Inconsistencies in Public Opinion of Body-Worn Cameras on Police: Transparency, Trust, and Improved Police–Citizen Relationships

Inconsistencies in Public Opinion of Body-Worn Cameras on Police: Transparency, Trust, and... Abstract Given the national interest in equipping police with body-worn cameras (BWCs), it is important to consider public attitudes concerning the technology. This article draws on the results of a national survey of citizen opinions of BWCs. The survey includes items related to general support for BWCs, opinions on their potential advantages, and attitudes towards their potential consequences. Results indicate that while there is general support for BWCs on police, opinions vary on the capacity of BWCs to increase transparency of police work, improve trust in police, and better police–citizen relationships. Introduction Advances in modern policing have often been associated with technological innovations (see Lynch (2016) for a review). Within this wider context of technology and policing, police departments across the USA have demonstrated an interest in body-worn cameras (BWCs) on officers for the better part of the last decade. This interest has greatly accelerated in recent years, however, as a result of several high-profile cases involving controversial interactions between police and citizens. These cases helped to generate a growing demand for increased accountability concerning police actions, especially officer use of force and deadly force in particular. In this regard, BWCs are often considered to be a tool that can help improve police–community relationships and enhance police legitimacy. The growing affordability of BWCs, the increasing experience with their use among different agencies, and the mounting incentives for departments to adopt BWCs, have also likely contributed to the swelling popularity of the technology. The federal government has also taken an interest in the role of BWCs for police departments, making it clear that local agencies should seriously consider adopting the technology. In late 2014, the White House proposed $75 million over 3 years to help purchase BWCs for local agencies as part of the President’s Community Policing Initiative (White House, 2014). Furthermore, although it recommended caution when adopting new tools, the President’s Task Force on 21st-century policing (created in response to the demand for greater police accountability) indicates that the use of technology in general—and BWCs specifically—can help to enhance transparency and build community trust (President’s Task Force, 2015). Although BWCs have become highly touted for their perceived benefits, evidence of BWC effectiveness remains limited, and research on the matter is still in its infancy. In particular, relatively little is known concerning public attitudes towards the technology. In this article, we examine public opinion of BWCs on police. We begin with a brief background on BWC research before turning to an analysis of survey data designed to determine public opinion of BWCs on officers. We focus on public expectations of the technology’s ability to achieve positive outcomes, including improved transparency, reduced excessive force, increased trust in policing, and better relations between police and citizens. Background Much of the published research on BWCs to date is descriptive in nature, describing their advantages to policing. White (2014), for example, discusses potential benefits and possible concerns with the technology. Potential benefits include the possibility of greater transparency of police activities since video recordings may be subject to public review, protection of citizens from police misconduct and/or unnecessary use of force, and protection of officers from false allegations of misconduct. BWCs can also help to improve police practice in other ways, such as gathering visual evidence and recording interviews with witnesses or victims. In addition, video from BWCs can be used for police training purposes. Among these potential benefits are several concerns involving BWCs (White, 2014). The financial and logistical resources needed to manage the technology, for example, can be a challenge for some agencies. Another major concern relates to the issue of privacy, particularly if video of an encounter between an officer and a private citizen is potentially available to the media or to the public through a public records request. In addition, BWCs could negatively influence the way that citizens communicate with officers, making them reluctant to reveal certain information knowing that their statements are recorded (Miller et al., 2014). There are many limits to the technology as well—a video record of an incident, for example, can still be open to interpretation in terms of the appropriateness of an officer’s actions (Ready and Young, 2014). Although currently limited, a growing body of research on BWCs has employed various empirical methods to examine the impact of the technology on officer behaviours or officer perceptions of BWCs.1 Many of these studies demonstrate the benefits of BWCs in terms of reducing police use of force and/or complaints of officer misconduct (Ariel et al., 2015, 2017; Jennings et al., 2015; Katz et al., 2015). Research also suggests that officers with BWCs may be more proactive in terms of initiating encounters with citizens, but do not become overly intrusive or invasive in their tactics (Ready and Young, 2015). Additional studies indicate that police themselves are generally supportive of BWCs on officers (Jennings et al., 2014), especially as they become more acquainted with the use of the technology (Katz et al., 2015). Current study Given the political and financial investments in BWCs, it is important to examine public perceptions of the technology. Some survey research has demonstrated strong support for BWCs in general (Pew Research Center, 2014; Sousa et al., 2015; YouGov, 2015). However, less is known about the public’s faith in the prospective positive consequences of BWCs. In other words, few have examined the public’s belief in the ability of BWCs to actually fulfil the promises of improved transparency, increased trust, and better relations between police and citizens. To explore these issues, we rely on survey research first reported by Sousa et al. (2015). The survey was designed to determine people’s opinions of BWCs on police. Importantly, specific items asked respondents to indicate their confidence in the ability of BWCs to impact transparency, trust, use of force, relationships between police and citizens, and tensions between police and minority communities. We are, therefore, able to examine these variables while also considering the influence of respondents’ demographic characteristics. The conceptual model underlying this study involves both direct and indirect effects. As illustrated in Fig. 1, various demographic factors are expected to influence support for police use of BWCs both directly and indirectly through the impact of the perceived consequences of this technology. Individuals’ socio-economic characteristics (e.g. gender, age, race, income, residency) should influence attitudes towards BWCs because these demographic factors are associated with public satisfaction, confidence, cooperation, and contact with police in past research (Tuch and Weitzer, 1997; Tyler, 2005; Eith and Durose, 2011). Figure 1: View largeDownload slide Conceptual model of public support for BWCs. Figure 1: View largeDownload slide Conceptual model of public support for BWCs. Sample and key variables The survey for this study was administered online to a national sample of US residents over a 10-day period in May 2015.2 The final sample consisted of 599 respondents. Just over half of the sample was male (54%), and a majority were college-educated (87%), lived in a city having less than 1 million population (82%), were White (78%), were aged 30 years or more (63%), and earned under $50,000 per year (57%). These demographic characteristics served as independent variables for the analysis. The dependent variables for this study represent the level of general support for BWCs on officers and the level of agreement with BWCs’ potential impact on several outcomes. Participants were first asked to indicate whether they were opposed to or supported a requirement that police wear BWCs. Responses were coded into two categories: 0 = opposed/unsure; 1 = support. Participants were then presented with items that asked about the ability of BWCs to (a) increase transparency, (b) reduce use of excessive force, (c) improve police–citizen relations, (d) increase citizens’ trust, and (e) decrease racial tensions. Respondents were asked to indicate their level of agreement with each of these items using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Responses to these questions were also coded into two categories: 0 = strongly disagree/disagree/unsure; 1 = agree/strongly agree.3 Analysis We performed a series of univariate, bivariate, and multivariate analyses to assess the influence of individuals’ demographic characteristics on their views about the perceived consequences of BWCs and public support for BWCs. Logistic regression analysis was conducted to assess the net effects of these variables on the outcome measures. The results of these analyses are summarized below. Table 1 displays the coding schemes for predictor and outcome variables as well as their univariate distributions. As the univariate analyses indicate, the sample as a whole was very supportive of policies that require police to wear BWCs (approximately 85%). Similarly, high percentages agreed that BWCs will help to increase transparency of police work (91%) and reduce excessive use of force by officers (80%). Smaller percentages (although still the majority of respondents) indicated that BWCs will help to improve police–citizen relationships (66%) and increase citizens’ trust of police (61%). The sample was also less optimistic that BWCs will help to decrease tensions between police and racial minorities (36% in agreement). Table 1: Coding of variables and univariate distributions Variable  Coding  % (n)  Independent variables      Gender (male)  0 = Female  45.7 (274)    1 = Male  54.3 (325)  Age (<30 years)  0 = 30 or older  63.1 (378)    1 = Under 30 years old  36.9 (221)  Race/ethnicity1 (reference category)  0 = White  78.5 (470)  Race/ethnicity2 (Black)  1 = Black  6.7 (40)  Race/ethnicity3 (Hispanic)  1 = Hispanic  5.7 (34)  Race/ethnicity4 (Other)  1 = Other race/ethnicity  9.2 (55)  Education (college graduate)  0 = High school graduate or less  12.9 (77)    1 = Some college/college graduate  87.1 (522)  City resident >1 million  0 = City/town < 1 million population  82.1 (492)    1 = Large city > 1 million population  17.9 (107)  Income >$50,000  0 = < $50k Annual income  56.9 (341)    1 = > $50k Annual income  43.1 (258)  Dependent variables      Support requiring BWC by police  0 = Oppose/unsure  15.2 (91)    1 = Support  84.8 (508)  Agree BWC increases transparency  0 = Disagree/unsure  8.7 (52)    1 = Agree  91.3 (547)  Agree BWC reduces use of excessive force  0 = Disagree/unsure  19.9 (119)    1 = Agree  80.1 (480)  Agree BWC improves police–citizen relations  0 = Disagree/unsure  33.7 (202)    1 = Agree  66.3 (397)  Agree BWC increase citizen’s trust  0 = Disagree/unsure  38.9 (233)    1 = Agree  61.1 (366)  Agree BWC decreases racial tension  0 = Disagree/unsure  63.8 (382)    1 = Agree  36.2 (217)  Variable  Coding  % (n)  Independent variables      Gender (male)  0 = Female  45.7 (274)    1 = Male  54.3 (325)  Age (<30 years)  0 = 30 or older  63.1 (378)    1 = Under 30 years old  36.9 (221)  Race/ethnicity1 (reference category)  0 = White  78.5 (470)  Race/ethnicity2 (Black)  1 = Black  6.7 (40)  Race/ethnicity3 (Hispanic)  1 = Hispanic  5.7 (34)  Race/ethnicity4 (Other)  1 = Other race/ethnicity  9.2 (55)  Education (college graduate)  0 = High school graduate or less  12.9 (77)    1 = Some college/college graduate  87.1 (522)  City resident >1 million  0 = City/town < 1 million population  82.1 (492)    1 = Large city > 1 million population  17.9 (107)  Income >$50,000  0 = < $50k Annual income  56.9 (341)    1 = > $50k Annual income  43.1 (258)  Dependent variables      Support requiring BWC by police  0 = Oppose/unsure  15.2 (91)    1 = Support  84.8 (508)  Agree BWC increases transparency  0 = Disagree/unsure  8.7 (52)    1 = Agree  91.3 (547)  Agree BWC reduces use of excessive force  0 = Disagree/unsure  19.9 (119)    1 = Agree  80.1 (480)  Agree BWC improves police–citizen relations  0 = Disagree/unsure  33.7 (202)    1 = Agree  66.3 (397)  Agree BWC increase citizen’s trust  0 = Disagree/unsure  38.9 (233)    1 = Agree  61.1 (366)  Agree BWC decreases racial tension  0 = Disagree/unsure  63.8 (382)    1 = Agree  36.2 (217)  The bivariate relations between respondents’ demographic attributes, views about the benefits of BWCs, and public support for body cameras are displayed in Table 2. These results indicate that attitudes in support of BWCs and beliefs about their benefits are largely unrelated to individuals’ demographic characteristics. The primary exception is that Black respondents and individuals under 30 years of age were significantly (P < 0.05) less likely than their counterparts to believe that BWCs will increase transparency. However, for each presumed benefit of BWC, there was a strong and significant positive bivariate relationship between these beliefs and public support for BWCs. Table 2: Bivariate relations between demographic factors, perceived benefits of BWCs, and public support for BWCs Group differences  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support BWC requirement    Percent  Percent  Percent  Percent  Percent  Percent  Male  93  80  68  61  35  85  Female  90  80  66  61  38  85  <30 years  88*  83  72  65  45*  85  30–49 years  92  78  62  57  33  85  50 years and older  98  82  66  65  27  87  Black  76*  76  51  45  33  90  Hispanic  88  76  59  62  35  91  White  93  80  68  63  37  84  Other race  88  88  71  59  36  90  College graduate  92  81  67  62  37  85  Non-college  90  75  66  53  34  86  Urban  90  84  65  67  36  86  Rural  92  79  67  60  37  85  Income < $50,000  92  82  66  59  38  83  Income > $50,000  90  79  67  65  35  88  Average percent  91  80  66  61  36  85  Transparency (agree)            87*  Transparency (disagree)            63  Reduce excessive force (agree)            89*  Reduce excessive force (disagree)            70  Increase police–citizen relations (agree)            91*  Increase police–citizen relations (disagree)            72  Increase trust (agree)            92*  Increase trust (disagree)            74  Reduce race tensions (agree)            93*  Reduce race tensions (disagree)            80  Group differences  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support BWC requirement    Percent  Percent  Percent  Percent  Percent  Percent  Male  93  80  68  61  35  85  Female  90  80  66  61  38  85  <30 years  88*  83  72  65  45*  85  30–49 years  92  78  62  57  33  85  50 years and older  98  82  66  65  27  87  Black  76*  76  51  45  33  90  Hispanic  88  76  59  62  35  91  White  93  80  68  63  37  84  Other race  88  88  71  59  36  90  College graduate  92  81  67  62  37  85  Non-college  90  75  66  53  34  86  Urban  90  84  65  67  36  86  Rural  92  79  67  60  37  85  Income < $50,000  92  82  66  59  38  83  Income > $50,000  90  79  67  65  35  88  Average percent  91  80  66  61  36  85  Transparency (agree)            87*  Transparency (disagree)            63  Reduce excessive force (agree)            89*  Reduce excessive force (disagree)            70  Increase police–citizen relations (agree)            91*  Increase police–citizen relations (disagree)            72  Increase trust (agree)            92*  Increase trust (disagree)            74  Reduce race tensions (agree)            93*  Reduce race tensions (disagree)            80  * P < 0.05. To further examine these issues, we consider the relative influence of demographic characteristics on one’s beliefs about the perceived consequences of BWCs and support for them. Table 3 summarizes the results of logistic regression analyses that assess the net impact of particular demographic characteristics on these public attitudes about BWCs and their perceived benefits. Table 3: Logistic regression analysis of predictors of perceived consequences of BWCs and public BWC support Demographic predictor variable  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support requiring BWC by police    Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Increase transparency  —  —  —  —  —  2.51*  Decrease excessive force  —  —  —  —  —  1.62  Improve police–citizen relations  —  —  —  —  —  2.21*  Increase citizen trust  —  —  —  —  —  2.12*  Decrease racial tension  —  —  —  —  —  1.78  Male  0.65  1.01  0.87  0.94  1.14  1.02  <30 years  0.56  1.28  1.59*  1.43*  1.89*  0.74  Black  0.19*  0.66  0.45*  0.43*  0.69  3.67*  Hispanic  0.59  0.75  0.63  0.91  0.83  2.78  Other race  0.54  1.62  0.93  0.69  0.77  2.05  College graduate  1.41  1.43  1.02  1.40  1.20  0.70  City resident >1 million  1.00  1.42  0.97  1.39  0.98  1.02  Income > $50,000  0.76  0.79  1.02  1.26  0.87  1.60  N  599  599  599  599  599  599  Nagelkerke R2  0.08  0.02  0.03  0.03  0.04  0.20  Demographic predictor variable  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support requiring BWC by police    Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Increase transparency  —  —  —  —  —  2.51*  Decrease excessive force  —  —  —  —  —  1.62  Improve police–citizen relations  —  —  —  —  —  2.21*  Increase citizen trust  —  —  —  —  —  2.12*  Decrease racial tension  —  —  —  —  —  1.78  Male  0.65  1.01  0.87  0.94  1.14  1.02  <30 years  0.56  1.28  1.59*  1.43*  1.89*  0.74  Black  0.19*  0.66  0.45*  0.43*  0.69  3.67*  Hispanic  0.59  0.75  0.63  0.91  0.83  2.78  Other race  0.54  1.62  0.93  0.69  0.77  2.05  College graduate  1.41  1.43  1.02  1.40  1.20  0.70  City resident >1 million  1.00  1.42  0.97  1.39  0.98  1.02  Income > $50,000  0.76  0.79  1.02  1.26  0.87  1.60  N  599  599  599  599  599  599  Nagelkerke R2  0.08  0.02  0.03  0.03  0.04  0.20  * P < 0.05. As shown in Table 3, no significant differences were found in public support for BWCs and their attitudes about their consequences by the respondent’s gender, level of education, income, or the location of their residency. There were some differences in age, however, with younger respondents demonstrating more confidence in BWCs’ ability to improve police–citizen relations, increase trust in police, and decrease racial tensions. There were also some differences by respondents’ race, with those identifying as Black indicating less optimism in terms of BWCs’ ability to increase transparency, improve relationships between police and citizens, or increase trust in police. Among the perceived benefits of BWCs, beliefs about this technology increasing transparency, improving citizen–police relations, and increasing public trust had a significant net effect on increasing public support for officers’ use of BWCs. In contrast, public attitudes about the capacity of BWCs to decrease excessive force by police and reduce racial tension did not have a significant net effect on public support for the technology. Based on these results, it appears that citizen’s general demographic characteristics have little direct or indirect effect on support for BWCs. Instead, public support for police use of BWCs is more directly tied to their beliefs about the perceived benefits of this technology in terms of improving transparency, police–citizen relations, and citizen’s trust. As an indication of the lack of major indirect effects, the nature and magnitude of the impact of citizens’ demographic characteristics did not change substantially once controls were introduced for the various measures of public attitudes about the consequences of BWCs. The minimal indirect effects in this analysis are also indicated in Table 3 by a general absence of significant effects of demographic characteristics (with the exception of race and age) on public views about the possible consequences of BWCs. Discussion The results above confirm, first and foremost, that the public is generally very supportive of BWCs on police. Secondly, with some minor differences by race, people are mostly positive in terms of their belief in the ability of BWCs to improve policing in numerous ways. Thirdly, public beliefs in the ability of BWCs to improve transparency, trust in police, and police–citizen relationships are the best predictors of overall support for BWCs—socio-demographic differences have little net impact on overall support. Importantly, however, people seem to have varying degrees of confidence in the various BWC advertised positive consequences. While people believe strongly in the ability of BWCs to increase transparency of police work and reduce excessive use of force by police, there is less agreement that BWCs can improve trust in police or improve police–community relationships. Furthermore, the majority of survey respondents are pessimistic on the question of whether BWCs can help to reduce racial tensions between police and minority communities. It would appear, therefore, that the public clearly distinguishes between the intended outcomes of BWCs. For example, the overwhelming majority of respondents believed that BWCs would increase the transparency of police work and a sizeable majority indicated that BWCs would reduce excessive force. It may be that people interpret these outcomes—transparency and excessive force—as generally concrete concepts with relatively direct links to BWCs. If BWC video can be accessed by the courts, the media, or the general public, the police agency is directly demonstrating its transparency. Similarly, from the public’s perspective, a BWC is likely to have an immediate impact on officer’s behaviour, thereby tempering his or her use of force. Complaints of excessive force are also quantifiable (presumably), and can, therefore, be clearly monitored as a direct outcome of the implementation of BWCs. The public was less convinced in the ability of BWCs to increase trust in police or improve police–citizen relationships—and most were not convinced that BWCs could decrease racial tensions between police and members of minority communities. This may be because these notions—trust, police–citizen relationships, tensions between police and citizens—are likely less tangible to most citizens. Community trust in police is a somewhat abstract concept that cannot be easily quantified. Positive police–citizen relationships are built over extended periods of time and often require enormous investment on the part of both police agencies and communities. Similarly, racial tension between police and citizens in a given community often has long history that cannot be easily addressed or resolved. Unlike BWCs’ potential consequences of increased transparency or reduced excessive force that may be perceived to have direct ties to BWCs, people may consider ‘trust’ and concepts like it to be dependent on many factors that are not directly related to the technology. Additionally, the difference between the perceived consequences of BWCs may also be an indication that, to the public, these concepts can operate in opposite directions. Consider the difference between transparency and trust, for example. If a police agency releases BWC video involving a controversial police shooting of a minority citizen, most would agree that the agency is demonstrating transparency. If, however, that video clearly shows an officer’s actions as inappropriate, unjustified, or unlawful, it is unlikely that the community’s trust in police will greatly improve. Indeed, trust may decrease, police–citizen relations may worsen, and tensions between police and minority communities could increase. It is also difficult to know how an individual citizen will perceive being approached by an officer with a BWC. It is entirely possible that people could interpret a BWC on an officer as a signal that the officer does not trust the citizen (hence the need for the recording), thereby placing the citizen on the defensive. Again, the recording of the interaction demonstrates transparency, but it is difficult to argue that the BWC will necessarily improve the trust that the citizen has for the police agency. Conclusion We acknowledge the limitations of the study. As with all survey data that rely on national samples, concerns arise regarding the sample’s representativeness of the US population. This is particularly an issue when using online surveys since participants are restricted to those who have internet access. Although other studies suggest similar findings regarding the public’s overall support for BWCs (see e.g. YouGov, 2015), the results presented here should be interpreted with some caution due to the potential limits of the sample. The survey data used in this study are also cross-sectional in nature; they were collected at a time (May 2015) when BWCs were much less ubiquitous than they are at present. It is possible that public opinion of BWCs has changed in the (however brief) period of time between the survey and the writing of this article. Despite the potential limitations, these data do offer some insight into citizen opinion of the potential positive consequences of BWCs. It is most apparent that citizens are supportive of BWCs in policing. Furthermore, of the advertised positive outcomes of BWCs discussed in this article, the public appears most enthusiastic about the potential for BWCs to improve the transparency of police work, while there is less agreement in terms of whether BWCs can impact trust in policing or improve police–citizen relationships. If it is the case that policing will become more transparent as a result of BWCs, it is necessary to carefully consider the effects of this transparency. Elsewhere there are suggestions that, despite support for BWCs, citizens are leery about allowing media or the general public access to recordings of interactions between police and private citizens (Sousa et al., 2015). This may point to an interesting conflict in public opinion of BWCs: people see the potential value of BWCs in terms of making policing transparent, but they are concerned about allowing the media (a primary mechanism of police transparency) access to videos. It may be that the public has not yet come to fully realize that the potential benefits of BWCs also come with a cost. The transparency of BWCs might make police more accountable, but that same transparency can expose private citizens to public scrutiny as well. BWCs are often marketed as technology with many positive consequences. While citizens are generally optimistic, they however appear to be at least somewhat sceptical of some of these potential outcomes. Future research should, therefore, continue to explore the actual impact of BWCs on concepts such as police transparency, trust in police, and police–citizen relationships. Footnotes 1 See Lum et al. (2015) for a recent review of empirical studies on BWCs. See also Drover and Ariel (2015) and Sousa et al. (2016) for recent methodological discussions. 2 The sample was generated using a sampling platform created by Amazon’s Mechanical Turk. Those who agreed to complete the survey were directed to Qualtrics and offered a nominal payment (0.50 USD) for their participation. Although several demographic characteristics were over-represented in this sample compared to US population estimates (i.e. males, college educated), the overall level of support for BWCs found in this sample was comparable to the results from other US studies using online samples (see Pew Research Center, 2014; YouGov, 2015). In addition, previous research has demonstrated that samples generated by Mechanical Turk better represent known population estimates than other online sampling methods (Heen et al., 2014). To evaluate whether the under-representation of particular groups in the online sample affected the observed results, the regression analyses in this article were conducted with and without post-stratification weighting based on national estimates of gender, age, and racial/ethnic distribution in 2015. No substantive differences in the observed results were found across these weighted and unweighted analyses. Thus, the unweighted results are presented without loss of generalizability. The results of the weighted analyses are available upon request. 3 Our decision to recode variables into dichotomous categories reflects our primary purpose to highlight the basic differences between those who support / agree with BWC usage and those who do not. This decision to recode ordinal measures into binary categories, however, had little impact on the substantive conclusions derived from this study. In particular, regardless of their coding as binary or ordinal variables, the same variables were found to be significantly or insignificantly related to public attitudes about the impact of BWCs, and the nature and statistical significance of the impact of these variables, in turn, was similar across coding methods in their observed effects on public support for the police use of BWCs. The results of analyses using ordinal-level measures are available upon request. References Ariel B., Farrar W., Sutherland A. ( 2015). ‘ The Effect of Police Body-Worn Cameras on Use of Force and Citizens’ Complaints against the Police: A Randomized Controlled Trial’. Journal of Quantitative Criminology  31( 3): 509– 535. Google Scholar CrossRef Search ADS   Ariel B., Sutherland A., Henstock D. et al.   ( 2017). ‘ Contagious Accountability: A Global Multisite Randomized Controlled Trial on the Effect of Police Body-Worn Cameras on Citizens’ Complaints Against the Police’. Criminal Justice and Behavior  44( 2): 293– 316. Google Scholar CrossRef Search ADS   Drover P., Ariel B. ( 2015). ‘ Leading an Experiment in Police Body-Worn Video Cameras’. International Criminal Justice Review  25( 1): 80– 97. Google Scholar CrossRef Search ADS   Eith C., Durose M. R. ( 2011). Contact between police and the public, 2008. Bureau of Justice Statistics NCJ 234599. http://www.bjs.gov/index.cfm?ty=pbdetail&iid=2229/ (accessed 8 March 2017). Heen M., Lieberman J., Miethe T. ( 2014). ‘ A Comparison of Different Online Sampling Approaches for Generating National Samples’ . University of Nevada Las Vegas: Center for Crime and Justice Policy. Jennings W., Fridell L., Lynch M. ( 2014). ‘ Cops and Cameras: Officer Perceptions of the Use of Body-Worn Cameras in Law Enforcement’. Journal of Criminal Justice  42: 549– 556. Google Scholar CrossRef Search ADS   Jennings W., Lynch M., Fridell L. ( 2015). ‘ Evaluating the Impact of Police Officer Body-Worn Cameras (BWCs) on Response-to-Resistance and Serious External Complaints: Evidence from the Orlando Police Department (OPD) Experience Utilizing a Randomized Controlled Experiment’. Journal of Criminal Justice  43: 480– 486. Google Scholar CrossRef Search ADS   Katz C., Kurtenbach M., Choate D., White M. ( 2015). Phoenix, Arizona, Smart Policing Initiative: Evaluating the Impact of Police Officer Body-Worn Cameras . Washington, DC: Bureau of Justice Assistance, US Department of Justice. Lum C., Koper C., Merola L., Scherer A., Reioux A. ( 2015). Existing and ongoing body worn camera research: knowledge gaps and opportunities. Report for the Laura and John Arnold Foundation. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University. Lynch M. ( 2016). Police Technology. In W. Jennings (ed.), The Encyclopedia of Crime and Punishment . Hoboken, NJ: Wiley-Blackwell, pp. 1– 5. Miller L., Toliver J., and Police Executive Research Forum ( 2014). Implementing a Body-Worn Camera Program: Recommendations and Lessons Learned . Washington, DC: Office of Community Oriented Policing Services. Pew Research Center ( 2014). Sharp Racial Divisions in Reactions to Brown, Garner Decisions. A Pew Research Center/USA TODAY Survey. http://www.people-press.org/2014/12/08/sharp-racial-divisions-in-reactions-to-brown-garner-decisions/ (accessed 8 March 2017). President’s Task Force on 21st Century Policing ( 2015). Final report of the President’s Task Force on 21st Century Policing . Washington, DC: Office of Community Oriented Policing Services. Ready J., Young J. ( 2014). Three myths about police body cams. Slate. http://www.slate.com/articles/technology/future_tense/2014/09/ferguson_body_cams_myths_about_police_body_worn_recorders.html/ (accessed 8 March 2017). Ready J., Young J. ( 2015). ‘ The Impact of On-Officer Video Cameras on Police-Citizen Contacts: Findings from a Controlled Experiment in Mesa, AZ’. Journal of Experimental Criminology  11: 445– 458. Google Scholar CrossRef Search ADS   Sousa W., Coldren J., Rodriguez D., Braga A. ( 2016). ‘ Research on Body Worn Cameras: Meeting the Challenges of Police Operations, Program Implementation, and Randomized Controlled Trial Designs’. Police Quarterly  19( 3): 363– 384. Google Scholar CrossRef Search ADS   Sousa W., Miethe T., Sakiyama M. ( 2015). ‘ Body Worn Cameras on Police: Results from a National Survey of Public Attitudes’ . University of Nevada Las Vegas: Center for Crime and Justice Policy. Tuch S., Weitzer R. ( 1997). ‘ Racial Differences in Attitudes toward the Police’. The Public Opinion Quarterly  61: 642– 663. Google Scholar CrossRef Search ADS   Tyler T. ( 2005). ‘ Policing in Black and White: Ethnic Group Differences in Trust and Confidence in the Police’. Police Quarterly  8: 322– 342. Google Scholar CrossRef Search ADS   White House, Office of the Press Secretary ( 2014). Fact Sheet: strengthening community policing. https://www.whitehouse.gov/the-press-office/2014/12/01/fact-sheet-strengthening-community-policing/ (accessed 8 March 2017). White M. ( 2014). Police Officer Body-Worn Cameras: Assessing the Evidence . Washington, DC: Office of Community Oriented Policing Services. YouGov ( 2015). Overwhelming support for police body cameras. YouGov.com. https://today.yougov.com/news/2015/05/07/body-cams/ (accessed 8 March 2017). © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions please e-mail: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Policing: A Journal of Policy and Practice Oxford University Press

Inconsistencies in Public Opinion of Body-Worn Cameras on Police: Transparency, Trust, and Improved Police–Citizen Relationships

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Abstract

Abstract Given the national interest in equipping police with body-worn cameras (BWCs), it is important to consider public attitudes concerning the technology. This article draws on the results of a national survey of citizen opinions of BWCs. The survey includes items related to general support for BWCs, opinions on their potential advantages, and attitudes towards their potential consequences. Results indicate that while there is general support for BWCs on police, opinions vary on the capacity of BWCs to increase transparency of police work, improve trust in police, and better police–citizen relationships. Introduction Advances in modern policing have often been associated with technological innovations (see Lynch (2016) for a review). Within this wider context of technology and policing, police departments across the USA have demonstrated an interest in body-worn cameras (BWCs) on officers for the better part of the last decade. This interest has greatly accelerated in recent years, however, as a result of several high-profile cases involving controversial interactions between police and citizens. These cases helped to generate a growing demand for increased accountability concerning police actions, especially officer use of force and deadly force in particular. In this regard, BWCs are often considered to be a tool that can help improve police–community relationships and enhance police legitimacy. The growing affordability of BWCs, the increasing experience with their use among different agencies, and the mounting incentives for departments to adopt BWCs, have also likely contributed to the swelling popularity of the technology. The federal government has also taken an interest in the role of BWCs for police departments, making it clear that local agencies should seriously consider adopting the technology. In late 2014, the White House proposed $75 million over 3 years to help purchase BWCs for local agencies as part of the President’s Community Policing Initiative (White House, 2014). Furthermore, although it recommended caution when adopting new tools, the President’s Task Force on 21st-century policing (created in response to the demand for greater police accountability) indicates that the use of technology in general—and BWCs specifically—can help to enhance transparency and build community trust (President’s Task Force, 2015). Although BWCs have become highly touted for their perceived benefits, evidence of BWC effectiveness remains limited, and research on the matter is still in its infancy. In particular, relatively little is known concerning public attitudes towards the technology. In this article, we examine public opinion of BWCs on police. We begin with a brief background on BWC research before turning to an analysis of survey data designed to determine public opinion of BWCs on officers. We focus on public expectations of the technology’s ability to achieve positive outcomes, including improved transparency, reduced excessive force, increased trust in policing, and better relations between police and citizens. Background Much of the published research on BWCs to date is descriptive in nature, describing their advantages to policing. White (2014), for example, discusses potential benefits and possible concerns with the technology. Potential benefits include the possibility of greater transparency of police activities since video recordings may be subject to public review, protection of citizens from police misconduct and/or unnecessary use of force, and protection of officers from false allegations of misconduct. BWCs can also help to improve police practice in other ways, such as gathering visual evidence and recording interviews with witnesses or victims. In addition, video from BWCs can be used for police training purposes. Among these potential benefits are several concerns involving BWCs (White, 2014). The financial and logistical resources needed to manage the technology, for example, can be a challenge for some agencies. Another major concern relates to the issue of privacy, particularly if video of an encounter between an officer and a private citizen is potentially available to the media or to the public through a public records request. In addition, BWCs could negatively influence the way that citizens communicate with officers, making them reluctant to reveal certain information knowing that their statements are recorded (Miller et al., 2014). There are many limits to the technology as well—a video record of an incident, for example, can still be open to interpretation in terms of the appropriateness of an officer’s actions (Ready and Young, 2014). Although currently limited, a growing body of research on BWCs has employed various empirical methods to examine the impact of the technology on officer behaviours or officer perceptions of BWCs.1 Many of these studies demonstrate the benefits of BWCs in terms of reducing police use of force and/or complaints of officer misconduct (Ariel et al., 2015, 2017; Jennings et al., 2015; Katz et al., 2015). Research also suggests that officers with BWCs may be more proactive in terms of initiating encounters with citizens, but do not become overly intrusive or invasive in their tactics (Ready and Young, 2015). Additional studies indicate that police themselves are generally supportive of BWCs on officers (Jennings et al., 2014), especially as they become more acquainted with the use of the technology (Katz et al., 2015). Current study Given the political and financial investments in BWCs, it is important to examine public perceptions of the technology. Some survey research has demonstrated strong support for BWCs in general (Pew Research Center, 2014; Sousa et al., 2015; YouGov, 2015). However, less is known about the public’s faith in the prospective positive consequences of BWCs. In other words, few have examined the public’s belief in the ability of BWCs to actually fulfil the promises of improved transparency, increased trust, and better relations between police and citizens. To explore these issues, we rely on survey research first reported by Sousa et al. (2015). The survey was designed to determine people’s opinions of BWCs on police. Importantly, specific items asked respondents to indicate their confidence in the ability of BWCs to impact transparency, trust, use of force, relationships between police and citizens, and tensions between police and minority communities. We are, therefore, able to examine these variables while also considering the influence of respondents’ demographic characteristics. The conceptual model underlying this study involves both direct and indirect effects. As illustrated in Fig. 1, various demographic factors are expected to influence support for police use of BWCs both directly and indirectly through the impact of the perceived consequences of this technology. Individuals’ socio-economic characteristics (e.g. gender, age, race, income, residency) should influence attitudes towards BWCs because these demographic factors are associated with public satisfaction, confidence, cooperation, and contact with police in past research (Tuch and Weitzer, 1997; Tyler, 2005; Eith and Durose, 2011). Figure 1: View largeDownload slide Conceptual model of public support for BWCs. Figure 1: View largeDownload slide Conceptual model of public support for BWCs. Sample and key variables The survey for this study was administered online to a national sample of US residents over a 10-day period in May 2015.2 The final sample consisted of 599 respondents. Just over half of the sample was male (54%), and a majority were college-educated (87%), lived in a city having less than 1 million population (82%), were White (78%), were aged 30 years or more (63%), and earned under $50,000 per year (57%). These demographic characteristics served as independent variables for the analysis. The dependent variables for this study represent the level of general support for BWCs on officers and the level of agreement with BWCs’ potential impact on several outcomes. Participants were first asked to indicate whether they were opposed to or supported a requirement that police wear BWCs. Responses were coded into two categories: 0 = opposed/unsure; 1 = support. Participants were then presented with items that asked about the ability of BWCs to (a) increase transparency, (b) reduce use of excessive force, (c) improve police–citizen relations, (d) increase citizens’ trust, and (e) decrease racial tensions. Respondents were asked to indicate their level of agreement with each of these items using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Responses to these questions were also coded into two categories: 0 = strongly disagree/disagree/unsure; 1 = agree/strongly agree.3 Analysis We performed a series of univariate, bivariate, and multivariate analyses to assess the influence of individuals’ demographic characteristics on their views about the perceived consequences of BWCs and public support for BWCs. Logistic regression analysis was conducted to assess the net effects of these variables on the outcome measures. The results of these analyses are summarized below. Table 1 displays the coding schemes for predictor and outcome variables as well as their univariate distributions. As the univariate analyses indicate, the sample as a whole was very supportive of policies that require police to wear BWCs (approximately 85%). Similarly, high percentages agreed that BWCs will help to increase transparency of police work (91%) and reduce excessive use of force by officers (80%). Smaller percentages (although still the majority of respondents) indicated that BWCs will help to improve police–citizen relationships (66%) and increase citizens’ trust of police (61%). The sample was also less optimistic that BWCs will help to decrease tensions between police and racial minorities (36% in agreement). Table 1: Coding of variables and univariate distributions Variable  Coding  % (n)  Independent variables      Gender (male)  0 = Female  45.7 (274)    1 = Male  54.3 (325)  Age (<30 years)  0 = 30 or older  63.1 (378)    1 = Under 30 years old  36.9 (221)  Race/ethnicity1 (reference category)  0 = White  78.5 (470)  Race/ethnicity2 (Black)  1 = Black  6.7 (40)  Race/ethnicity3 (Hispanic)  1 = Hispanic  5.7 (34)  Race/ethnicity4 (Other)  1 = Other race/ethnicity  9.2 (55)  Education (college graduate)  0 = High school graduate or less  12.9 (77)    1 = Some college/college graduate  87.1 (522)  City resident >1 million  0 = City/town < 1 million population  82.1 (492)    1 = Large city > 1 million population  17.9 (107)  Income >$50,000  0 = < $50k Annual income  56.9 (341)    1 = > $50k Annual income  43.1 (258)  Dependent variables      Support requiring BWC by police  0 = Oppose/unsure  15.2 (91)    1 = Support  84.8 (508)  Agree BWC increases transparency  0 = Disagree/unsure  8.7 (52)    1 = Agree  91.3 (547)  Agree BWC reduces use of excessive force  0 = Disagree/unsure  19.9 (119)    1 = Agree  80.1 (480)  Agree BWC improves police–citizen relations  0 = Disagree/unsure  33.7 (202)    1 = Agree  66.3 (397)  Agree BWC increase citizen’s trust  0 = Disagree/unsure  38.9 (233)    1 = Agree  61.1 (366)  Agree BWC decreases racial tension  0 = Disagree/unsure  63.8 (382)    1 = Agree  36.2 (217)  Variable  Coding  % (n)  Independent variables      Gender (male)  0 = Female  45.7 (274)    1 = Male  54.3 (325)  Age (<30 years)  0 = 30 or older  63.1 (378)    1 = Under 30 years old  36.9 (221)  Race/ethnicity1 (reference category)  0 = White  78.5 (470)  Race/ethnicity2 (Black)  1 = Black  6.7 (40)  Race/ethnicity3 (Hispanic)  1 = Hispanic  5.7 (34)  Race/ethnicity4 (Other)  1 = Other race/ethnicity  9.2 (55)  Education (college graduate)  0 = High school graduate or less  12.9 (77)    1 = Some college/college graduate  87.1 (522)  City resident >1 million  0 = City/town < 1 million population  82.1 (492)    1 = Large city > 1 million population  17.9 (107)  Income >$50,000  0 = < $50k Annual income  56.9 (341)    1 = > $50k Annual income  43.1 (258)  Dependent variables      Support requiring BWC by police  0 = Oppose/unsure  15.2 (91)    1 = Support  84.8 (508)  Agree BWC increases transparency  0 = Disagree/unsure  8.7 (52)    1 = Agree  91.3 (547)  Agree BWC reduces use of excessive force  0 = Disagree/unsure  19.9 (119)    1 = Agree  80.1 (480)  Agree BWC improves police–citizen relations  0 = Disagree/unsure  33.7 (202)    1 = Agree  66.3 (397)  Agree BWC increase citizen’s trust  0 = Disagree/unsure  38.9 (233)    1 = Agree  61.1 (366)  Agree BWC decreases racial tension  0 = Disagree/unsure  63.8 (382)    1 = Agree  36.2 (217)  The bivariate relations between respondents’ demographic attributes, views about the benefits of BWCs, and public support for body cameras are displayed in Table 2. These results indicate that attitudes in support of BWCs and beliefs about their benefits are largely unrelated to individuals’ demographic characteristics. The primary exception is that Black respondents and individuals under 30 years of age were significantly (P < 0.05) less likely than their counterparts to believe that BWCs will increase transparency. However, for each presumed benefit of BWC, there was a strong and significant positive bivariate relationship between these beliefs and public support for BWCs. Table 2: Bivariate relations between demographic factors, perceived benefits of BWCs, and public support for BWCs Group differences  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support BWC requirement    Percent  Percent  Percent  Percent  Percent  Percent  Male  93  80  68  61  35  85  Female  90  80  66  61  38  85  <30 years  88*  83  72  65  45*  85  30–49 years  92  78  62  57  33  85  50 years and older  98  82  66  65  27  87  Black  76*  76  51  45  33  90  Hispanic  88  76  59  62  35  91  White  93  80  68  63  37  84  Other race  88  88  71  59  36  90  College graduate  92  81  67  62  37  85  Non-college  90  75  66  53  34  86  Urban  90  84  65  67  36  86  Rural  92  79  67  60  37  85  Income < $50,000  92  82  66  59  38  83  Income > $50,000  90  79  67  65  35  88  Average percent  91  80  66  61  36  85  Transparency (agree)            87*  Transparency (disagree)            63  Reduce excessive force (agree)            89*  Reduce excessive force (disagree)            70  Increase police–citizen relations (agree)            91*  Increase police–citizen relations (disagree)            72  Increase trust (agree)            92*  Increase trust (disagree)            74  Reduce race tensions (agree)            93*  Reduce race tensions (disagree)            80  Group differences  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support BWC requirement    Percent  Percent  Percent  Percent  Percent  Percent  Male  93  80  68  61  35  85  Female  90  80  66  61  38  85  <30 years  88*  83  72  65  45*  85  30–49 years  92  78  62  57  33  85  50 years and older  98  82  66  65  27  87  Black  76*  76  51  45  33  90  Hispanic  88  76  59  62  35  91  White  93  80  68  63  37  84  Other race  88  88  71  59  36  90  College graduate  92  81  67  62  37  85  Non-college  90  75  66  53  34  86  Urban  90  84  65  67  36  86  Rural  92  79  67  60  37  85  Income < $50,000  92  82  66  59  38  83  Income > $50,000  90  79  67  65  35  88  Average percent  91  80  66  61  36  85  Transparency (agree)            87*  Transparency (disagree)            63  Reduce excessive force (agree)            89*  Reduce excessive force (disagree)            70  Increase police–citizen relations (agree)            91*  Increase police–citizen relations (disagree)            72  Increase trust (agree)            92*  Increase trust (disagree)            74  Reduce race tensions (agree)            93*  Reduce race tensions (disagree)            80  * P < 0.05. To further examine these issues, we consider the relative influence of demographic characteristics on one’s beliefs about the perceived consequences of BWCs and support for them. Table 3 summarizes the results of logistic regression analyses that assess the net impact of particular demographic characteristics on these public attitudes about BWCs and their perceived benefits. Table 3: Logistic regression analysis of predictors of perceived consequences of BWCs and public BWC support Demographic predictor variable  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support requiring BWC by police    Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Increase transparency  —  —  —  —  —  2.51*  Decrease excessive force  —  —  —  —  —  1.62  Improve police–citizen relations  —  —  —  —  —  2.21*  Increase citizen trust  —  —  —  —  —  2.12*  Decrease racial tension  —  —  —  —  —  1.78  Male  0.65  1.01  0.87  0.94  1.14  1.02  <30 years  0.56  1.28  1.59*  1.43*  1.89*  0.74  Black  0.19*  0.66  0.45*  0.43*  0.69  3.67*  Hispanic  0.59  0.75  0.63  0.91  0.83  2.78  Other race  0.54  1.62  0.93  0.69  0.77  2.05  College graduate  1.41  1.43  1.02  1.40  1.20  0.70  City resident >1 million  1.00  1.42  0.97  1.39  0.98  1.02  Income > $50,000  0.76  0.79  1.02  1.26  0.87  1.60  N  599  599  599  599  599  599  Nagelkerke R2  0.08  0.02  0.03  0.03  0.04  0.20  Demographic predictor variable  BWC increase transparency  BWC decrease excessive force  BWC improves police–citizen relations  BWC increase citizen’s trust  BWC decreases racial tension  Support requiring BWC by police    Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Odds ratio  Increase transparency  —  —  —  —  —  2.51*  Decrease excessive force  —  —  —  —  —  1.62  Improve police–citizen relations  —  —  —  —  —  2.21*  Increase citizen trust  —  —  —  —  —  2.12*  Decrease racial tension  —  —  —  —  —  1.78  Male  0.65  1.01  0.87  0.94  1.14  1.02  <30 years  0.56  1.28  1.59*  1.43*  1.89*  0.74  Black  0.19*  0.66  0.45*  0.43*  0.69  3.67*  Hispanic  0.59  0.75  0.63  0.91  0.83  2.78  Other race  0.54  1.62  0.93  0.69  0.77  2.05  College graduate  1.41  1.43  1.02  1.40  1.20  0.70  City resident >1 million  1.00  1.42  0.97  1.39  0.98  1.02  Income > $50,000  0.76  0.79  1.02  1.26  0.87  1.60  N  599  599  599  599  599  599  Nagelkerke R2  0.08  0.02  0.03  0.03  0.04  0.20  * P < 0.05. As shown in Table 3, no significant differences were found in public support for BWCs and their attitudes about their consequences by the respondent’s gender, level of education, income, or the location of their residency. There were some differences in age, however, with younger respondents demonstrating more confidence in BWCs’ ability to improve police–citizen relations, increase trust in police, and decrease racial tensions. There were also some differences by respondents’ race, with those identifying as Black indicating less optimism in terms of BWCs’ ability to increase transparency, improve relationships between police and citizens, or increase trust in police. Among the perceived benefits of BWCs, beliefs about this technology increasing transparency, improving citizen–police relations, and increasing public trust had a significant net effect on increasing public support for officers’ use of BWCs. In contrast, public attitudes about the capacity of BWCs to decrease excessive force by police and reduce racial tension did not have a significant net effect on public support for the technology. Based on these results, it appears that citizen’s general demographic characteristics have little direct or indirect effect on support for BWCs. Instead, public support for police use of BWCs is more directly tied to their beliefs about the perceived benefits of this technology in terms of improving transparency, police–citizen relations, and citizen’s trust. As an indication of the lack of major indirect effects, the nature and magnitude of the impact of citizens’ demographic characteristics did not change substantially once controls were introduced for the various measures of public attitudes about the consequences of BWCs. The minimal indirect effects in this analysis are also indicated in Table 3 by a general absence of significant effects of demographic characteristics (with the exception of race and age) on public views about the possible consequences of BWCs. Discussion The results above confirm, first and foremost, that the public is generally very supportive of BWCs on police. Secondly, with some minor differences by race, people are mostly positive in terms of their belief in the ability of BWCs to improve policing in numerous ways. Thirdly, public beliefs in the ability of BWCs to improve transparency, trust in police, and police–citizen relationships are the best predictors of overall support for BWCs—socio-demographic differences have little net impact on overall support. Importantly, however, people seem to have varying degrees of confidence in the various BWC advertised positive consequences. While people believe strongly in the ability of BWCs to increase transparency of police work and reduce excessive use of force by police, there is less agreement that BWCs can improve trust in police or improve police–community relationships. Furthermore, the majority of survey respondents are pessimistic on the question of whether BWCs can help to reduce racial tensions between police and minority communities. It would appear, therefore, that the public clearly distinguishes between the intended outcomes of BWCs. For example, the overwhelming majority of respondents believed that BWCs would increase the transparency of police work and a sizeable majority indicated that BWCs would reduce excessive force. It may be that people interpret these outcomes—transparency and excessive force—as generally concrete concepts with relatively direct links to BWCs. If BWC video can be accessed by the courts, the media, or the general public, the police agency is directly demonstrating its transparency. Similarly, from the public’s perspective, a BWC is likely to have an immediate impact on officer’s behaviour, thereby tempering his or her use of force. Complaints of excessive force are also quantifiable (presumably), and can, therefore, be clearly monitored as a direct outcome of the implementation of BWCs. The public was less convinced in the ability of BWCs to increase trust in police or improve police–citizen relationships—and most were not convinced that BWCs could decrease racial tensions between police and members of minority communities. This may be because these notions—trust, police–citizen relationships, tensions between police and citizens—are likely less tangible to most citizens. Community trust in police is a somewhat abstract concept that cannot be easily quantified. Positive police–citizen relationships are built over extended periods of time and often require enormous investment on the part of both police agencies and communities. Similarly, racial tension between police and citizens in a given community often has long history that cannot be easily addressed or resolved. Unlike BWCs’ potential consequences of increased transparency or reduced excessive force that may be perceived to have direct ties to BWCs, people may consider ‘trust’ and concepts like it to be dependent on many factors that are not directly related to the technology. Additionally, the difference between the perceived consequences of BWCs may also be an indication that, to the public, these concepts can operate in opposite directions. Consider the difference between transparency and trust, for example. If a police agency releases BWC video involving a controversial police shooting of a minority citizen, most would agree that the agency is demonstrating transparency. If, however, that video clearly shows an officer’s actions as inappropriate, unjustified, or unlawful, it is unlikely that the community’s trust in police will greatly improve. Indeed, trust may decrease, police–citizen relations may worsen, and tensions between police and minority communities could increase. It is also difficult to know how an individual citizen will perceive being approached by an officer with a BWC. It is entirely possible that people could interpret a BWC on an officer as a signal that the officer does not trust the citizen (hence the need for the recording), thereby placing the citizen on the defensive. Again, the recording of the interaction demonstrates transparency, but it is difficult to argue that the BWC will necessarily improve the trust that the citizen has for the police agency. Conclusion We acknowledge the limitations of the study. As with all survey data that rely on national samples, concerns arise regarding the sample’s representativeness of the US population. This is particularly an issue when using online surveys since participants are restricted to those who have internet access. Although other studies suggest similar findings regarding the public’s overall support for BWCs (see e.g. YouGov, 2015), the results presented here should be interpreted with some caution due to the potential limits of the sample. The survey data used in this study are also cross-sectional in nature; they were collected at a time (May 2015) when BWCs were much less ubiquitous than they are at present. It is possible that public opinion of BWCs has changed in the (however brief) period of time between the survey and the writing of this article. Despite the potential limitations, these data do offer some insight into citizen opinion of the potential positive consequences of BWCs. It is most apparent that citizens are supportive of BWCs in policing. Furthermore, of the advertised positive outcomes of BWCs discussed in this article, the public appears most enthusiastic about the potential for BWCs to improve the transparency of police work, while there is less agreement in terms of whether BWCs can impact trust in policing or improve police–citizen relationships. If it is the case that policing will become more transparent as a result of BWCs, it is necessary to carefully consider the effects of this transparency. Elsewhere there are suggestions that, despite support for BWCs, citizens are leery about allowing media or the general public access to recordings of interactions between police and private citizens (Sousa et al., 2015). This may point to an interesting conflict in public opinion of BWCs: people see the potential value of BWCs in terms of making policing transparent, but they are concerned about allowing the media (a primary mechanism of police transparency) access to videos. It may be that the public has not yet come to fully realize that the potential benefits of BWCs also come with a cost. The transparency of BWCs might make police more accountable, but that same transparency can expose private citizens to public scrutiny as well. BWCs are often marketed as technology with many positive consequences. While citizens are generally optimistic, they however appear to be at least somewhat sceptical of some of these potential outcomes. Future research should, therefore, continue to explore the actual impact of BWCs on concepts such as police transparency, trust in police, and police–citizen relationships. Footnotes 1 See Lum et al. (2015) for a recent review of empirical studies on BWCs. See also Drover and Ariel (2015) and Sousa et al. (2016) for recent methodological discussions. 2 The sample was generated using a sampling platform created by Amazon’s Mechanical Turk. Those who agreed to complete the survey were directed to Qualtrics and offered a nominal payment (0.50 USD) for their participation. Although several demographic characteristics were over-represented in this sample compared to US population estimates (i.e. males, college educated), the overall level of support for BWCs found in this sample was comparable to the results from other US studies using online samples (see Pew Research Center, 2014; YouGov, 2015). In addition, previous research has demonstrated that samples generated by Mechanical Turk better represent known population estimates than other online sampling methods (Heen et al., 2014). To evaluate whether the under-representation of particular groups in the online sample affected the observed results, the regression analyses in this article were conducted with and without post-stratification weighting based on national estimates of gender, age, and racial/ethnic distribution in 2015. No substantive differences in the observed results were found across these weighted and unweighted analyses. Thus, the unweighted results are presented without loss of generalizability. The results of the weighted analyses are available upon request. 3 Our decision to recode variables into dichotomous categories reflects our primary purpose to highlight the basic differences between those who support / agree with BWC usage and those who do not. This decision to recode ordinal measures into binary categories, however, had little impact on the substantive conclusions derived from this study. In particular, regardless of their coding as binary or ordinal variables, the same variables were found to be significantly or insignificantly related to public attitudes about the impact of BWCs, and the nature and statistical significance of the impact of these variables, in turn, was similar across coding methods in their observed effects on public support for the police use of BWCs. The results of analyses using ordinal-level measures are available upon request. References Ariel B., Farrar W., Sutherland A. ( 2015). ‘ The Effect of Police Body-Worn Cameras on Use of Force and Citizens’ Complaints against the Police: A Randomized Controlled Trial’. Journal of Quantitative Criminology  31( 3): 509– 535. Google Scholar CrossRef Search ADS   Ariel B., Sutherland A., Henstock D. et al.   ( 2017). ‘ Contagious Accountability: A Global Multisite Randomized Controlled Trial on the Effect of Police Body-Worn Cameras on Citizens’ Complaints Against the Police’. Criminal Justice and Behavior  44( 2): 293– 316. Google Scholar CrossRef Search ADS   Drover P., Ariel B. ( 2015). ‘ Leading an Experiment in Police Body-Worn Video Cameras’. International Criminal Justice Review  25( 1): 80– 97. Google Scholar CrossRef Search ADS   Eith C., Durose M. R. ( 2011). Contact between police and the public, 2008. Bureau of Justice Statistics NCJ 234599. http://www.bjs.gov/index.cfm?ty=pbdetail&iid=2229/ (accessed 8 March 2017). Heen M., Lieberman J., Miethe T. ( 2014). ‘ A Comparison of Different Online Sampling Approaches for Generating National Samples’ . University of Nevada Las Vegas: Center for Crime and Justice Policy. Jennings W., Fridell L., Lynch M. ( 2014). ‘ Cops and Cameras: Officer Perceptions of the Use of Body-Worn Cameras in Law Enforcement’. Journal of Criminal Justice  42: 549– 556. Google Scholar CrossRef Search ADS   Jennings W., Lynch M., Fridell L. ( 2015). ‘ Evaluating the Impact of Police Officer Body-Worn Cameras (BWCs) on Response-to-Resistance and Serious External Complaints: Evidence from the Orlando Police Department (OPD) Experience Utilizing a Randomized Controlled Experiment’. Journal of Criminal Justice  43: 480– 486. Google Scholar CrossRef Search ADS   Katz C., Kurtenbach M., Choate D., White M. ( 2015). Phoenix, Arizona, Smart Policing Initiative: Evaluating the Impact of Police Officer Body-Worn Cameras . Washington, DC: Bureau of Justice Assistance, US Department of Justice. Lum C., Koper C., Merola L., Scherer A., Reioux A. ( 2015). Existing and ongoing body worn camera research: knowledge gaps and opportunities. Report for the Laura and John Arnold Foundation. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University. Lynch M. ( 2016). Police Technology. In W. Jennings (ed.), The Encyclopedia of Crime and Punishment . Hoboken, NJ: Wiley-Blackwell, pp. 1– 5. Miller L., Toliver J., and Police Executive Research Forum ( 2014). Implementing a Body-Worn Camera Program: Recommendations and Lessons Learned . Washington, DC: Office of Community Oriented Policing Services. Pew Research Center ( 2014). Sharp Racial Divisions in Reactions to Brown, Garner Decisions. A Pew Research Center/USA TODAY Survey. http://www.people-press.org/2014/12/08/sharp-racial-divisions-in-reactions-to-brown-garner-decisions/ (accessed 8 March 2017). President’s Task Force on 21st Century Policing ( 2015). Final report of the President’s Task Force on 21st Century Policing . Washington, DC: Office of Community Oriented Policing Services. Ready J., Young J. ( 2014). Three myths about police body cams. Slate. http://www.slate.com/articles/technology/future_tense/2014/09/ferguson_body_cams_myths_about_police_body_worn_recorders.html/ (accessed 8 March 2017). Ready J., Young J. ( 2015). ‘ The Impact of On-Officer Video Cameras on Police-Citizen Contacts: Findings from a Controlled Experiment in Mesa, AZ’. Journal of Experimental Criminology  11: 445– 458. Google Scholar CrossRef Search ADS   Sousa W., Coldren J., Rodriguez D., Braga A. ( 2016). ‘ Research on Body Worn Cameras: Meeting the Challenges of Police Operations, Program Implementation, and Randomized Controlled Trial Designs’. Police Quarterly  19( 3): 363– 384. Google Scholar CrossRef Search ADS   Sousa W., Miethe T., Sakiyama M. ( 2015). ‘ Body Worn Cameras on Police: Results from a National Survey of Public Attitudes’ . University of Nevada Las Vegas: Center for Crime and Justice Policy. Tuch S., Weitzer R. ( 1997). ‘ Racial Differences in Attitudes toward the Police’. The Public Opinion Quarterly  61: 642– 663. Google Scholar CrossRef Search ADS   Tyler T. ( 2005). ‘ Policing in Black and White: Ethnic Group Differences in Trust and Confidence in the Police’. Police Quarterly  8: 322– 342. Google Scholar CrossRef Search ADS   White House, Office of the Press Secretary ( 2014). Fact Sheet: strengthening community policing. https://www.whitehouse.gov/the-press-office/2014/12/01/fact-sheet-strengthening-community-policing/ (accessed 8 March 2017). White M. ( 2014). Police Officer Body-Worn Cameras: Assessing the Evidence . Washington, DC: Office of Community Oriented Policing Services. YouGov ( 2015). Overwhelming support for police body cameras. YouGov.com. https://today.yougov.com/news/2015/05/07/body-cams/ (accessed 8 March 2017). © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions please e-mail: journals.permissions@oup.com

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Policing: A Journal of Policy and PracticeOxford University Press

Published: Mar 1, 2018

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