Abstract
Objectives
The study examined whether Assets Coming Together (ACT), a policing intervention directed at increasing collective action and collective efficacy at crime hot spots in Brooklyn Park, Minnesota, would have impacts on these outcomes, as well as police legitimacy, crime and fear of crime.
Methods
We used a block-randomized experimental design in which hot spots of crime were randomly allocated to treatment and control conditions. The treatment condition received the ACT program, and the control condition received normal police response. We analyzed crime data using an ANOVA approach, taking into account treatment and block. We analyzed survey data collected at each hot spot using mixed-effects linear regression models with robust standard errors to account for the nesting of responses within hot spots.
Results
We find that the intervention increased citizen reporting of collective actions (including collaboration in problem solving and contacts with the police) at hot spots, but it had little impact on general measures of collective efficacy or police legitimacy. Fear of crime increased at the treatment sites. We found that crime reporting was significantly inflated in the treatment sites. Crime outcomes were non-significant without accounting for this reporting inflation, but the treatment areas had a significant crime decrease when adjusting estimates based on reporting inflation.
Conclusions
Our experimental findings show that collective actions at hot spots can be encouraged through programs like ACT and that ordinary policing resources—patrol officers in this case—can be successfully used to carry out such programs. We find preliminary evidence that the program also impacted crime. At the same time, our study points to a bias in using official crime data to assess outcomes in programs that encourage community collaboration.
Similar content being viewed by others
Notes
All population and demographic information are taken from the American Community Survey 2012–2016 5-year estimates, “Community Facts,” http://factfinder.census.gov (accessed September 7, 2018).
Our analysis of dispatch data during the planning phase of the project showed that BPPD officers have on average 3 h 51 min of discretionary time during a 12-h shift (approximately one third of the shift).
The intervention was initially intended to last for a year, but BPPD extended the implementation using their own funds to provide additional time for problem-solving and data for analysis.
In a block-randomized experiment, blocks can be removed from the study without affecting the overall assumptions of an experimental design (see Weisburd and Gill 2014).
For a detailed description of the study methods, see the technical report for this project (Weisburd et al., 2018a).
However, we did include some civil complaints that reflected social disorganization and informal social control, including disorder, neighbor disputes, fighting, animal complaints, and noise violations.
Commercial streets were included as long as there was a business community to work with (i.e., a block that contained a large national chain retailer where staff would not be able to work with police without permission from corporate headquarters was not included).
This variable did not reduce the heterogeneity in the other factors and was therefore unnecessary. Each blocking factor reduces the degrees of freedom and can limit statistical power (Weisburd and Gill 2014).
Mean monthly citizen-initiated CFS in the treatment sites = 12.2 (SD = 18.5); control sites = 11.4 (SD = 10.1). Mean monthly crime incidents in treatment sites = 4.3 (SD = 6.8); control sites = 4.1 (SD = 4.0).
Again, we assume an ICC of .40 for the block level, but an ICC of only .02 for the hot spot level (these are all hot spots of crime, and we expect them to have relatively disadvantaged residents living across the sites).
Independent samples t tests indicate no significant differences at baseline between study conditions for both CFS and crime incidents. t42 = − .442, p = .661 and t42 = − .639, p = .527, respectively.
See Weisburd et al. (2018a) for full technical details of the survey.
Some business locations, such as small strip malls, had fewer addresses than our target number of surveys (for example, one of our hot spots consisted of a street segment with just three businesses). In these cases, the researchers attempted to interview multiple employees within the same business.
We drew a new sample of addresses for the follow-up survey, but six addresses were surveyed in both Wave 1 and Wave 2. Seventeen respondents in the follow-up survey said they remembered taking the survey before, although we cannot verify they were correctly remembering our survey. In most cases, we only conducted one survey per address; however, a few hot spots had fewer than seven addresses on the street, and at others, multiple people were willing to take the survey (this was usually the case at business addresses where a number of employees were working). Only 24 individuals (7.6% of all individuals surveyed) were nested in addresses at Waves 1 and 2 (3.7%) at Wave 2. As a sensitivity analysis, we also ran the models including random effects for individuals and addresses. Due to the lack of variability, the random effect for individuals created instability in the models. The random effect for address also did not contribute to several of the models, but where we were able to include it, the results were very similar to the models presented here.
The inflation factors were almost identical when we calculated them excluding Block 2 (1.67 in the treatment group and 1.26 in the control group), so we use the above inflation factor in later analyses, whether or not Block 2 is included.
Because of the very high correlation between block and logged pre-intervention crime, we also ran the models for the adjusted crime outcomes with block or logged pre-intervention crime excluded. For the model with block excluded, the observed one-tailed p value was .047 for the full sample. The p value excluding pre-intervention crime was .099, still significant at the .10 level.
Nagin and Sampson (2019) have raised the question of whether scaling up interventions like ACT creates interference between units, making it difficult to assess jurisdictional impact. We think it important to note that we expect that these types of programs implemented on a large scale would still be restricted to the most intractable hot spots in a city. The resources involved in applying treatment make scaling up much beyond that prohibitive.
References
Babbie, E. (2007). The practice of social research (11th ed.). Belmont: Wadsworth.
Borenstein, M., Hedges, L. V., & Rothstein, H. (2012). CRT Power. Teaneck: Biostat.
Braga, A. A., & Bond, B. J. (2008). Policing crime and disorder hot spots: A randomized controlled trial. Criminology, 46(3), 577–607. https://doi.org/10.1111/j.1745-9125.2008.00124.x.
Braga, A. A., & Clarke, R. V. (2014). Explaining high-risk concentrations of crime in the city: Social disorganization, crime opportunities, and important next steps. Journal of Research in Crime and Delinquency, 51(4), 480–498. https://doi.org/10.1177/0022427814521217.
Braga, A. A., & Schnell, C. (2013). Evaluating place-based policing strategies: Lessons learned from the smart policing initiative in Boston. Police Quarterly, 16(3), 339–357. https://doi.org/10.1177/1098611113497046.
Braga, A. A., Weisburd, D. L., Waring, E. J., Mazerolle, L. G., Spelman, W., & Gajewski, F. (1999). Problem-oriented policing in violent crime places: A randomized controlled experiment. Criminology, 37(3), 541–580. https://doi.org/10.1111/j.1745-9125.1999.tb00496.x.
Braga, A. A., Papachristos, A., & Hureau, D. (2012). Hot spots policing effects on crime. Campbell Systematic Reviews, 8(8), 1–94. https://doi.org/10.4073/csr.2012.8.
Braga, A. A., Papachristos, A. V., & Hureau, D. M. (2014). The effects of hot spots policing on crime: An updated systematic review and meta-analysis. Justice Quarterly, 31(4), 633–663. https://doi.org/10.1080/07418825.2012.673632.
Bursik, R. J. (1988). Social disorganization and theories of crime and delinquency: Problems and prospects. Criminology, 26(4), 519–552. https://doi.org/10.1111/j.1745-9125.1988.tb00854.x.
Bursik, R. J., & Grasmick, H. G. (1993). Neighborhoods and crime: The dimensions of effective community control. New York: Lexington Books.
Bursik, R. J., & Webb, J. (1982). Community change and patterns of delinquency. American Journal of Sociology, 88(1), 24–42. https://doi.org/10.1086/227632.
Coleman, S. (2002). A test for the effect of conformity on crime rates using voter turnout. The Sociological Quarterly, 43(2), 257–276. https://doi.org/10.1111/j.1533-8525.2002.tb00049.x.
Durlauf, S. N., & Nagin, D. S. (2011). Imprisonment and crime: Can both be reduced? Criminology & Public Policy, 10(1), 13–54. https://doi.org/10.1111/j.1745-9133.2010.00680.x.
Fung, A. (2004). Empowered participation: Reinventing urban democracy. Princeton: Princeton University Press.
Gill, C., & Weisburd, D. (2013). Increasing equivalence in small-sample place-based experiments: Taking advantage of block randomization methods. In B. C. Welsh, A. A. Braga, & G. J. N. Bruinsma (Eds.), Experimental criminology: Prospects for advancing science and public policy (pp. 141–162). New York: Cambridge University Press.
Gill, C., Weisburd, D., Telep, C. W., Vitter, Z., & Bennett, T. (2014). Community-oriented policing to reduce crime, disorder and fear and increase satisfaction and legitimacy among citizens: A systematic review. Journal of Experimental Criminology, 10(4), 399–428. https://doi.org/10.1007/s11292-014-9210-y.
Gill, C., Wooditch, A., & Weisburd, D. (2017). Testing the “law of crime concentration at place” in a suburban setting: Implications for research and practice. Journal of Quantitative Criminology, 33(3), 519–545. https://doi.org/10.1007/s10940-016-9304-y.
Holbrook, A. L., Krosnick, J. A., & Pfent, A. (2008). The causes and consequences of response rates in surveys by the news media and government contractor survey research firms. In J. M. Lepkowski, C. Tucker, J. M. Brick, E. de Leeuw, L. Japec, P. J. Lavrakas, et al. (Eds.), Advances in telephone survey methodology (pp. 499–528). Hoboken: Wiley.
Koper, C. S. (1995). Just enough police presence: Reducing crime and disorderly behavior by optimizing patrol time in crime hot spots. Justice Quarterly, 12(4), 649–672. https://doi.org/10.1080/07418829500096231.
Kubrin, C. E., & Weitzer, R. (2003). New directions in social disorganization theory. Journal of Research in Crime and Delinquency, 40(4), 374–402. https://doi.org/10.1177/0022427803256238.
Leshem, R., & Weisburd, D. (2019). Epigenetics and hot spots of crime: Rethinking the relationship between genetics and criminal behavior. Journal of Contemporary Criminal Justice, 35(2), 186–204. https://doi.org/10.1177/1043986219828924.
Nagin, D. S., & Sampson, R. J. (2019). The real gold standard: Measuring counterfactual worlds that matter most to social science and policy. Annual Review of Criminology, 2, 123–145. https://doi.org/10.1146/annurev-criminol-011518-024838.
Nagin, D. S., & Telep, C. W. (2017). Procedural justice and legal compliance. Annual Review of Law and Social Science, 13, 5–28. https://doi.org/10.1146/annurev-lawsocsci-110316-113310.
Nagin, D. S., & Telep, C. W. (2019). Procedural justice and legal compliance: A revisionist perspective. Manuscript submitted for publication.
Putnam, R. D. (2001). Social capital: measurement and consequences. Canadian Journal of Policy Research, 2(1), 41–51.
Ratcliffe, J. H. (2004). Geocoding crime and a first estimate of a minimum acceptable hit rate. International Journal of Geographical Information Science, 18(1), 61–72. https://doi.org/10.1080/13658810310001596076.
Reiss, A. J. (1971). The police and the public. New Haven: Yale University Press.
Rice, K. J., & Smith, W. R. (2002). Socioecological models of automotive theft: Integrating routine activity and social disorganization approaches. Journal of Research in Crime and Delinquency, 39(3), 304–336. https://doi.org/10.1177/002242780203900303.
Sampson, R. J. (2012). Great American city: Chicago and the enduring neighborhood effect. Chicago: University of Chicago Press.
Sampson, R. J., & Groves, W. B. (1989). Community structure and crime: Testing social-disorganization theory. American Journal of Sociology, 94(4), 774–802. https://doi.org/10.1086/229068.
Sampson, R. J., & Morenoff, J. D. (1997). Ecological perspectives on the neighborhood context of urban poverty: Past and present. In J. Brooks-Gunn, G. J. Duncan, & J. L. Aber (Eds.), Neighborhood poverty: Policy implications in studying poverty (pp. 1–22). New York: Russell Sage Foundation.
Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277(5328), 918–924. https://doi.org/10.1126/science.277.5328.918.
Shaw, C. R., & McKay, H. D. (1942). Juvenile delinquency in urban areas. Chicago: University of Chicago Press.
Shaw, C. R., Zorbaugh, F. M., McKay, H. D., & Cottrell, L. S. (1929). Delinquency areas: A study of the geographic distribution of school truants, juvenile delinquents, and adult offenders in Chicago. Chicago: University of Chicago Press.
Sherman, L. W., & Weisburd, D. (1995). General deterrent effects of police patrol in crime “hot spots”: A randomized, controlled trial. Justice Quarterly, 12(4), 625–648. https://doi.org/10.1080/07418829500096221.
Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hot spots of predatory crime: Routine activities and the criminology of place. Criminology, 27(1), 27–56. https://doi.org/10.1111/j.1745-9125.1989.tb00862.x.
Skogan, W. G. (2018). The commission and the police. Criminology & Public Policy, 17(2), 379–396. https://doi.org/10.1111/1745-9133.12366.
Skogan, W. G., & Frydl, K. (Eds.). (2004). Fairness and effectiveness in policing: The evidence. Washington, DC: National Academies Press.
Smith, W. R., Frazee, S. G., & Davison, E. L. (2000). Furthering the integration of routine activity and social disorganization theories: Small units of analysis and the study of street robbery as a diffusion process. Criminology, 38(2), 489–524. https://doi.org/10.1111/j.1745-9125.2000.tb00897.x.
Spelman, W., & Brown, D. K. (1984). Calling the police: Citizen reporting of serious crime. Washington: Police Executive Research Forum.
Taylor, R. B. (1997). Social order and disorder of street blocks and neighborhoods: Ecology, microecology, and the systemic model of social disorganization. Journal of Research in Crime and Delinquency, 34(1), 113–155. https://doi.org/10.1177/0022427897034001006.
Taylor, R. B. (2012). Defining neighborhoods in space and time. Cityscape: A Journal of Policy Development and Research, 14(2), 225–230. http://www.jstor.org/stable/41581108.
Taylor, R. B., Gottfredson, S. D., & Brower, S. (1984). Block crime and fear: Defensible space, local social ties, and territorial functioning. Journal of Research in Crime and Delinquency, 21(4), 303–331. https://doi.org/10.1177/0022427884021004003.
Telep, C. W., Mitchell, R. J., & Weisburd, D. (2014). How much time should the police spend at crime hot spots? Answers from a police agency directed randomized field trial in Sacramento, California. Justice Quarterly, 31(5), 905–933. https://doi.org/10.1080/07418825.2012.710645.
Thacher, D. (2019). The limits of procedural justice. In D. Weisburd & A. A. Braga (Eds.), Police innovation: Contrasting perspectives (2nd ed., pp. 95–119). New York: Cambridge University Press.
Trojanowicz, R. C., Kappeler, V. E., Gaines, L. K., & Bucqueroux, B. (1998). Community policing: A contemporary perspective (2nd ed.). Cincinnati: Anderson.
Tyler, T. R., Goff, P. A., & MacCoun, R. J. (2015). The impact of psychological science on policing in the United States: Procedural justice, legitimacy, and effective law enforcement. Psychological Science in the Public Interest, 16(3), 75–109. https://doi.org/10.1177/1529100615617791.
Uchida, C. D., Swatt, M. L., Solomon, S. E., & Varano, S. P. (2013). Neighborhoods and crime: Collective efficacy and social cohesion in Miami-Dade County (no. NCJ 245406). Silver Spring: Justice & Security Strategies, Inc. https://www.ncjrs.gov/pdffiles1/nij/grants/245406.pdf. Accessed 26 Nov 2019.
Uchida, C. D., Swatt, M. L., Solomon, S. E., & Varano, S. (2014). Data-driven crime prevention: New tools for community involvement and crime control (no. NCJ 245408). Silver Spring: Justice & Security Strategies, Inc https://www.ncjrs.gov/pdffiles1/nij/grants/245408.pdf. Accessed 26 Nov 2019.
Weisburd, D. (2012). Bringing social context back into the equation: The importance of social characteristics of places in the prevention of crime. Criminology & Public Policy, 11(2), 317–326. https://doi.org/10.1111/j.1745-9133.2012.00810.x.
Weisburd, D. (2015). The law of crime concentration and the criminology of place. Criminology, 53(2), 133–157. https://doi.org/10.1111/1745-9125.12070.
Weisburd, D., & Eck, J. E. (2004). What can police do to reduce crime, disorder, and fear? The Annals of the American Academy of Political and Social Science, 593(1), 42–65. https://doi.org/10.1177/0002716203262548.
Weisburd, D., & Gill, C. (2014). Block randomized trials at places: Rethinking the limitations of small N experiments. Journal of Quantitative Criminology, 30(1), 97–112. https://doi.org/10.1007/s10940-013-9196-z.
Weisburd, D., & Green, L. (1995). Policing drug hot spots: The Jersey City drug market analysis experiment. Justice Quarterly, 12(4), 711–735. https://doi.org/10.1080/07418829500096261.
Weisburd, D., & Majmundar, M. K. (Eds.). (2018). Proactive policing: Effects on crime and communities. Washington: National Academies Press. Accessed 26 Nov 2019.
Weisburd, D., & Mazerolle, L. G. (2000). Crime and disorder in drug hot spots: Implications for theory and practice in policing. Police Quarterly, 3(3), 331–349. https://doi.org/10.1177/1098611100003003006.
Weisburd, D., Groff, E. R., & Yang, S.-M. (2012). The criminology of place: Street segments and our understanding of the crime problem. New York: Oxford University Press.
Weisburd, D., Groff, E. R., & Yang, S.-M. (2014). Understanding and controlling hot spots of crime: The importance of formal and informal social controls. Prevention Science, 15(1), 31–43. https://doi.org/10.1007/s11121-012-0351-9.
Weisburd, D., Davis, M., & Gill, C. (2015). Increasing collective efficacy and social capital at crime hot spots: New crime control tools for police. Policing: A Journal of Policy and Practice, 9(3), 265–274. https://doi.org/10.1093/police/pav019.
Weisburd, D., Gill, C., Wooditch, A., Barritt, W., & Murphy, J. (2018a). Assets coming together (ACT) at crime hot spots: An experimental evaluation in Brooklyn Park, Minnesota. Fairfax: Center for Evidence-Based Crime Policy, Department of Criminology, Law & Society, George Mason University https://cebcp.org/wp-content/evidence-based-policing/Brooklyn-Park_Final-Report.pdf.
Weisburd, D., Wilson, D. B., & Mazerolle, L. (2018b). Analyzing block randomized studies: The example of the Jersey City drug market analysis experiment. Journal of Experimental Criminology. https://doi.org/10.1007/s11292-018-9349-z.
White, C., Weisburd, D., & Wire, S. (2018). Examining the impact of the Freddie gray unrest on perceptions of the police. Criminology & Public Policy, 17(4), 829–858. https://doi.org/10.1111/1745-9133.12404.
Wicker, A. W. (1987). Behavior settings reconsidered: Temporal stages, resources, internal dynamics, context. In D. Stokols & I. Altman (Eds.), Handbook of environmental psychology (pp. 613–653). New York: Wiley.
Acknowledgments
The opinions, recommendations, and conclusions herein are those of the authors and do not necessarily reflect the position of the U.S. Department of Justice. We would like to thank Chip Coldren, Craig Uchida, Robert Sampson, and Shellie Solomon for their advice and support in developing and implementing this study.
Funding
This research was funded by the U.S. Department of Justice, Bureau of Justice Assistance under Award Number 2013-DB-BX-0030.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Weisburd, D., Gill, C., Wooditch, A. et al. Building collective action at crime hot spots: Findings from a randomized field experiment. J Exp Criminol 17, 161–191 (2021). https://doi.org/10.1007/s11292-019-09401-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11292-019-09401-1