از ور کلید ماشین روبردار: ساختار شهری و جاده طولانی تا بزهکاری
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38598||2012||11 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Criminal Justice, Volume 40, Issue 1, January–February 2012, Pages 83–93
Abstract Purpose This research fulfills a void in offender mobility discourse. Metropolitan socioeconomic and spatial structure, defined in crime pattern theory as the urban backcloth, plays a significant role in shaping travel behavior; and yet, current analysis of offender mobility continues to favor individual characteristics to account for travel range. Methods Using a large sample of juveniles, both delinquent and at-risk youth (N = 2,552), this study compared the predictive utility of individual characteristics against indicators of urban backcloth. Results Delinquent youth were found to be more sensitive to the environmental conditions exerted by community-level socioeconomic characteristics than their at-risk counterparts. However, two factors—intercity hierarchical structure and motor vehicle access—accounted for travel variability among all youth. Conclusions Offending behavior must be examined within the context of a dynamic environmental context formed by the metropolitan socioeconomic and spatial structure. Delinquents constitute an identifiable subgroup of youth.
Introduction Underpinning studies of metropolitan structure is deference to the ideas of central place theory (Christaller, 1933, Lösch, 1954 and Berry, 1967): market systems shape the intercity arrangement of social, economic, and political activities that are reflected in city and regional geography (e.g., ESPON, 2003, Felson, 1987 and Gordon and Richardson, 1996). Crime pattern theory integrates, expands, and applies these geographic concepts to offender behavior to explain how metropolitan structure—the spatial and social organization of communities—influences offender travel habits and ultimately, crime patterns ( Brantingham & Brantingham, 2008). If routine travel reflects the spatially embedded processes that shape urban landscapes, then variation in mobility patterns are as much a function of individual objectives, perspectives and demographics, as the environmental context ( Forman et al., 2008, Johansson, 2006 and McDonald, 2007). Integrating geographic principles is necessary to advance knowledge about offender movement; however, this must occur through systematic testing. Prior studies have not included a non-offending comparison group when examining the travel habits of deviants. While it is theoretically feasible to assume that the travel habits of deviants and non-offending, at-risk youth are similarly influenced by critical variables, a direct comparison is needed to bolster the empirical connection between tenets of geography and applied criminology. The present study aims to address these caveats and extend a line of inquiry aimed at decoding variability in offender travel behavior by assessing the relative effects of predictors measured at two different units of analysis with multilevel models (MLM).1 If travel is nested within metropolitan structure as geographic research suggests (e.g., Schlossberg et al., 2006 and Wheeler and Stutz, 1971), then MLM can uncover the complex dynamics affecting individual behavior (Raudenbush and Bryk, 2002 and Singer and Willett, 2003). As will be shown here, isolating specific factors and interaction effects, while comparing deviants to at-risk youth, provides an opportunity to empirically bridge streams of travel research. In turn, this will fuel theoretical development in several fields, advance efforts to identify population subgroups, and support the development of effective crime prevention strategies. Prior to discussing the results of this study, a brief overview of the relevant literature is presented.
نتیجه گیری انگلیسی
Conclusion Delinquents exhibited substantially greater travel range compared to at-risk youth with the introduction of individual level characteristics (delinquents travel almost twice as far). Though the gap diminished slightly with the introduction of second-level factors, a 1.5 mile discrepancy remained. This distance may appear small relative to adult patterns, but the length is important within a juvenile context. Delinquent youth routinely travel about 4 miles from home, generating an 8 mile diameter (and a 50.3 square mile territory); with residential neighborhoods located at a distance from commercial areas, this could mean that youth escape to the downtown cores of their home city, or they may cross city boundaries, choosing to spend discretionary time in adjacent cities. Either way, their travel will bring them into contact with youth (potentially delinquent) from other social networks (other schools). Delinquent youth are different than at-risk youth; they travel a longer road, exhibiting greater mobility. While cell phones may enable parents to speak with their children, these communications are no substitute for seeing what the youth are doing. Again, the findings support the likelihood that a material difference between delinquents and at-risk youth may be found in the supervision potential of their discretionary time. The results of this study indicate that subgroup variation accounts for, at least to some extent, the travel patterns of juvenile delinquents; however, even with the use of MLM some of the variation remains unexplained. With 45 percent of the variance being located at the city level, it is imperative that continued attention be focused on identifying robust community-level factors. Future research examining offender mobility should continue to compare offenders to other segments of the population. Even among offenders, subgroups are likely to exist. If most of the prior research studied chronic, serial offenders—a small though prolific segment of the offending population—then their behavior is likely to be markedly different from the occasional criminal. If, as several theories suggest, the vast proportion of the offending population are occasional, opportunistic offenders, then we know very little about their travel habits. Consequently, we also know very little about the way most offenders identify/ select targets. If so, how is it possible to develop effective, broad-based crime prevention programs? Clearly, there is still a lot of research to be done.