Control Exp't Exp't Control Exp't
Night Shift Exp't Control Control Exp't Control Exp't Exp't
Cover   Exp't Control Control Control Control  

Apparatus

The department collaborated with Taser International Inc. to provide all frontline officers with HD body-worn cameras. These body-mounted cameras capture video evidence from the officer’s perspective. Weighing 108 grams (fewer than 4 ounces) and small enough to place in the officer’s shirt pocket, the camera systems can be affixed to the hat, collar, shoulder, or specially designed Oakley sunglasses. During the Rialto study the officers were given the option of choosing which mounting system they preferred, although it was quickly discovered that wearing the cameras on the sunglasses or cap provided the best overall video, as the camera would naturally follow where the officer was looking. The unit is water resistant, the video is full color, and the battery life lasts for over 12 hours, making it ideal for the shift patterns of Rialto Police.

All data from the cameras were collated using a web-based computerized video management system developed by evidence.com. The software tracked and inventoried the evidence from all Taser International Inc. video cameras. The system automatically uploaded the officers’ videos at the end of their shifts, and the research team was granted full access to these rich data encompassing over 50,000 hours of police-public interactions.

Measures

Police General Orders require all officers to document any instance of use of force, which encompasses physical force more than a basic control or “compliance hold,” including use of OC spray, baton, Taser, canine bite, or firearm. Four main outcomes were examined to measure use of force. First, a standardized police tracking system called BlueTeam measures all recorded use of force incidents. The system enabled the research team to count how many incidents occurred during the experimental period in both experimental and control shifts and to verify the details of the incidents, such as whether the officer or the suspect initiated the incident.

Second, the police tracked formal complaints against officers with a software called IAPro. Citizens’ complaints are incidents where the reporting party has filed a grievance form against alleged misconduct or what they perceive as poor performance. Data captured on this system provided a count of the number of complaints filed against police officers as a proxy for use of force.

Third, the total number of contacts between the police and the public was measured. Any non-casual interaction with the public was recorded via computer-aided dispatch (CAD). These included attending to calls for service, formal advice given to individuals, collecting evidence and statements during any type of investigation, and other similar interactions. With this variable, the researchers were able to compute the rate of incidents per 1,000 police-public contacts.

Fourth, the team tracked all officers’ schedules and shifts via a computerized, web-based scheduling system called TeleStaff. TeleStaff is an automated scheduling system for public safety that includes a comprehensive workforce management platform that optimizes the scheduling, communications, and deployment of personnel.

Finally, the researchers analyzed the content of the videotapes in order to enrich the analysis with qualitative data. Here, they primarily focused on the incidents in which force was used; however, the data can be used more broadly to systematically observe police-public encounters and measure police performance and possibly elements of procedural justice, as well. The outcome of the choice to analyze the video contents was primarily a validation of the BlueTeam and IAPro reports in terms of the type of force used and how the incident was initiated.

Baseline Analysis

Table 3 lists the outcome variables at baseline, up to three years prior to the experiment. As shown, use of force is a relatively rare event, with approximately 65 incidents per year, or 1.46 incidents for every 1,000 police-public contacts. Similarly, complaints lodged by citizens against police officers are infrequent, with 28 grievances filed against officers in 2011 (about 0.7 for every 1,000 contacts). Police-public contacts data show that, on average, Rialto officers interacted with members of the public about 3,600 times per month (approximately 42 recorded contacts per shift).

Table 3: Historical and Experimental Data Used for Analysis
Use of Force, Citizens Complaints and Police-Public Raw Figures—
Baseline and Experimental Raw Data
  2009 2010 2011 02/2012–02/2013
Use of Force 70 65 60 25
Complaints 36 51 28 3
Police-Public Contacts 40,111 43,289

Statistical Procedure

Negative binomial Generalized Linear Model was used to model the data, given the distribution of the outcome data.14 Group assignment (experimental shifts/control shifts) was set as a predicting variable, and the dependent variables are the number of use of force incidents and the number of citizens’ complaints. Researchers also looked at the likelihood of use of force and the likelihood of citizens’ complaints by measuring the magnitude of the treatment effect using odds ratios (OR), and then the magnitude of the difference in terms of the rates of these measures per shift, using standardized mean difference (SMD).

Results

The department detected a significant treatment effect on use of force {B=-0.924 95% CI [(-.1806)-(-.042)]}. Shifts without cameras experienced twice as many incidents of use of force as shifts with cameras {OR=2.121; 95%CI = (0.907)-(4.960)}. The direction of the findings was mirrored by the difference in the rate of use of force per shift between treatment and control conditions, though not to the same magnitude (d=.140; CI 95% =.015-.265). The department also detected that, globally, the rate of use of force incidents per 1,000 contacts was reduced by 2.5 times compared to the 12 months prior to the experimental period (mean baseline=1.46; mean treatment=.33; mean control=.78).

Table 4, shows that 25 use-of-force instances occurred during the 12 months of the experiment (02/13/12 to 02/12/13) compared to 59 during the same date range (12 months) prior to the experiment (02/13/2011 to 02/12/2012). There were 8 use-of-force incidents on the experiment days (all of which were captured on the body-worn video cameras), and 17 on the control days. This represents at 60 percent reduction.

Table 4: Baseline and Experimental Use of Force Data
 

In terms of complaints against officers, the department was unable to compute a treatment effect as planned, since the overall reduction was so large that there were not enough complaints to conduct any meaningful analyses (only one complaint lodged for an incident that occurred during control conditions and two for incidents that occurred during treatment condition). Table 5 shows that there were 3 officer complaints during the 12 months of the experiment (02/13/12 to 02/12/13) compared to 24 during the same date range (12 months) prior to the experiment (02/13/2011 to 02/12/2012). This represents an 88 percent reduction.

Table 5: Baseline and Experimental Citizen Complaints Data
 

Police-public contacts were tracked to ensure there was no backfire effect by having the officers simply work less. Table 6 shows that the number of police-public contacts increased by more than 3,000 contacts.

Table 6: Baseline and Experimental Public Contacts Data
 

The qualitative analysis of the recorded footage—6,776 video files of 724 gigabytes of memory—and BlueTeam data reveal three major findings. First, the difference between the study conditions concentrated in less-severe cases: during experimental shifts in which use of force was required, police weapons were often not used. In all video-taped incidents (treatment condition) in which force was used by officers, the subject was clearly seen to be physically abusive or physically resisting arrest. On the other hand, in 5 incidents that occurred during control shifts (out of a total of 17 incidents), officers resorted to use of force without being physically threatened.

Second, in both experimental and control groups, the police used force via Taser guns, but Tasers were used to a far greater degree in the experimental arm (5 out of 8 and 7 out of 17, respectively). The incident logs suggest that Taser guns were used when officers were physically assaulted or threatened (by drunken suspects or while in pursuit of offenders). Lastly, the research team reviewed who initiated the use of force. All videotaped incidents are cases in which the physical contact was commenced by the member of the public, whereas in 4 out of the 17 control cases, the officer initiated the physical contact.

Discussion

In this experiment, the department tested for the first time the effect of body-worn video cameras on self-awareness and, ultimately, socially desirable behavior. The cameras were hypothesized to increase police officers’ self-consciousness and, therefore, increase their compliance to rules of conduct, especially concerning use of force. The findings suggest a more than 50 percent reduction in the total number of incidents of use of force compared to control-conditions, and nearly 10 times less citizens’ complaints than in the 12 months prior to the experiment.

The implications of these findings for psychosocial theories, particularly for the understanding of self-awareness are meaningful, but perhaps not unexpected. The department anticipated that the videotaped interactions would include fewer incidents of use of force because of the fundamental tendency of rational beings to exhibit more desirable behaviors when they know they are under surveillance, particularly in scenarios that require them to follow rules. What is surprising, however, is that the Rialto Police’s experiment appears to be the first field experiment that has tested this paradigm in real-life settings, at least under these conditions. Mobile cameras are everywhere, but at the same time, nowhere in social science research, insofar as studying their effect on compliance.

Therefore, this convergence of self-awareness theory with deterrence theory in the context of police-public relations is something of a terra nullius. Deterrence theory presupposes self-consciousness to being observed, but never really explored it with sufficient rigor. What is the measurable level of certainty that enables deterrence to take place? What is the threshold of cognitive attentiveness, under which the rule-breaker does not internalize the possibility of getting caught? At the very least, this experiment provides an example of a method to measure these dimensions. More broadly, however, the study was able to expose what happens when the level of certainty of apprehension for professional misconduct was set at 100 percent. These are social circumstances that are characterized with an inescapable panopticonic gaze.15 Future explorations of the nexus between deterrence and self-awareness of being observed will therefore have to scrutinize other contexts, other recording technologies, and other levels of certainty of apprehension.

In practical terms, the findings can easily be extended to not only other law enforcement agencies, but also to other professional arenas and social contexts. Leaders certainly can envision that any rule-enforcing profession can benefit from the intensified certainty of apprehension created by monitoring devices such as body-worn cameras.

Lastly, leaders cannot rule out the possibility that the cameras have (also) modified the behavior of those who interacted with the police. Members of the public with whom the officers communicated were also aware of being videotaped and, therefore, were likely to be cognizant that they ought to act cooperatively. However, no evidence was collected from these individuals to be able to ascertain the validity of this assumption. In spite of that, the psychological mechanisms ought to be substantially similar, although this is an avenue best explored experimentally in the future. ♦

Notes:
1For examples, see Nelson v. City of Davis, 685 F.3d 867 (9th Cir. 2012); Bryan v. McPherson, 608. F.3d 614 (9th Cir. 2010); Parker v. Gerrish, 547 F.3d 1 (1st Cir. 2008);Vinyard v. Wilson, 311. F.3d 1340 (11th Cir. 2002). 
2Tanya L. Chartrand and John A. Bargh, “The Chameleon Effect: The Perception–Behavior Link and Social Interaction,” Journal of Personality and Social Psychology 76, no. 6 (1999): 893–910, http://www.yale.edu/acmelab/articles/chartrand_bargh_1999.pdf (accessed November 19, 2013); Teresa L. Dziewecyznski, Amy C. Eklund, and Willliam J. Rowland, “Male 11-Ketotestosterone Levels Change as a Result of Being Watched in Siamese Fighting Fish, Betta Splendens,” General and Comparative Endocrinology 147, no. 2 (June 2006): 184–189; Edward E. Jones and Richard E. Nisbett, The Actor and the Observer: Divergent Perceptions of the Causes of Behavior (Morristown, NJ: General Learning Press, 1971), 79–94. 
3Robert A. Wicklund, “Objective Self-Awareness,” Advances in Experimental Social Psychology 8 (1975): 233–275; Delroy L. Paulhus, “Balanced Inventory of Desirable Responding (BIDR)” Acceptance and Commitment Therapy, Measures Package (1988): 41; Kristen Munger and Shelby J. Harris, “Effects of an Observer on Hand Washing in a Public Restroom,” Perceptual and Motor Skills 69, no. 3 (1989): 733–734.
4Will M. Gervais and Ara Norenzayan, “Like a Camera in the Sky? Thinking about God Increases Public Self-Awareness and Socially Desirable Responding,” Journal of Experimental Social Psychology 48, no. 1 (January 2012): 298–302; Shelley Duval and Robert A. Wicklund, A Theory of Objective Self-Awareness (New York: Academic Press, 1972); Lee Sproull, Mani Subramani, Sara Kiesler, Janet H. Walker, and Keith Waters, “When the Interface Is a Face,” Human-Computer Interaction 11, no. 2 (1996): 97–124; Manfred Milinski, Dirk Semmann, and Hans-Jürgen Krambeck, “Donors to Charity Gain in Both Indirect Reciprocity and Political Reputation,” Proceedings of the Royal Society of London, Series B: Biological Sciences 269, no. 1494 (May 2002): 881–883; Claus Wedekind and Victoria A. Braithwaite, “The Long-Term Benefits of Human Generosity in Indirect Reciprocity,” Current Biology 12, no. 12 (June 2002): 1,012–1,015; Pat Barclay, “Trustworthiness and Competitive Altruism Can Also Solve the ‘Tragedy of the Commons,’” Evolution and Human Behavior 25, no. 4 (July 2004): 209–220. 
5 Steven Klepper and Daniel Nagin, “The Deterrent Effect of Perceived Certainty and Severity of Punishment Revisited,” Criminology 27, no. 4 (2006): 721–746; Steven Klepper and Daniel Nagin, “Tax Compliance and Perceptions of the Risks of Detention and Criminal Prosecution,” Law and Society Review 23 (1989): 209. 
6Melissa Bateson, Daniel Nettle, and Gilbert Roberts, “Cues of Being Watched Enhance Cooperation in a Real-World Setting,” Biology Letters 2, no. 3 (September 2006): 412–414; Terence C. Burnham and Dominic D. P. Johnson, “The Biological and Evolutionary Logic of Human Cooperation.” Analyse & Kritik 27, no. 1 (2005): 113–135,http://analyse-und-kritik.net/en/2005-1/AK_Burnham_Johnson_2005.pdf; Kevin J. Haley and Daniel M.T. Fessler, “Nobody’s Watching? Subtle Cues Affect Generosity in an Anonymous Economic Game,” Evolution and Human Behavior 26 (2005): 2455–256,http://www.sscnet.ucla.edu/anthro/faculty/fessler/pubs/HaleyFesslerEyespots.pdf (accessed November 20, 2013); Ernst Fehr and Frédéric Schneider, “Eyes Are on Us, but Nobody Cares: Are Eye Cues Relevant for Strong Reciprocity?” Proceedings of the Royal Society, Series B: Biological Sciences 277, no. 1686 (May 2010): 1315–1323, http://rspb.royalsocietypublishing.org/content/277/1686/1315.full.pdf (accessed November 20, 2013); Barak Ariel, “Deterrence and Moral Persuasion Effects on Corporate Tax Compliance: Findings from a Randomized Controlled Trial,” Criminology 50, no. 1 (February 2012): 27–69; Robert Boyd, Herbert Gintis, and Samuel Bowles, “Coordinated Punishment of Defectors Sustains Cooperation and Can Proliferate When Rare,” Science 328, no. 5978 (April 2010): 617–620. 
7Cesare Beccaria, On Crimes and Punishment and Other Writings, trans. by Richard Davies (Washington D.C.: Carnegie Institute, 1995); Andrew von Hirsch, Anthony E. Bottoms, Elizabeth Burney, and P.O. Wikstrom, Criminal Deterrence and Sentence Severity: An Analysis of Recent Research (Oxford: Hart, 1999). 
8Robyn M. Dawes, Jeanne McTavish, and Harriet Shaklee, “Behavior, Communication, and Assumptions about Other People’s Behavior in a Commons Dilemma Situation,”Journal of Personality and Social Psychology 35, no. 1 (January 1977): 1–11; Elizabeth Hoffman, Kevin McCabe, Keith Shachat, and Vernon Smith, “Preferences, Property Rights, and Anonymity in Bargaining Games,” Games and Economic Behavior 7, no. 3 (November 1994): 346–380. 
9Max Ernest Jones, Daniel Nettle, and Melissa Bateson, “Effects of Eye Images on Everyday Cooperative Behavior: A Field Experiment,” Evolution and Human Behavior 32, no. 3 (May 2011): 172–178. 
10Steven J. Heine, Timothy Takemoto, Sophia Moskalenko, Jannine Lasaleta, and Joseph Henrich, “Mirrors in the Head: Cultural Variation in Objective Self-Awareness,”Personality and Social Psychology Bulletin 34, no. 7 (July 2008): 879–887; William M. Webb, Kerry L. Marsh, William Schneiderman, and Bob Davis, “Interaction between Self-Monitoring and Manipulated States of Self-Awareness,” Journal of Personality and Social Psychology 56, no. 1 (January 1989): 70–80. 
11Brandon C. Welsh and David P. Farrington, “Public Area CCTV and Crime Prevention: An Updated Systematic Review and Meta- Analysis,” Justice Quarterly 26, no. 4 (December 2009): 716–745. 
12Cecilia Wilson, Charlene Willis, Joan K. Hendrikz, Robyne Le Brocque, and Nicholas Bellamy, “Speed Cameras for the Prevention of Road Traffic Injuries and Deaths,” Cochrane Database of Systematic Reviews 11 Art. No.: CD004607 (2010). 
13Barak Ariel, Jordi Vila, and Lawrence. Sherman, “Random Assignment without Tears: How to Stop Worrying and Love the Cambridge Randomizer,” Journal of Experimental Criminology 8, no. 2 (June 2012): 193–208; J. Cohen, Statistical Power Analysis for the Behavioral Sciences (Hillsdale, N.J.: Lawrence Erlbaum Associates, 1969). 
14Noriszura Ismail and Abdul Aziz Jemain, “Handling Overdispersion with Negative Binomial and Generalized Poisson Regression Oodels,” Casualty Actuarial Society Forum(Winter 2007): 103–158, http://www.casact.org/pubs/forum/07wforum/07w109.pdf (accessed November 20, 2013). 
15Michel Foucault, Discipline & Punish: The Birth of the Prison (Second Vintage Books, May 1995).

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