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Date: April 18, 2024 Thu
Time: 5:39 pm
Time: 5:39 pm
Results for hotspots
5 results foundAuthor: Clear, Todd R. Title: Predicting Crime through Incarceration: The Impact of Rates of Prison Cycling On Rates of Crime in Communities Summary: The purpose of this project has been to estimate the impact of "prison cycling" -the flow into and out of prison - on crime rates in communities, with special concern about areas that have high rates of prison cycling. In this work, we explicitly hypothesized that: (1) there would be a positive impact of neighborhood reentry rates on neighborhood crime rates, controlling for neighborhood characteristics; (2) there would be a positive effect of neighborhood removal rates (admissions) on neighborhood crime rates, controlling for neighborhood characteristics; (3) the effect of the rate of both removal and reentry on the neighborhood crime rate would depend upon the level of removal and reentry (tipping point); and (4) the effect of the rate of both removal and reentry on crime the neighborhood crime rate would depend upon the level of concentrated disadvantage in the neighborhood (interaction effect). To complete the proposed work, we compiled datasets on prison admissions and releases that would be comparable across places and geocoded and mapped those data onto crime rates across those same places. The data used were panel data. The data were quarterly or annual data, depending on the location, from a mix of urban (Boston, Newark and Trenton) and rural communities in New Jersey covering various years between 2000 and 2012. Census tract characteristics come from the 2000 Census Summary File 3. The crime, release, and admission data were individual level data that were then aggregated from the individual incident level to the census tract level by quarter (in Boston and Newark) or year (in Trenton). The analyses centered on the effects of rates of prison removals and returns on rates of crime in communities (defined as census tracts) in the cities of Boston, Massachusetts, Newark, New Jersey, and Trenton, New Jersey, and across rural municipalities in New Jersey. Our analytic strategy, was one of analytic triangulation. Through the data collection associated with this project, we amassed a uniquely comprehensive crime and incarceration dataset over time - arguably one of the most comprehensive assembled to date. This dataset allowed us to model the relationship between crime and incarceration using a range of techniques (fixed effects panel models, Arrellano-Bond estimations, and vector auto-regression) taking advantage of each and being partially freed of the limitations of any one. We gave considerable attention to the problem of modeling. As might be expected, different models often provide different results. The most parsimonious models provide small standard errors with significant results, but there are sometimes sign changes when new control variables are added, suggesting instability in the modeling strategy. By contrast, the most stable results are provided by fixed effects models that, while intuitively attractive, have the disadvantage of large standard errors. When we use this analytic approach, we achieve results that, we believe, are more reliable. Overall, our work finds strong support for the impact of prison cycling on crime. It seems that such cycling has different effects in different kinds of neighborhoods, consistent with the idea of a "tipping point" but more clearly expressed as an interaction between crime policy and type of neighborhood. The results in Tallahassee, Boston, and Trenton provide consistent support for this idea. In Newark, as a result of the city's limited variability in neighborhood disadvantage, we failed to find the same pattern. Further research will investigate whether this neighborhood interaction holds in other sites. It will also enable us to think about how neighborhood change over time affects the prison cycling-crime relationship. Do neighborhoods that improve start to benefit from incarceration policy? In contrast, does current incarceration policy become a factor that inhibits neighborhood improvement? Details: Final Report submitted to the U.S. National Institute of Justice, 2014. 141p. Source: Internet Resource: Accessed August 11, 2014 at: https://www.ncjrs.gov/pdffiles1/nij/grants/247318.pdf Year: 2014 Country: United States URL: https://www.ncjrs.gov/pdffiles1/nij/grants/247318.pdf Shelf Number: 132949 Keywords: Crime ModelingCrime PlacesHotspotsNeighborhoods and CrimeRecidivismSocioeconomic Conditions and Crime |
Author: Kuo, Pei-Fen Title: Using Geographical Information Systems to Organize Police Patrol Routes Effectively by Grouping Hot Spots of Crash and Crime Data Summary: Applying Data-Driven Approaches to Crime and Traffic Safety (DDACTS) can help police departments allocate limited resources more efficiently. By focusing on hazardous areas, highly visible traffic law enforcement can reduce crime and crashes simultaneously. Most studies have focused on the reduction of crime and crashes after applying new patrol routes, but few have documented how to improve or change police dispatch time. The objective of this study was to compare the police dispatch time between two conditions: (1)Police patrol routes with organized hotspots; and (2) Police patrol route patterns without focusing on hotspots. A secondary objective consisted of developing a procedure describes the calculation of the change in dispatch time. This study used data obtained from the College Station Police Department. Crime and crash data were collected between January 2005 and September 2010, which included 65,461 offense reports and 14,712 crash reports. The proposed study procedure included four steps: (1) Geocoding data, (2) defining hotspots, (3) organizing the best patrol routes, and (4) estimating the effectiveness. ArcGIS was used for the data analysis. The results indicated that using DDACTS principles can potentially reduce police dispatch time by 13% and 17% when the top 5 and top 10 hotspot routes are included in the analysis, respectively. The procedure can be used by law enforcement agencies to estimate whether or not the DDACTS protocols can be an effective tool for reducing law enforcement dispatch times when crash and crime data are analyzed simultaneously. Details: Paper submitted for potential publication in Journal of Transportation Geography, 2011. 23p. Source: Internet Resource: Accessed February 25, 2016 at: https://ceprofs.civil.tamu.edu/dlord/Papers/Kuo_et_al._DDACT.pdf Year: 2012 Country: United States URL: https://ceprofs.civil.tamu.edu/dlord/Papers/Kuo_et_al._DDACT.pdf Shelf Number: 137963 Keywords: Crime and Place Crime Hotspots Geographical Information Systems (GIS) HotspotsPolice Patrol |
Author: de Brito, Charlotte Title: Will Providing Tracking Feedback on Hot Spot Patrols Affect the Amount of Patrol Dosage Delivered? A Level 4 Experiment Summary: Objectives Hot spots patrol is a police tactic shown time and time again to reduce crime, with a robust body of supporting evidence suggested. Less widely researched is how to ensure the police tasked with carrying out these patrols do as they have been asked. In this thesis, research will be presented which seeks to bridge this gap. Methods In a before-after experiment carried out over 4 weeks in August 2016 within British Transport Police (BTP), two sites assigned to treatment conditions (London Waterloo and London Euston) were provided feedback on dosage delivery - i.e., weekly reports showing the number of "hot spots visits" carried out the previous week by the PCs and PCSOs assigned to hot spot patrol. Two sites assigned to control conditions received no such information, but were still required to conduct hot spots patrols as business as usual. Results No overall statistically significant differences in terms of patrol dosage between the two treatment and two control sites were found, indicating that feedback in the form of a set of figures and graphs on the previous weeks' performance sent via email does not increase dosage. However, when the 2 treatment sites were analysed separately, substantial increases were found in patrol dosage at London Waterloo but no discernible effect at London Euston, compared to control conditions. These subgroup analyses are likely to be driven by varying leadership styles in the two treatment sites. Conclusions Patrol dosage feedback can be positively correlated with patrol dosage, however only when the leader responsible for those individuals is willing to act. In this experiment, there was no adverse consequence for poor patrol performance in the treatment sites, hence the threat can be deemed 'toothless'. Onus cannot be left on individuals to react to and improve on poor performance, and a feedback loop must be put in place to allow corrective action to be taken if an individual consistently fails to improve. Further research is recommended, testing treatment conditions which include an adverse consequence of poor performance, with a larger number of experimental sites. Details: Cambridge, UK: Fitzwilliam College, 2016. 75p. Source: Internet Resource: Thesis: Accessed April 10, 2017 at: http://www.crim.cam.ac.uk/alumni/theses/Charlotte%20de%20Brito.pdf Year: 2016 Country: United Kingdom URL: http://www.crim.cam.ac.uk/alumni/theses/Charlotte%20de%20Brito.pdf Shelf Number: 144773 Keywords: Crime AnalysisCrime HotspotsHigh Crime AreasHotspotsPolice Patrol |
Author: Fabusuyi, Tayo Title: East Liberty Crime Data Analysis Summary: Within a span of five years, 2008 to 2012, overall crime in the residential area of East Liberty has decreased by 49%, and residential property prices have doubled. These developments occurred in an environment where the median income stagnated and actually declined in real terms and where there was minimal change in the racial composition of the neighborhood. This crime reduction is significantly greater than what occurred in the City of Pittsburgh during that period, and is also larger than that observed for comparable neighborhoods in close proximity to East Liberty. A series of questions prompted by these developments are what informed this study. Numeritics, a Pittsburgh-based consulting practice, was approached by the real estate arm of East Liberty Development Incorporated (ELDI), to examine the linkages between these developments and ELDI initiatives. Numeritics was tasked with providing plausible reasons that explain these developments; examining the degree to which ELDI was responsible for them and documenting the process by which these outcomes were achieved while providing some formalism on the process. ELDI staff who live in or around East Liberty came to the realization that crime is a real estate problem and therefore requires a real estate solution. In their experience, most of the criminal activity emanated from or around nuisance properties typically owned by slumlords, an observation buttressed by existing "hot spot" literature on crime that shows that 3% of addresses are responsible for 50% of all service calls to the police. This prompted the decision to embark on targeted acquisition of these properties at scale - a strategy reminiscent of the hot spot theory. Decisions on which properties to target came out of a combination of approaches. Using a "boots on the ground" approach, ELDI staffers became intimately involved in the neighborhood. They listened to complaints from neighbors, talked to the police and examined crime statistics. As a result of this process, East liberty "hot spots" were identified, most of which were either slumlord or abandoned properties. These properties were then targeted for acquisition by ELDI. In total, more than 200 units were purchased, representing 3% of the total rental housing units within the neighborhood. Post-acquisition, effective property managers were put in place to regulate the conduct of the properties and to function as place-owners. This strategy of property acquisition and management was strengthened by a number of complementary initiatives that helped to increase neighborhood cohesiveness. Beginning in 1997, ELDI has been highly conscious of involving neighborhood residents in the planning, decisionmaking and redevelopment process. These efforts allowed for the rebuilding of neighborhood cohesion and trust; what some call "collective efficacy"; the willingness of neighbors to intervene on behalf of the common good. This side effect in turn increases informal social controls; or neighbors looking out for each other, with the result being a positive effect on crime rates. Details: Pittsburgh, PA: Numeritics, 2013. 23p. Source: Internet Resource: Accessed February 8, 2018 at: http://helppgh.org/wp-content/uploads/2016/04/Report_of_the_ELDI_Crime_Study.pdf Year: 2013 Country: United States URL: http://helppgh.org/wp-content/uploads/2016/04/Report_of_the_ELDI_Crime_Study.pdf Shelf Number: 149026 Keywords: Collective EfficacyCrime AnalysisCrime HotspotsHotspotsHousing and CrimeNeighborhoods and CrimeResidential Areas and Crime |
Author: Barrett, Kimberly L. Title: Assessing the Relationship Between Hotspots of Lead and Hotspots of Crime Summary: Abstract Numerous medical and environmental toxicology studies have established a link between lead (Pb) exposure, crime, and delinquency. In human environments, lead pollution- like crime- is unequally distributed, creating lead hot spots. In spite of this, studies of crime hotspots have routinely focused on traditional sociological predictors of crime, leaving environmental predictors of crime like lead and other neurotoxins relatively unaddressed. This study attends to this gap in the literature by asking a very straightforward research question: Is there a relationship between hotspots of lead and hotspots of crime? Furthermore, what is the nature and extent of this relationship? Lastly, is the distribution of lead across communities relative to race, class, and/or ethnicity? To explore these issues, a series of thirteen research hypotheses are derived based on findings from previous lead and crime studies. To test these research hypotheses, data was collected from the city of Chicago’s Community Areas (n = 77) in Cook County, Illinois. Information from a range of secondary sources including the U.S. Census, Environmental Protection Agency, Chicago Police Department, and City of Chicago are merged and analyzed. Cross sectional and longitudinal assessments are conducted, and results from a series of negative binomial regressions, fixed effects negative binomial regressions, and correlations are presented. Findings suggest the association between lead and crime appeared particularly robust with respect to rates of violent index crime, but less so for rates of property index crime. Contrary to what prior research suggests, the association between lead and crime appears stronger for rates of arrests for adult index crimes than rates of arrests for juvenile index crime arrests. This study concludes by discussing theory and policy implications alongside recommendations for future study. Details: Florida, 2013. 214p. Source: Internet Resource: Accessed October 5, 2018 at: https://scholarcommons.usf.edu/cgi/viewcontent.cgi?referer=https://www.google.com/&httpsredir=1&article=5632&context=etd Year: 2013 Country: United States URL: https://scholarcommons.usf.edu/cgi/viewcontent.cgi?referer=https://www.google.com/&httpsredir=1&article=5632&context=etd Shelf Number: 151534 Keywords: Crime Rates Environmental Factors Hotspots |