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- W3011149639 abstract "Predictive policing models aim to predict crime events based onavailable crime and socio-economic data at a micro-geographic level. The aim of this study isto investigate the potential of including data on social capital, disorder and fear of crime forimproving prediction performance of the predictive policing model. To this end, data is usedfrom the Social capital and Well-being In Neighbourhoods in Ghent (SWING) survey, theSocial Capital in Neighbourhoods (SCAN) project and the quality of life monitor from thecity of Ghent. These datasets are based on extensive surveys at the neighbourhood level inGhent and contain variables related to among others social capital, collective efficacy, socialand physical disorders, and fear of crime. The prediction performance of two models arecompared against each other: one model with the social capital variables included and onebase model without these variables, with only basic crime and socio-economic variablesincluded. The results of this analysis and its implications for the prediction performance of thepredictive policing model will be discussed." @default.
- W3011149639 created "2020-03-23" @default.
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- W3011149639 date "2019-01-01" @default.
- W3011149639 modified "2023-09-26" @default.
- W3011149639 title "Social capital variables at the neighbourhood level as predictors in a predictive policing model" @default.
- W3011149639 hasPublicationYear "2019" @default.
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