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Community Policing in Switzerland: A Comparative Evaluation of the Impact of Community Policing on Neighborhood Development in Major Swiss Urban Areas

English title Community Policing in Switzerland: A Comparative Evaluation of the Impact of Community Policing on Neighborhood Development in Major Swiss Urban Areas
Applicant Kuhn André
Number 132675
Funding scheme Project funding
Research institution Institut de criminologie et de droit pénal Ecole des Sciences Criminelles ESC Université de Lausanne
Institution of higher education University of Lausanne - LA
Main discipline Legal sciences
Start/End 01.10.2010 - 31.03.2012
Approved amount 80'272.00
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All Disciplines (2)

Discipline
Legal sciences
Social geography and ecology

Keywords (11)

neighborhood profiling; spatial statistics; community policing; process evaluation; impact evaluation; crime prevention; fear of crime; neighborhood profiling; machine learning; data mining; spatial statistics

Lay Summary (English)

Lead
Lay summary

Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The current research project is both a process and impact evaluation of community policing in Switzerland’s five major urban areas – Basel, Bern, Geneva, Lausanne, and Zurich.

The process evaluation builds on the results from an earlier SNSF research project (100015-122463), which tracked the organizational and strategic reforms the five police departments have undertaken to implement community policing. The qualitative data on police internal reforms were coded for quantitative analysis in order to measure implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that compares the implementation of community policing across urban areas and analyzes the impact of the different strategies between matched comparison areas across the five cites. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures.

In order to match comparison areas across the five urban areas, data mining algorithms were used to find meaningful subgroups of urban neighborhoods (using ZIP code districts as proxies). On the one hand, the clustering algorithm to develop the typology should regroup neighborhoods most similar with regard to the contextual variables that may affect the outcome variables. On the other hand, the survey response patterns should be similar for residents of the same neighborhood type across urban areas prior to the implementation of community policing.

The study concludes that over the last fifteen years, all five police departments have undertaken major internal reforms and forged strategic partnerships with local partners. The impact evaluation observed significant reductions in fear of crime over the 2000-2005 period in the neighborhoods in and around the centers of Bern and Zurich that covary temporally and spatially with progress made in the implementation of community policing. These improvements thus appear to be at least in part the result of community policing interventions, even if the observational design cannot completely rule out alternative explanations.

Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
Modélisation spatio-temporelle du sentiment d'insécurité dans 5 villes suisses
Kreis Christian (2011), Modélisation spatio-temporelle du sentiment d'insécurité dans 5 villes suisses, in Vues sur la ville, 26, 5-8.
Elaborer et tester des stratégies
GlardonM EspinozaM KreisC PerrierC PareinL LhuillierJ & DelgrandeN (2009), Elaborer et tester des stratégies, in Revue internationale de criminologie et de police technique et scientifique, 62(2), 114-128.
The Spatio-Temporal Patterns of Fear of Crime in Major Swiss Cities
Kreis Christian, The Spatio-Temporal Patterns of Fear of Crime in Major Swiss Cities, Université Franche-Comté et de Bourgogne, Besançon, France.

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Annual Meeting of the American Society of Criminology 19.11.2011 Washington DC, United States of America


Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
Journée de formation continues "Le rôle de la police en prévention" 14.01.2010 Lausanne, Switzerland


Associated projects

Number Title Start Funding scheme
122463 Community Policing in Switzerland: A Comparative Evaluation Study of the Community Policing Strategies of the Police in Major Swiss Urban Areas 01.10.2008 Project funding

Abstract

The current research project is a continuation of the SNSF research project “Community Policing in Switzerland: A Comparative Evaluation Study of the Community Policing Strategies of the Police in Major Swiss Urban Areas”. This ongoing project aims to provide a detailed overview of the community policing strategies of the police in Basel, Bern, Geneva, Lausanne, and Zurich and to assess their impact on neighborhood residents. First, the study tracked the organizational and strategic reforms the five police departments have undertaken to implement community policing. In a second step, the study analyzed data from the Swiss Crime Survey, which polled residents of these cities repeatedly between 1987 and 2005, for a discernable impact of community policing. Geostatistical analyses of spatio-temporal patterns using GIS software as well as long-term trend and preliminary multi-level analyses of the indicators of fear of crime, disorder, and popular satisfaction with the police have been performed.The results of these analyses consistently identified neighborhoods (using ZIP Code areas as proxies) as the pertinent unit of analysis to understanding recent developments in Swiss cities in matters of security. The geospatial analyses revealed that areas with elevated levels of fear shifted from the city centers to the peripheries over the last two decades. The preliminary multi-level analysis identified neighborhoods as the second most important source of inter-individual variance after the individual level, which accounted for a growing share of the variance of the indicators of community policing impact. Conversely, whereas some differences between the Swiss German and Swiss French cities appeared, response patterns within a given language area proved unexpectedly homogenous. It is thus contended that a community policing impact evaluation over such a long study period that does not control for neighborhood characteristics is unreliable at best and positively misleading at worst.The present study hence has a double objective. First, the development of a system to classify Swiss urban neighborhoods based on a series of environmental, socio-economic, and socio-demographic indicators and, second, the application of this neighborhood typology to enhance the validity of the planned impact evaluation of community policing. The study will use geomatics and GIS software in combination with advanced machine learning and data mining techniques to detect spatio-temporal patterns in high-dimensional space. The objective for this first phase of the project is to develop a clustering algorithm to create a classification system of urban neighborhoods that minimizes intra-neighborhood and maximizes inter-neighborhood variance in crime patterns and victimization survey responses. In a second phase, the neighborhood type will be used as an explanatory variable in spatial and multi-level multiple regression models to control for shifting neighborhood characteristics. The neighborhood typology will also serve as intelligence basis to select matching trial and control areas for quasi-experimental research designs to evaluate geographically confined community policing strategies such as neighborhood police stations, community liaison officers, and neighborhood improvement programs. The main innovative objectives of the present study are the following:1Apply new methodologies to enhance the validity of longitudinal impact evaluations of community policing2Aggregate survey respondents by neighborhood type to evaluate specific community policing strategies, which would otherwise be hampered by the small survey samples at the local level, in order to identify and exchange “best policing practices” ideally across the five cities3Devise ways for police practitioners to make enhanced use of the intelligence from regular public surveys to formulate proactive community oriented policing strategiesThe research team combines the necessary expertise in police research, data mining, and geostatistical modeling and already disposes over most of the data for the analyses envisioned by this study. The main results will be presented at academic conferences and published in scientific journals but also disseminated among police practitioners. International cooperative arrangements necessary for this interdisciplinary project are already established and will be strengthened during the project.
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