THE LAW OF CRIME CONCENTRATION AND THE CRIMINOLOGY OF PLACE*
Abstract
According to Laub (2004), criminology has a developmental life course with specific turning points that allow for innovations in how we understand and respond to crime. I argue that criminology should take another turn in direction, focusing on microgeographic hot spots. By examining articles published in Criminology , I show that only marginal attention has been paid to this area of study to date—often termed the criminology of place. I illustrate the potential utility of a turning point by examining the law of crime concentration at place, which states that for a defined measure of crime at a specific microgeographic unit, the concentration of crime will fall within a narrow bandwidth of percentages for a defined cumulative proportion of crime. By providing the first cross‐city comparison of crime concentration using a common geographic unit, the same crime type, and examining a general crime measure, I find strong support for a law of crime concentration. I also show that crime concentration stays within a narrow bandwidth across time, despite strong volatility in crime incidents. By drawing from these findings, I identify several key research questions for future study. In conclusion, I argue that a focus on the criminology of place provides significant opportunity for young scholars and has great promise for advancing criminology as a science.
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There is a law of crime concentration at places: crime is concentrated at similar levels across cities and across time.
“led Weisburd (2015) to argue that there is a “law of crime concentration” at places showing not just that crime is concentrated but that it is concentrated at similar levels across cities and across time.”
From Hot spots policing of small geographic areas effects on crime (2019) · cites this paper as Weisburd (2015)
Cites
Gottfredson, M. R., & Hirschi, T. (1990) · doi:10.1515/9781503621794 · Cited by 10,127 · see citing works
Social Change and Crime Rate Trends: A Routine Activity Approach
Cohen, L. E., & Felson, M. (1979) · American Sociological Review · doi:10.2307/2094589 · Cited by 8,856 · see citing works
HOT SPOTS OF PREDATORY CRIME: ROUTINE ACTIVITIES AND THE CRIMINOLOGY OF PLACE*
SHERMAN, L. W., GARTIN, P. R., & BUERGER, M. E. (1989) · Criminology · doi:10.1111/j.1745-9125.1989.tb00862.x · Cited by 2,104 · see citing works
General deterrent effects of police patrol in crime “hot spots”: A randomized, controlled trial
Sherman, L. W., & Weisburd, D. (1995) · Justice Quarterly · doi:10.1080/07418829500096221 · Cited by 1,029 · see citing works
Self-citationStatistic Notes: Regression towards the mean
Bland, J. M., & Altman, D. G. (1994) · BMJ · doi:10.1136/bmj.308.6942.1499 · Cited by 547 · see citing works
WEISBURD, D., WYCKOFF, L. A., READY, J., ECK, J. E., HINKLE, J. C., & GAJEWSKI, F. (2006) · Criminology · doi:10.1111/j.1745-9125.2006.00057.x · Cited by 533 · see citing works
Self-citationSherman, L. W. (2007) · Journal of Experimental Criminology · doi:10.1007/s11292-007-9044-y · Cited by 183 · see citing works
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Hot spots policing and crime reduction: an update of an ongoing systematic review and meta-analysis
Braga, A. A., Turchan, B. S., Papachristos, A. V., & Hureau, D. M. (2019) · Journal of Experimental Criminology · doi:10.1007/s11292-019-09372-3 · Cited by 352 · see citing works
Hot spots policing of small geographic areas effects on crime
Braga, A. A., Turchan, B., Papachristos, A. V., & Hureau, D. M. (2019) · Campbell Systematic Reviews: Better Evidence for a Better World · doi:10.1002/cl2.1046 · Cited by 226 · see citing works
CAN HOT SPOTS POLICING REDUCE CRIME IN URBAN AREAS? AN AGENT‐BASED SIMULATION*
WEISBURD, D., BRAGA, A. A., GROFF, E. R., & WOODITCH, A. (2017) · Criminology · doi:10.1111/1745-9125.12131 · Cited by 140 · see citing works
Self-citationAriel, B., Weinborn, C., & Sherman, L. W. (2016) · Journal of Experimental Criminology · doi:10.1007/s11292-016-9260-4 · Cited by 134 · see citing works
“…predictive and diagnostic approaches show that crime is disproportionately concentrated into a Bpower few^ Bmicro^ areas of land afflicted by a disproportional number of antisocial events (Pierce et al. 1988; Sherman 1987; Sherman 1995; Sherman et al. 1989; Weisburd 2015; Weisburd et al. 2004).”
InfluentialOwens, E., Weisburd, D., Amendola, K. L., & Alpert, G. P. (2018) · Criminology & Public Policy · doi:10.1111/1745-9133.12337 · Cited by 111 · see citing works
Self-citationBuilding collective action at crime hot spots: Findings from a randomized field experiment
Weisburd, D., Gill, C., Wooditch, A., Barritt, W., & Murphy, J. (2021) · Journal of Experimental Criminology · doi:10.1007/s11292-019-09401-1 · Cited by 46 · see citing works
Self-citationTaylor, R. B., & Ratcliffe, J. H. (2020) · Criminology & Public Policy · doi:10.1111/1745-9133.12514 · Cited by 16 · see citing works
- Authors
- WEISBURD, D.
- Affiliations
- George Mason University (US)
- Corresponding author
- WEISBURD, DAVID
- ORCID
- WEISBURD, DAVID
- Venue
- Criminology
- Publisher
- Wiley
- Published
- 2015-05
- Volume
- 53
- Issue
- 2
- Pages
- 133-157
- ISSN
- 0011-1384 (ISSN-L)
- 1745-9125
- OpenAlex
- W1479955723
- Cited by
- 1,064
- References
- 7
- Citations by year
- 2026: 168 · 2025: 103 · 2024: 95 · 2023: 90 · 2022: 112 · 2021: 114 · 2020: 111 · 2019: 102 · 2018: 74 · 2017: 46 · 2016: 38 · 2015: 11
- FWCI
- 173.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Criminology (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Crime Patterns and Interventions
- Social Sciences › Law › Criminal Justice and Penology
- Social Sciences › Sociology and Political Science › Urban, Neighborhood, and Segregation Studies
- Keywords
- crime concentration, crime hotspots, cross-city comparison
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