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Hot Spots of Juvenile Crime: A Longitudinal Study of Arrest Incidents at Street Segments in Seattle, Washington

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Abstract

Recent studies have shown that crime is concentrated at micro level units of geography defined as hot spots. Despite this growing evidence of the concentration of crime at place, studies to date have dealt primarily with adult crime or have failed to distinguish between adult and juvenile offenses. In this paper, we identify crime incidents in which a juvenile was arrested at street segments in Seattle, Washington, over a 14-year period, to assess the extent to which officially recorded juvenile crime is concentrated at hot spots. Using group-based trajectory analysis, we also assess the stability and variability of crime at street segments over the period of the study. Our findings suggest that officially recorded juvenile crime is strongly concentrated. Indeed, just 86 street segments in Seattle include one-third of crime incidents in which a juvenile was arrested during the study period. While we do observe variability over time in trajectories identified in the study, we also find that high rate juvenile crime street segments remain relatively stable across the 14 years examined. Finally, confirming the importance of routine activity theory in understanding the concentration of juvenile crime in hot spots, we find a strong connection between high rate trajectory groups and places likely to be a part of juvenile activity spaces. Though place-based crime prevention has not been a major focus of delinquency prevention, our work suggests that it may be an area with great promise.

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Notes

  1. It is important to note that portraits of the concentration of crime at place might be altered if larger geographic units were examined. This is often referred to as the ‘the modifiable areal unit problem' (Unwin 1996). However, the MAUP problem in studies of micro places is considerably lessened because the unit of aggregation is still extremely small and such studies generally use theoretically-driven units of analysis rather than ones of convenience. Street blocks for example, are much smaller than neighborhoods, census tracts or cities and thus have minimal aggregation bias. While some researchers have experimented with the use of grid cells to minimize the MAUP (Hirschfield et al. 1997), we believe that the use of a theoretically driven micro unit of analysis is a more defensible strategy. As we note below regarding our own approach, following Taylor (1997, 1998), we use street 100 blocks to represent ‘behavior settings’ and thus provide a theoretical basis for our choice of aggregation unit.

  2. Several studies have examined the concentration and stability of officially recorded crime in communities over time (Griffiths and Chavez 2004; Schmid 1960b). Additionally, several studies within the communities and crime literature have documented the concentration of self-reported crime within certain communities (Sampson and Groves 1989; Sampson et al. 1997). These studies have examined crime more generally, and have not disaggregated juvenile crime from adult crime.

  3. Normally, a street segment in Seattle is delimited in multiples of 100. For example, addresses from 100 to 199 Main Street would most likely occur on one street segment, between two intersections or other divisions. Following this, the database supporting the Seattle street map was used to develop “100 blocks” for each city street in Seattle. For example, if the base map listed a street as spanning house numbers 1 through 399, we created four segments from this range: 1–99, 100–199, 200–299, and 300–399. See Weisburd et al. (2004) for further discussion of the geo-coding process.

  4. The use of a street segment rather than an area (i.e., neighborhood, census tract, block group, zip code, etc.) also avoids the myriad of difficult coding issues that have been identified when trying to define perceptually-based geographic units such as a neighborhood (See Sampson et al. 2002; Suttles 1972).

  5. We want to remind the reader that our data refer only to crime at street segments and not crime at intersections. Of the 2,028,917 crime records initially obtained from the city from 1989 to 2002, 19% were linked to an intersection. Our decision to exclude these events was primarily technical. Intersections could not be assigned to any specific street segment because they were generally part of four different ones. However, it is also the case that incident reports at intersections differed dramatically from those at street segments. Traffic-related incidents, which are unlikely to involve juveniles, accounted for only 4.5% of reports at street segments, but for 44% of reports at intersections. Because we linked arrest data only to a street segment data base, we can not directly assess the number of juvenile arrest incidents that were dropped because of the exclusion of intersections. In a recent study by Braga et al. (1980–2008, Unpublished Manuscript) which compared shooting incidents using three different units of analysis (intersections, street segments, and both intersections and street segments) they found consistent overall results regardless of unit of analysis.

  6. We recognize that we could have used other statistical techniques such as hierarchical linear modeling (Bryk and Raudenbush 1987, 1992; Goldstein 1995), growth mixture modeling and nonparametric growth mixture modeling (Kreuter and Muthen 2008; Meredith and Tisak 1990; Muthen 1989) to identify developmental processes in our data. However, we thought that the trajectory approach was most fit to our interest in identifying specific crime patterns for street segments over time and visually displaying those patterns. While the interpretations drawn from the trajectory approach regarding whether groups are “real” have recently been criticized by some criminologists (e.g., see Eggleston et al. 2004; Sampson and Laub 2005), even its critics argue for the “scientific value of description and pattern recognition” (Sampson and Laub 2005: 911) that the trajectory approach offers. And indeed, this is precisely our interest in the use of trajectory analysis in this paper.

  7. We also used the zero-inflated Poisson model to accommodate over-dispersion and results are substantively similar to those generated by the non-inflated Poisson model. Given that the non-inflated model is more parsimonious, we report results from the Poisson model.

  8. A comparison of the Bayesian information criterion (BIC) across models is also useful for determining which models fit the best given the data. The BIC is useful for determining the optimal number of trajectory groups and is expressed in the following form:

    $$ {\text{BIC}} = { \log }\left( L \right) - 0. 5 \times { \log }\left( n \right) \times \left( k \right) $$

    where “L” is the value of the model’s maximized likelihood, “n” is the sample size, and “k” is the number of parameters (specifically groups). One very important benefit of the BIC is that it institutes a penalty for increasing the number of groups in the model. Expansion of the model by adding more groups is only desirable if the resulting improvement in the log likelihood exceeds the penalty for more parameters (Nagin 2005).

  9. For example, the odds of correct classification (OCC) estimates for all the trajectory groups are equal to or greater than 5.00, indicating that the model has high assessment accuracy. The odds of correct classification are a function of both the probability and posterior probability. Additionally, assignment accuracy is high when both the estimated group probabilities and the proportion of the sample assigned to the group on the basis of the maximum posterior probability rule are equivalent or correspond highly with each other.

  10. One intriguing question regarding this concentration of crime in juvenile crime hot spots is whether such places are spatially dependent. In another paper using these data, Groff, Weisburd and Morris (2009) have examined the spatial patterns of trajectory group members using a variety of local geographic measures. Overall, they found tremendous street segment to street segment variation in temporal patterns of juvenile crime.

  11. We constructed a 95% confidence interval around the average point estimate in 2002 for trajectory groups 6 (95% CI: 1.08–1.55) and 8 (95% CI: 5.94–7.09) to ensure that their respective end points did not overlap and were indeed significantly different. Confidence intervals indicated that each point estimate was distinct.

  12. We use the Poisson distribution to approximate the expected number of streets with exactly × incidents for both studies.

References

  • Agnew R, Peterson DM (1989) Leisure and delinquency. Soc Probl 36:332–350

    Google Scholar 

  • Appleyard D (1981) Livable streets. University of California Press, Berkeley

    Google Scholar 

  • Baumer EP, Lauritsen JL, Rosenfeld R, Wright R (1998) The influence of crack cocaine on robbery, burglary, and homicide rates: a cross-city longitudinal analysis. J Res Crime Delinq 35:316–340

    Google Scholar 

  • Block C, Dabdoub M, Fregly S (eds) (1995) Crime analysis through computer mapping. Police Executive Research Forum, Washington, DC

    Google Scholar 

  • Blumstein A, Wallman J (eds) (2000) The crime drop in America. Cambridge University Press, Cambridge

    Google Scholar 

  • Braga AA, Papachristos AV, Hureau D (1980–2008) The concentration and stability of gun violence at micro places in Boston (Unpublished Manuscript)

  • Braga AA, Weisburd D, Waring EJ, Mazerolle LG, Spelman W, Gajewski F (1999) Problem-oriented policing in violent crime places: a randomized controlled experiment. Criminology 37:541–580

    Google Scholar 

  • Brame R, Fagan J, Piquero AR, Schubert CA, Steinberg L (2004) Criminal careers of serious delinquents in two cities. Youth Violence Juv Violence 2:256–272

    Google Scholar 

  • Brame R, Nagin DS, Wasserman L (2006) Exploring some analytical characteristics of finite mixture models. J Quant Criminol 22:31–59

    Google Scholar 

  • Brantingham PL, Brantingham PJ (1975) Residential burglary and urban form. Urban Stud 12:104–125

    Google Scholar 

  • Brantingham PJ, Brantingham PL (1981) Environmental criminology. Waveland Press, Prospect Heights [1991]

    Google Scholar 

  • Brantingham PJ, Brantingham PL (1984) Patterns in crime. Macmillan, New York

    Google Scholar 

  • Brantingham PL, Brantingham PJ (1995) Criminality of place: crime generators and crime attractors. Eur J Crim Pol Res 3:5–26

    Google Scholar 

  • Brantingham PL, Brantingham PJ (1999) Theoretical model of crime hot spot generation. Stud Crim Crim Prev 8:7–26

    Google Scholar 

  • Bryk AS, Raudenbush SW (1987) Application of hierarchical linear models to assessing change. Psychol Bull 101:147–158

    Google Scholar 

  • Bryk AS, Raudenbush SW (1992) Hierarchical linear models for social and behavioral research: application and data analysis methods. Sage Publications, Newbury Park

    Google Scholar 

  • Burgess EW (1925a) The growth of the city: an introduction to a research project. In: Park RE, Burgess EW, McKenzie RD (eds) The city. University of Chicago Press, Chicago, pp 47–62 [1967]

    Google Scholar 

  • Burgess EW (1925b) Can neighborhood work have a scientific basis? In: Park RE, Burgess EW, McKenzie RD (eds) The city. University of Chicago Press, Chicago, pp 142–155 [1967]

    Google Scholar 

  • Bursik RJJ, Grasmick HG (1993) Neighborhoods and crime: the dimensions of effective community control. Lexington Books, New York

    Google Scholar 

  • Bursik RJJ, Webb J (1982) Community change and patterns of delinquency. Am J Sociol 88:24–42

    Google Scholar 

  • Bushway S, Brame R, Paternoster R (1999) Assessing stability and change in criminal offending: a comparison of random effects, semi-parametric, and fixed effects modeling strategies. J Quant Criminol 15:23–61

    Google Scholar 

  • Chilton RJ (1964) Continuity in delinquency area research: a comparison of studies for Baltimore, Detroit, and Indianapolis. Am Sociol Rev 29:71–83

    Google Scholar 

  • Clarke RV (1983) Situational crime prevention: its theoretical basis and practical scope. In: Morris N, Tonry M (eds) Crime and justice: a review of research, vol 14. University of Chicago Press, Chicago, pp 225–256

    Google Scholar 

  • Clarke RV, Cornish DB (1983) Crime control in Britain: a review of policy research. State University of New York Free Press, Albany

    Google Scholar 

  • Clarke RV, Weisburd D (1994) Diffusion of crime control benefits: observations on the reverse of displacement. In: Clarke RV (ed) Crime prevention studies, vol 3. Criminal Justice Press, Monsey, pp 165–184

    Google Scholar 

  • Cohen LE, Felson M (1979) Social change and crime rate trends: a routine activity approach. Am Sociol Rev 44:588–608

    Google Scholar 

  • Crow W, Bull J (1975) Robbery deterrence: an applied behavioral science demonstration—final report. Western Behavioral Science Institute, La Jolla

    Google Scholar 

  • Curtis LA (1974) Criminal violence: national patterns and behavior. Lexington Books, Lexington

    Google Scholar 

  • Duffala DC (1976) Convenience stores, armed robbery, and physical environmental features. Am Behav Sci 20:227–246

    Google Scholar 

  • Eck JE, Wartell J (1998) Improving the management of rental properties with drug problems: a randomized experiment. In: Mazerolle LG, Roehl J (eds) Civil remedies and crime prevention. Crime prevention studies, vol 9. Criminal Justice Press, Monsey, pp 161–185

  • Eck JE, Weisburd DL (1995) Crime places in crime theory. In: Eck JE, Weisburd DL (eds) Crime and place. Criminal Justice Press, Monsey, pp 1–33

    Google Scholar 

  • Eggleston EP, Laub JH, Sampson RJ (2004) Methodological sensitivities to latent class analysis of long-term criminal trajectories. J Quant Criminol 20:1–26

    Google Scholar 

  • Erickson ML, Empey LT (1963) Court records, undetected delinquency, and decision-making. J Crim Law Police Sci 54:456–469

    Google Scholar 

  • Federal Bureau of Investigation (2003) Crime in the United States 2002. Retrieved 21 May 2005 from: http://www.fbi.gov/ucr/cius_02/html/web/offreported/02- ncrimeindex01.html

  • Felson M (1995) Those who discourage crime. In: Eck JE, Weisburd DL (eds) Crime and place. Willow Tree Press, Monsey, pp 53–66

    Google Scholar 

  • Felson M (2002) Crime in everyday life. Sage, Thousand Oaks

    Google Scholar 

  • Felson M (2006) Crime and nature. Sage, Thousand Oaks

    Google Scholar 

  • Gold M (1966) Undetected delinquent behavior. J Res Crime Delinq 3:27–46

    Google Scholar 

  • Goldstein H (1995) Multilevel statistical models, 2nd edn. Arnold, London

    Google Scholar 

  • Gordon RA (1967) Issues in the ecological study of delinquency. Am Sociol Rev 32:927–944

    Google Scholar 

  • Green L (1996) Policing places with drug problems. Sage, Thousand Oaks

    Google Scholar 

  • Griffiths E, Chavez JM (2004) Communities, street guns, and homicide trajectories in Chicago, 1980–1995: merging methods for examining homicide trends across space and time. Criminology 42:941–978

    Google Scholar 

  • Groff ER, McEwen T (2005) Exploring the spatial configuration of places related to homicide events. National Institute of Justice, Washington, DC

    Google Scholar 

  • Groff ER, Weisburd D, Morris N (2009) Where the action is at places: examining spatio- temporal patterns of juvenile crime at places using trajectory analysis and GIS. In: Weisburd D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place: units of analysis in geographic criminology. Springer, New York, pp 61–86

    Google Scholar 

  • Guerry A-M (1833) Essai sur la Statisticque morale de la France. Crochard, Paris

    Google Scholar 

  • Hirschfield A, Yarwood D, Bowers K (1997) Crime pattern analysis, spatial targeting and GIS: the development of new approaches for use in evaluating community safety. In: Evans-Mudie N (ed) Crime and health data analysis using GIS. SCGISA, Sheffield

    Google Scholar 

  • Hunter RD (1988) Environmental characteristics of convenience store robberies in the state of Florida. American Society of Criminology, Chicago

    Google Scholar 

  • Hunter AJ, Baumer TL (1982) Street traffic, social integration, and fear of crime. Sociol Inq 52:122–131

    Google Scholar 

  • Jacobs J (1961) The death and life of great American cities. Vintage Books, New York

    Google Scholar 

  • Jeffery CR (1971) Crime prevention through environmental design. Sage, Beverly Hills

    Google Scholar 

  • Klinger D, Bridges G (1997) Measurement error in calls-for-service as an indicator of crime. Criminology 35:705–726

    Google Scholar 

  • Kreuter F, Muthen B (2008) Analyzing criminal trajectory profiles: bridging multilevel and group-based approaches using growth mixture modeling. J Quant Criminol 24:1–31

    Google Scholar 

  • LeBeau JL (1987) The methods and measures of centrography and the spatial dynamics of rape. J Quant Criminol 3:125–141

    Google Scholar 

  • Lind AW (1930) Some ecological patterns of community disorganization in Honolulu. Am J Sociol 36:206–220

    Google Scholar 

  • Lum C (2003) The spatial relationship between street-level drug activity and violence. Department of Criminology and Criminal Justice, University of Maryland, College Park

    Google Scholar 

  • Maltz MD, Gordon AC, Friedman W (1990 [2000]) Mapping crime in its community setting: event geography analysis. Originally published by Springer, New York, Internet edition available at http://www.uic.edu/depts/lib/forr/pdf/crimjust/mappingcrime.pdf. Accessed 15 August 2009

  • Mayhew P, Clarke RV, Hough M, Sturman A (1976) Crime as opportunity. Home office research study 34. H.M Stationary Office, London

    Google Scholar 

  • Mazerolle L, Rogan D, Frank J, Famega C, Eck JE (2005) Managing calls to the police with 911/311 systems. US Department of Justice, National Institute of Justice, Washington, DC

    Google Scholar 

  • McCord J, Widom CS, Crowell NA (eds) (2001) Juvenile crime, juvenile justice. National Academies Press, Washington, DC

    Google Scholar 

  • Meredith W, Tisak J (1990) Latent curve analysis. Psychometrika 55:107–122

    Google Scholar 

  • Muthen B (1989) Latent variable modeling in heterogeneous populations. Psychometrika 54:557–585

    Google Scholar 

  • Nagin DS (1999) Analyzing developmental trajectories: a semiparametric group-based approach. Psychol Methods 4:139–157

    Google Scholar 

  • Nagin DS (2004) Response to “methodological sensitivities to latent class analysis of long-term criminal trajectories”. J Quant Criminol 20:26–37

    Google Scholar 

  • Nagin DS (2005) Group-based modeling of development over the life course. Harvard University Press, Cambridge

    Google Scholar 

  • Nagin DS, Land KC (1993) Age, criminal careers, and population heterogeneity: specification and estimation of a nonparametric, mixed Poisson model. Criminology 31:327–362

    Google Scholar 

  • Newman O (1972) Defensible space: crime prevention through environmental design. Macmillan, New York

    Google Scholar 

  • Normandeau A (1968) Trends and patterns in crimes and robbery. University of Pennsylvania, Philadelphia

    Google Scholar 

  • Oberwittler D, Wikström PH (2009) Why small is better: advancing the study of the role of behavioral contexts in crime causation. In: Weisburd D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place: units of analysis in geographic criminology. Springer, New York, pp 35–59

    Google Scholar 

  • Osgood DW, Wilson JK, O’Malley PM, Bachman JG, Johnston LD (1996) Routine activities and individual deviant behavior. Am Sociol Rev 61:635–655

    Google Scholar 

  • Park RE, Burgess EW, McKenzie RD (eds) (1925) The city. University of Chicago Press, Chicago [1967]

    Google Scholar 

  • Pierce G, Spaar S, Briggs LR (1986) The character of police work: strategic and tactical implications. Center for Applied Social Research, Northeastern University, Boston

    Google Scholar 

  • Piquero AR (2008) Taking stock of developmental trajectories of criminal activity over the life course. In: Liberman AM (ed) The long view of crime: a synthesis of longitudinal research. Springer, Washington, DC, pp 23–78

    Google Scholar 

  • Pyle GF (1976) Spatial and temporal aspects of crime in Cleveland, Ohio. Am Behav Sci 20:175–198

    Google Scholar 

  • Quetelet AJ (1831) Research on the propensity for crime at different ages. Anderson Publishing, Cincinnati [1984]

    Google Scholar 

  • Rand A (1986) Mobility triangles. In: Figlio RM, Hakim S, Rengert GF (eds) Metropolitan crime patterns. Criminal Justice Press, Monsey, pp 117–126

    Google Scholar 

  • Reiss AJ Jr, Tonry M (eds) (1986) Communities and crime. Crime and justice: a review of research, vol 8. University of Chicago Press, Chicago

    Google Scholar 

  • Rengert G (1980) Spatial aspects of criminal behavior. In: Georges-Abeyie DE, Harries KD (eds) Crime: a spatial perspective. Columbia University Press, New York, pp 47–57

    Google Scholar 

  • Rengert GF (1981) Burglary in Philadelphia: a critique of an opportunity structure model. In: Brantingham PJ, Brantingham PL (eds) Environmental criminology. Waveland Press, Prospect Heights, pp 189–201

    Google Scholar 

  • Roman CG (2002) Schools as generators of crime: routine activities and the sociology of place. Department of Sociology, American University, Washington, DC

    Google Scholar 

  • Roman CG (2005) Routine activities of youth and neighborhood violence: spatial modeling of place, time, and crime. In: Wang F (ed) Geographic information systems and crime analysis. Idea Group, Hershey, pp 293–310

    Google Scholar 

  • Roncek DW (2000) Schools and crime. In: Goldsmith V, McGuire P, Mollenkopf JH, Ross TA (eds) Analyzing crime patterns: frontiers of practice. Sage, Thousand Oaks, pp 153–165

    Google Scholar 

  • Roncek DW, Bell R (1981) Bars, blocks and crimes. J Environ Syst 11:35–47

    Google Scholar 

  • Roncek DW, Faggiani D (1985) High schools and crime: a replication. Sociol Q 26:491–505

    Google Scholar 

  • Roncek DW, Maier PA (1991) Bars, blocks, and crimes revisited: linking the theory of routine activities to the empiricism of “hot spots”. Criminology 29:725–753

    Google Scholar 

  • Rosenbaum DP (2006) The limits of hot spots policing. In: Weisburd D, Braga A (eds) Police innovation: contrasting perspectives. Cambridge University Press, Campbridge, pp 245–263

    Google Scholar 

  • Sampson RJ, Groves WB (1989) Community structure and crime: testing social disorganization theory. Am J Sociol 94:774–802

    Google Scholar 

  • Sampson RJ, Laub JH (2005) Seductions of method: rejoinder to Nagin and Tremblay’s ‘developmental trajectory groups: fact or fiction’. Criminology 43(4):905–913

    Google Scholar 

  • Sampson RJ, Raudenbush SW, Earls F (1997) Neighborhoods and violent crime: a multilevel study of collective efficacy. Science 277:918–924

    Google Scholar 

  • Sampson RJ, Morenoff JD, Gannon-Rowley T (2002) Assessing “neighborhood effects”: social processes and new directions in research. Annu Rev Sociol 28:443–478

    Google Scholar 

  • Schmid CF (1960a) Urban crime areas: part I. Am Sociol Rev 25:527–542

    Google Scholar 

  • Schmid CF (1960b) Urban crime areas: part II. Am Sociol Rev 25:655–678

    Google Scholar 

  • Schmitt RC (1957) Density, delinquency and crime in Honolulu. Sociol Soc Res 41:274–276

    Google Scholar 

  • Schuerman L, Kobrin S (1986) Community careers in crime. In: Reiss AJ Jr, Tonry M (eds) Crime and justice: a review of research, vol 8. University of Chicago Press, Chicago, pp 67–100

    Google Scholar 

  • Shaw CR, McKay HD (1942) Juvenile delinquency and urban areas. University of Chicago Press, Chicago [1969]

    Google Scholar 

  • Shaw CR, Zorbaugh H, McKay HD, Cottrell LD (1929) Delinquency areas. University of Chicago Press, Chicago

    Google Scholar 

  • Sherman LW (1995) Hot spots of crime and criminal careers of places. In: Eck JE, Weisburd DL (eds) Crime and place. Criminal Justice Press, Monsey, pp 35–52

    Google Scholar 

  • Sherman LW, Weisburd D (1995) General deterrent effects of police patrol in crime ‘hot spots’: a randomized, controlled trial. Justice Quart 12:625–648

    Google Scholar 

  • Sherman LW, Gartin PR, Buerger ME (1989) Hot spots of predatory crime: routine activities and the criminology of place. Criminology 27:27–55

    Google Scholar 

  • Sickmund M, Snyder HN, Poe-Yamagata E (1997) Juvenile offenders and victims: 1997 update on violence, statistics summary. Office of Juvenile Justice and Delinquency Prevention, Washington, DC

    Google Scholar 

  • Skogan WG (1990) Disorder and decline: crime and the spiral of decay in American cities. Free Press, New York

    Google Scholar 

  • Skogan WG, Annan S (1994) Drugs and public housing: toward an effective police response. In: MacKenzie D, Uchida CD (eds) Drugs and crime: evaluating public policy initiatives. Sage, Thousand Oaks

    Google Scholar 

  • Skogan W, Frydl K (eds) (2004) Fairness and effectiveness in policing: the evidence. National Academies Press, Washington, DC

  • 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 38:489–523

    Google Scholar 

  • Snyder HN (2003) Juvenile arrests 2001. Juvenile justice bulletin. Office of Juvenile Justice and Delinquency Prevention, Washington, DC

    Google Scholar 

  • Sparrow MK, Moore MH, Kennedy DM (1990) Beyond 911: a new era for policing. Basic Books, New York

    Google Scholar 

  • Stephenson LK (1974) Spatial dispersion of intra-urban juvenile delinquency. J Geogr 73:20–26

    Google Scholar 

  • Suttles GD (1972) The social construction of communities. University of Chicago Press, Chicago

    Google Scholar 

  • 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 34:113–155

    Google Scholar 

  • Taylor RB (1998) Crime and small-scale places: what we know, what we can prevent, and what else we need to know. Crime and place: plenary papers of the 1997 conference on criminal justice research and evaluation. National Institute of Justice, Washington, DC, pp 1–22

    Google Scholar 

  • Taylor RB, Gottfredson SD, Brower S (1984) Block crime and fear: defensible space, local social ties, and territorial functioning. J Res Crime Delinq 21:303–331

    Google Scholar 

  • Thrasher FM (1927) The gang: a study of 1, 313 gangs in Chicago. University of Chicago Press, Chicago

    Google Scholar 

  • Tita G, Griffiths E (2005) Traveling to violence: the case for a mobility-based spatial typology of homicide. J Res Crime Delinq 42:275–308

    Google Scholar 

  • Turner S (1969) The ecology of delinquency. In: Sellin T, Wolfgang EM (eds) Delinquency: selected studies. Wiley, New York, pp 27–60

    Google Scholar 

  • Unwin DJ (1996) GIS, spatial analysis and spatial statistics. Prog Hum Geogr 20:540–541

    Google Scholar 

  • Wallace JM, Bachman JG (1991) Explaining racial/ethnic differences in adolescent drug use: the impact of background and lifestyle. Soc Probl 38:333–357

    Google Scholar 

  • Weisburd DL (2002) From criminals to criminal contexts: reorienting crime prevention. In: Waring E, Weisburd D (eds) Crime & social organization. Advances in criminological theory, vol 10. Transactions Publishers, New Brunswick, pp 197–216

    Google Scholar 

  • Weisburd D, Eck JE (2004) What can police do to reduce crime, disorder, and fear? Ann Am Acad Pol Soc Sci 593:42–65

    Google Scholar 

  • Weisburd D, Green L (1994) Defining the drug market: the case of the Jersey City DMA system. In: MacKenzie D, Uchida CD (eds) Drugs and crime: evaluating public policy initiatives. Sage, Thousand Oaks

    Google Scholar 

  • Weisburd D, Green L (1995) Policing drug hot spots: the Jersey City drug market analysis experiment. Justice Quart 12:711–735

    Google Scholar 

  • Weisburd DL, McEwen T (1997) Introduction: crime mapping and crime prevention. In: Weisburd DL, McEwen T (eds) Crime mapping and crime prevention: Crime prevention studies, vol 8. Criminal Justice Press, Monsey

    Google Scholar 

  • Weisburd D, Maher L, Sherman L (1992) Contrasting crime general and crime specific theory: the case of hot spots of crime. In: Adler F, Laufer WS (eds) Advances in criminological theory, vol 4. Transaction, New Brunswick, NJ, pp 45–70

  • Weisburd D, Bushway S, Lum C, Yang S-M (2004) Trajectories of crime at places: a longitudinal study of street segments in the city of Seattle. Criminology 42:283–321

    Google Scholar 

  • Weisburd D, Wyckoff LA, Ready J, Eck JE, Hinkle JC, Gajewski F (2006) Does crime just move around the corner? A controlled study of spatial displacement and diffusion of crime control benefits. Criminology 44:549–592

    Google Scholar 

  • Weisburd D, Bernasco W, Bruinsma GJN (eds) (2009) Putting crime in its place: units of analysis in geographic criminology. Springer, New York

    Google Scholar 

  • Williams JR, Gold M (1972) From delinquent behavior to official delinquency. Soc Probl 20:209–229

    Google Scholar 

  • Worden R, Bynum T, Frank J (1994) Police crackdowns on drug abuse and trafficking. In: MacKenzie D, Uchida CD (eds) Drugs and crime: evaluating public policy initiatives. Sage, Thousand Oaks

    Google Scholar 

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Acknowledgments

This research was supported via subcontract by grant 2001-JN-JX-K001 from the Office of Juvenile Justice and Delinquency Prevention (US Department of Justice) to the Jerry Lee Center of Criminology, University of Pennsylvania. Points of view in this paper are those of the authors and do not necessarily represent the US Department of Justice. We would like to thank John Eck, Josh Hinkle, Chris Koper, Cynthia Lum, Lorraine Mazerolle, Daniel Nagin, Alex Piquero, Jeff Roth, Cody Telep and Sue-Ming Yang for their thoughtful suggestions on earlier drafts of this manuscript. We want to express our gratitude for the cooperation of the Seattle Police Department, and especially to Chief Gil Kerlikowske for his interest and support of our work.

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Authors and Affiliations

  1. Hebrew University, Jerusalem, Israel

    David Weisburd

  2. George Mason University, Fairfax, VA, USA

    David Weisburd

  3. Southern Illinois University, Carbondale, IL, USA

    Nancy A. Morris

  4. Temple University, Philadelphia, PA, USA

    Elizabeth R. Groff

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  1. David Weisburd
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  3. Elizabeth R. Groff
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Correspondence to David Weisburd.

Appendix

Appendix

See Table 3.

Table 3 Distribution of all juvenile arrest incidents in Seattle by observed and expected number of street segments each year, (a) 1989–1993, (b) 1994–1998, (c) 1999–2002
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Weisburd, D., Morris, N.A. & Groff, E.R. Hot Spots of Juvenile Crime: A Longitudinal Study of Arrest Incidents at Street Segments in Seattle, Washington. J Quant Criminol 25, 443–467 (2009). https://doi.org/10.1007/s10940-009-9075-9

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