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The Effect of Social Cohesion on Levels of Recorded Crime in Disadvantaged Areas

Author

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  • A. Hirschfield

    (Urban Research and Policy Evaluation Regional Research Laboratory, Department of Civic Design, University of Liverpool, P. O. Box 147, Liverpool L69 3BX, UK.hirsch@liverpool.ac.uk)

  • K.J. Bowers

    (Urban Research and Policy Evaluation Regional Research Laboratory, Department of Civic Design, University of Liverpool, P. O. Box 147, Liverpool L69 3BX, UK. KJ.Bowers@liverpool.ac.uk)

Abstract

This paper investigates the hypothesis that the level of crime in disadvantaged areas will be influenced by their levels of social cohesion. This issue is examined using two methods for delineating areas of disadvantage (geodemographic classifications and the British government's official deprivation measure, the Index of Local Conditions) and two independent components of social cohesion, one defines the level of 'social control' in an area and the other identifies 'ethnic heterogeneity'. The results suggest that levels of crime are significantly lower than expected in disadvantaged areas with high levels of social cohesion and vice versa. A complementary analysis of Homewatch schemes revealed that such schemes lead to reduced levels of burglary in affluent areas, but appear to have the opposite effect to that desired in more disadvantaged areas.

Suggested Citation

  • A. Hirschfield & K.J. Bowers, 1997. "The Effect of Social Cohesion on Levels of Recorded Crime in Disadvantaged Areas," Urban Studies, Urban Studies Journal Limited, vol. 34(8), pages 1275-1295, July.
  • Handle: RePEc:sae:urbstu:v:34:y:1997:i:8:p:1275-1295
    DOI: 10.1080/0042098975637
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    References listed on IDEAS

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    1. Klitgaard, Robert & Fedderke, Johannes, 1995. "Social integration and disintegration: An exploratory analysis of cross-country data," World Development, Elsevier, vol. 23(3), pages 357-369, March.
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    Cited by:

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    2. Dongping Long & Lin Liu & Jiaxin Feng & Suhong Zhou & Fengrui Jing, 2018. "Assessing the Influence of Prior on Subsequent Street Robbery Location Choices: A Case Study in ZG City, China," Sustainability, MDPI, vol. 10(6), pages 1-16, May.
    3. Haining, Robert & Law, Jane & Griffith, Daniel, 2009. "Modelling small area counts in the presence of overdispersion and spatial autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2923-2937, June.
    4. Domínguez, Magdalena & Montolio, Daniel, 2021. "Bolstering community ties as a mean of reducing crime," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 916-945.
    5. Robert Haining & Jane Law, 2007. "Combining police perceptions with police records of serious crime areas: a modelling approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 1019-1034, October.
    6. Gorr, Wilpen & Olligschlaeger, Andreas & Thompson, Yvonne, 2003. "Short-term forecasting of crime," International Journal of Forecasting, Elsevier, vol. 19(4), pages 579-594.
    7. Debertin, David L. & Goetz, Stephan J., 2013. "Social Capital Formation in Rural, Urban and Suburban Communities," Staff Papers 159102, University of Kentucky, Department of Agricultural Economics.
    8. Fernando Rajulton & Zenaida Ravanera & Roderic Beaujot, 2007. "Measuring Social Cohesion: An Experiment using the Canadian National Survey of Giving, Volunteering, and Participating," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 80(3), pages 461-492, February.
    9. Quick, Matthew & Li, Guangquan & Brunton-Smith, Ian, 2018. "Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 22-32.
    10. Jane Law & Matthew Quick, 2013. "Exploring links between juvenile offenders and social disorganization at a large map scale: a Bayesian spatial modeling approach," Journal of Geographical Systems, Springer, vol. 15(1), pages 89-113, January.
    11. Vania Ceccato & Robert Haining & Paola Signoretta, 2001. "Exploring offence statistics in stockholm city using spatial analysis tools," ERSA conference papers ersa01p97, European Regional Science Association.

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