Journal of Quantitative Criminology

, Volume 33, Issue 3, pp 649–674 | Cite as

The Gains of Greater Granularity: The Presence and Persistence of Problem Properties in Urban Neighborhoods

  • Daniel Tumminelli O’BrienEmail author
  • Christopher Winship
Original Paper



This study applies the growing emphasis on micro-places to the analysis of addresses, assessing the presence and persistence of “problem properties” with elevated levels of crime and disorder. It evaluates what insights this additional detail offers beyond the analysis of neighborhoods and street segments.


We used over 2,000,000 geocoded emergency and non-emergency requests received by the City of Boston’s 911 and 311 systems from 2011–2013 to calculate six indices of violent crime, physical disorder, and social disorder for all addresses (n = 123,265). We linked addresses to their street segment (n = 13,767) and census tract (n = 178), creating a three-level hierarchy that enabled a series of multilevel Poisson hierarchical models.


Less than 1% of addresses generated 25% of reports of crime and disorder. Across indices, 95–99% of variance was at the address level, though there was significant clustering at the street segment and neighborhood levels. Models with lag predictors found that levels of crime and disorder persisted across years for all outcomes at all three geographic levels, with stronger effects at higher geographic levels. Distinctively, ~15% of addresses generated crime or disorder in one year and not in the other.


The analysis suggests new opportunities for both the criminology of place and the management of public safety in considering addresses in conjunction with higher-order geographies. We explore directions for empirical work including the further experimentation with and evaluation of law enforcement policies targeting problem properties.


Law of concentration of crime Physical disorder Social disorder Violent crime Computational social science 



The authors would like to thank our collaborative partners at the Department of Innovation and Technology and the Problem Properties Task Force at the City of Boston, as well as our colleagues Cynthia Rudin and Fulton Wang for valuable input during the conceptualization of the analysis.


This work received support from the National Science Foundation (Grant # SMA 1338446), the John D. and Catherine T. MacArthur Foundation (Grant # 13-105766-000), and support from the Radcliffe Institute for Advanced Study at Harvard University for the Boston Area Research Initiative.


  1. Andresen Martin A, Malleson Nicolas (2011) Testing the stability of crime patterns: implications for theory and policy. J Res Crime Delinq 48(1):58–82CrossRefGoogle Scholar
  2. Ashton Julie, Brown Imogen, Senior Barbara, Pease Ken (1998) Repeat victimisation: offender accounts. Int J Risk Secur Crime Prev 3(4):269–279Google Scholar
  3. Bennett Trevor (1995) Identifying, explaining, and targeting burglary ‘hot spots’. Eur J Crim Policy Res 3(3):113–123CrossRefGoogle Scholar
  4. Bernasco Wim (2008) Them again? Same-offender involvement in repeat and near repeat burglaries. Eur J Criminol 5(4):411–431CrossRefGoogle Scholar
  5. Bernasco Wim, Johnson Shane D, Ruiter Stijn (2015) Learning where to offend: effects of past on future burglary locations. Appl Geogr 60:120–129CrossRefGoogle Scholar
  6. Bichler G, Schmerler K, Enriquez J (2013) Curbing nuisance motels: an evaluation of police as place regulators. Polic An Int J Police Strateg Manag 36(2):437–462CrossRefGoogle Scholar
  7. Booth C (1903) Life and labour of the people in London. Macmillan & co, LondonGoogle Scholar
  8. Bowers KJ, Johnson SD (2005) Domestic burglary repeats and space-time clusters. Eur J Criminol 2(1):67–92CrossRefGoogle Scholar
  9. Braga AA, Bond BJ (2008) Policing crime and disorder hot spots: a randomized controlled trial. Criminology 46:577–607CrossRefGoogle Scholar
  10. Braga AA, Papachristos AV, Hureau DM (2010) The concentration and stability of gun violence at micro places in Boston, 1980–2008. J Quant Criminol 26:33–53CrossRefGoogle Scholar
  11. Braga AA, Hureau DM, Papachristos AV (2011) The relevance of micro places to citywide robbery trents: a longitudinal analysis of robbery incidents at street corners and block faces in Boston. J Res Crime Delinq 48(1):7–32CrossRefGoogle Scholar
  12. Browne WJ, Subramanian SV, Jones K, Goldstein H (2005) Variance partitioning in multilevel logistic models that exhibit overdispersion. J Royal Stat Soc A 168:599–613CrossRefGoogle Scholar
  13. Budd T (1999) Burglary of domestic dwellings: findings from the British Crime Survey. Home Office Statistical Bulletin 4/99. Home Office, LondonGoogle Scholar
  14. Bursik R, Grasmick HG (1993) Neighborhoods and crime: the dimensions of effective community control. Lexington Books, New YorkGoogle Scholar
  15. City of Boston (2011) Ordinance to eliminate public nuisance precipitated by problem properties in the city. In: Council C (ed) Ordinances, Chapter 16–55Google Scholar
  16. Curman ASN, Andresen MA, Brantingham PJ (2015) Crime and place: a longitudinal examination of street segment patterns in Vancouver, BC. J Quant Criminol 31:127–147CrossRefGoogle Scholar
  17. Eck John E (1994) Drug markets and drug places: a case-control study of the spatial structure of illicit drug dealing. University Microfilms International, Ann ArborGoogle Scholar
  18. Eck JE, Weisburd D (1995a) Crime places in crime theory. In: Eck JE, Weisburd D (eds) Crime and place. Criminal Justice Press, MonseyGoogle Scholar
  19. Eck JE, Weisburd D (eds) (1995b) Crime and place. Vol. 4, crime prevention studies. Criminal Justice Press, MonseyGoogle Scholar
  20. Farrell G, Pease K (2001) Repeat victimization. Criminal Justice Press, MonseyGoogle Scholar
  21. Frank R, Brantingham PL, Farrell G (2012) Estimating the true rate of repeat victimization from police recorded crime data: a study of burglary in metro Vancouver. Can J Criminol Crim Justice 54(4):481–494CrossRefGoogle Scholar
  22. Groff E, Weisburd D, Yang S-M (2010) Is it important to examine crime trends at a local “micro” level: a longitudinal analysis of street to steet variability in crime trajectories. J Quant Criminol 26:7–32CrossRefGoogle Scholar
  23. Grove LE, Farrell G, Farrington DP, Johnson SD (2012) Preventing repeat victimization: a systematic review. Swedish National Council for Crime PreventionGoogle Scholar
  24. Hibdon J, Telep CW, Groff ER (2016) The concentration and stability of drug activity in Seattle, Washington using police and emergency medical services data. J Quant Criminol. doi: 10.1007/s10940-016-9302-0
  25. Johnson SD (2008) Repeat victimisation: a tale of two theories. J Exp Criminol 23:201–219Google Scholar
  26. Johnson SD, Bowers KJ (2004) The burglary as clue to the future: the beginnings of prospective hot-spotting. Eur J Criminol 1(2):237–255CrossRefGoogle Scholar
  27. Johnson SD, Bowers KJ, Hirschfield AFG (1997) New insights into the spatial and temporal distribution of repeat victimization. Br J Criminol 37:224–241CrossRefGoogle Scholar
  28. Johnson SD, Bernasco W, Bowers KJ, Elffers H, Ratcliffe J, Rengert G, Townsley M (2007) Space-time patterns of risk: a cross national assessment of residential burglary victimization. J Quant Criminol 23:201–219CrossRefGoogle Scholar
  29. Johnson SD, Bowers KJ, Birks DJ, Pease K (2008) Predictive mapping of crime by ProMap: accuracy, units of analysis, and the environmental backcloth. In: Weisburd D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place. Springer, New YorkGoogle Scholar
  30. Johnson SD, Summers L, Pease K (2009) Offender as forager? A direct test of the boost account of victimization. J Quant Criminol 25:181–200CrossRefGoogle Scholar
  31. Kleemans E (2001) Repeat burglary victimization: results of empirical research in the Netherlands. In: Farrell G, Pease K (eds) Repeat victimization. Criminal Justice Press, MonseyGoogle Scholar
  32. Klinger DA, Bridges GS (1997) Measurement error in calls-for-service as an indicator of crime. Criminology 35(4):705–726CrossRefGoogle Scholar
  33. Levy MP, Tartaro C (2010) Repeat victimization: a study of auto theft in Atlantic City using the WALLS variables to measure environmental indicators. Crim Justice Policy Rev 21(3):296–318CrossRefGoogle Scholar
  34. LISC (2016) Problem properties 2015 [cited 1/4/2016 2016].
  35. Maciejewski R, Hafen R, Rudolph S, Larew SG, Mitchell MA, Cleveland WS, Ebert DS (2011) Forecasting hotspots–a predictive analytics approach. Vis Comput Gr 17:440–453CrossRefGoogle Scholar
  36. Minneapolis, MN (2016) Problem properties unit 2015 [cited 1/4/2016 2016].
  37. Mohler GO, Short MB, Brantingham PJ, Schoenberg FP, Tita GE (2011) Self-exciting point process modeling of crime. J Am Stat Assoc 106(493):100–107CrossRefGoogle Scholar
  38. O’Brien DT, Sampson RJ (2015) Public and private spheres of neighborhood disorder: assessing pathways to violence using large-scale digital records. J Res Crime Delinq 52:486–510Google Scholar
  39. O’Brien DT, Sampson RJ, Winship C (2015) Ecometrics in the age of big data: measuring and assessing “broken windows” using administrative records. Sociol Methodol 45:101–147CrossRefGoogle Scholar
  40. Pease K (1998) Repeat victimisation: taking stock. Vol. Paper 90, Crime detection and prevention series. Home Office, LondonGoogle Scholar
  41. Perry WL, McInnis CCP, Smith SC, Hollywood JS (2013) Predictive policing: the role of crime forecasting in law enforcement operations. RAND, Santa MonicaGoogle Scholar
  42. Pierce GL, Spaar S, Briggs LR (1988) The character of police work: stategic and tactical implications. Center for Applied Social Research, Northeastern University, BostonGoogle Scholar
  43. Ratcliffe JH, Rengert GF (2008) Near-repeat patterns in Philadelphia shootings. Secur J 21:58–76CrossRefGoogle Scholar
  44. Raudenbush SW, Bryk A (2002) Hierarchical linear models: applications and data analysis. Sage, Thousand OaksGoogle Scholar
  45. Raudenbush SW, Bryk A, Cheong YF, Congdon R, du Toit M (2004) HLM 6: hierarchical linear and nonlinear modeling. Scientific Software International, LincolnwoodGoogle Scholar
  46. Reiss AJ Jr (1980) Victim proneness in repeat victimization by type of crime. In: Fienberg SE, Reiss AJ Jr (eds) Indicators of crime and criminal justice: quantitative studies. United States Department of Justice, WashingtonGoogle Scholar
  47. Sampson RJ (2012) Great American City: Chicago and the enduring neighborhood effect. University of Chicago Press, ChicagoCrossRefGoogle Scholar
  48. Sampson RJ, Raudenbush SW, Earls F (1997) Neighborhoods and violent crime: a multilevel study of collective efficacy. Science 277:918–924CrossRefGoogle Scholar
  49. Schnell C, Braga AA, Piza EL (2016) The influence of community areas, neighborhood clusters, and street segments on the spatial variability of violent crime in Chicago. J Quant Criminol. doi: 10.1007/s10940-016-9313-x
  50. Shaw C, McKay H (1942/1969) Juvenile delinquency and urban areas. University of Chicago Press, ChicagoGoogle Scholar
  51. Sherman LW, Gartin PR, Buerger ME (1989) Hot spots of predatory crime: routine activities and the ciminology of place. Criminology 27(1):27–55CrossRefGoogle Scholar
  52. Smith WR, Frazee SG, Davison EL (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):489–524CrossRefGoogle Scholar
  53. Steenbeek W, Weisburd D (2016) Where the action is in crime? An examination of variability of crime across different spatial units in The Hague, 2001–2009. J Quant Criminol 32(3):449–469CrossRefGoogle Scholar
  54. Suttles GD (1972) The social construction of communities. University of Chicago Press, ChicagoGoogle Scholar
  55. Taylor RB (1997) Social order and disorder of street blocks and neighborhoods: ecology, microecology, and the systemic model of social disorganization. J Res Crime Delinq 34:113–155CrossRefGoogle Scholar
  56. Taylor RB, Gottfredson SD, Bower S (1984) Block crime and fear: defensible space, local social ties, and territorial functioning. J Res Crime Delinq 21:303–331CrossRefGoogle Scholar
  57. Townsley M, Homel R, Chaseline J (2003) Infectious burglaries: a test of the near repeat hypothesis. Br J Criminol 43:615–633CrossRefGoogle Scholar
  58. Trickett A, Osborn DR, Seymour J, Pease K (1992) What is different about high crime areas? Br J Criminol 32(1):81–89CrossRefGoogle Scholar
  59. Trickett A, Osborn DR, Ellingworth D (1995) Property crime victimisation: the roles of individual and area influences. Int Rev Victimol 3(4):273–295CrossRefGoogle Scholar
  60. Tseloni Ai (2006) Multilevel modelling of the number of property crimes: household and area effects. J Royal Stat Soc Series A (Stat Soc) 169(2):205–233CrossRefGoogle Scholar
  61. Tseloni A, Pease K (2014) Using modeling to predict and prevent victimization. Springer, New YorkGoogle Scholar
  62. Wang T, Rudin C, Wagner D, Sevieri R (2013) Learning to detect patterns of crime. In: Eurpoean conference on machine learning and principles and practice of knowledge discovery in databases. PragueGoogle Scholar
  63. Warner BD, Pierce GL (1993) Reexamining social disorganization theory using calls to the police as a measure of crime. Criminology 31(4):493–517CrossRefGoogle Scholar
  64. Way HK, Trinh S, Wyatt M (2013) Addressing problem properties: legal and policy tools for a safer Rundberg and Safer Austin. Entrepreneurship and Community Development Clinic: University of Texas Law School. Austin, TXGoogle Scholar
  65. Weisburd D (2012) Bringing social context back into the equation. Criminol Public Policy 11(2):317–326CrossRefGoogle Scholar
  66. Weisburd D (2015) The law of crime concentration and the criminology of place. Criminology 53(2):133–157CrossRefGoogle Scholar
  67. Weisburd D, Amram S (2014) The law of concentrations of crime at place: the case of Tel Aviv-Jaffa. Police Pract Res 15(2):101–114CrossRefGoogle Scholar
  68. Weisburd D, Bushway S, Lum C, Yang S-M (2004) Trajectories of crime at place: a longitudinal study of street segments in the city of Seattle. Criminology 42:283–322CrossRefGoogle Scholar
  69. Weisburd D, Morris NA, Groff ER (2009) Hot spots of juvenile crime: a longitudinal study of street segments in Seattle, Washington. J Quant Criminol 25:443–467CrossRefGoogle Scholar
  70. Weisburd D, Hinkle J, Famega C, Ready J (2011) The possible ‘backfire’ effects of hot spots policing: an experimental assessment of impacts on legitimacy, fear and collective efficacy. J Exp Criminol 7:297–320CrossRefGoogle Scholar
  71. Weisburd D, Groff ER, Yang S-M (2012) The criminology of place: street segments and our understanding of the crime problem. Oxford University Press, OxfordCrossRefGoogle Scholar
  72. Wells W, Wu L, Ye X (2012) Patterns of near-repeat gun assaults in Houston. J Res Crime Delinq 49:186–212CrossRefGoogle Scholar
  73. Wilcox P, Land KC, Hunt SC (2003) Criminal circumstance: a dynamic multicontextual criminal opportunity theory. Walter de Gruyster, New YorkGoogle Scholar
  74. Wilson JQ, Kelling GL (1982) The police and neighborhood safety: broken windows. Atlantic Mon 127:29–38Google Scholar
  75. Youstin TJ, Nobles MR, Ward JT, Cook CL (2011) Assessing the generalizability of the near repeat phenomenon. Crim Justice Behav 38:1042–1063CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Daniel Tumminelli O’Brien
    • 1
    • 2
    Email author
  • Christopher Winship
    • 2
  1. 1.Northeastern UniversityBostonUSA
  2. 2.Harvard UniversityCambridgeUSA

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