Abstract
Up till now, a systematic test of the impact of theoretically relevant locality characteristics on social cohesion has been lacking in Europe. In this paper, we investigated the impact of a wide array of characteristics of Dutch neighbourhoods and municipalities on contact frequency with one's neighbours, tolerance to neighbours from a different race, generalized social trust and volunteering. Based on the homophily proposition, we expected that ethnic and economic heterogeneity in Dutch localities negatively affect these indicators of social cohesion. We also expected that poor localities, localities with high crime rates and localities that suffer from high residential mobility rates offer their residents less favourable circumstances for social cohesion to arise. For our individual level data, we used the survey ‘Culturele Veranderingen 2004’, which contains 2949 individuals living in 503 neighbourhoods and 245 municipalities. Economic deprivation (at the neighbourhood level) is most consistently negatively related to social cohesion. We did not find a consistent negative impact of ethnic heterogeneity on social cohesion. We conclude that not all aspects of social cohesion are affected in the same way by neighbourhood and municipality characteristics and that the impact of these characteristics on social cohesion depends on residents’ income and educational level.
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Notes
More specifically, we are more confident to find a detrimental effect of (ethnic and economic) heterogeneity, poverty, crime and residential mobility within localities on social cohesion among the poor and low educated than among the rich and high educated.
These are singing/music, sports, hobby, political, interest, religious organizations, schools, neighbours/elderly/handicapped, action groups and local community organizations.
The Herfindahl Index is given by: HI=∑ i p i 2, where p i is the proportion of the respective distinguished ethnic group within the locale. The measure of ethnic heterogeneity is obtained by taking the complement of the HI: 1 – HI.
This operationalization causes an underestimation of the income inequality within neighbourhoods and municipalities and our tests regarding the impact of income inequality should be considered conservative. The definition of the Gini-coefficient as the mean of absolute differences between all pair of individuals is given by: , where y is the observed income, n the total individuals and y bar the mean income. We calculated the Gini-coefficient by the SPSS-script provided on Raynald's SPSS Tools website (http://www.spsstools.net/). As said before, instead of income data at the individual level we use information on the mean income level of the complete zip code to construct the Gini-coefficient. We weighted the complete zip codes by the number of residents.
We would like to thank L. Prins and his colleagues of the Dutch police force (Korps Landelijke Politiediensten, Dienst Nationale Recherce Informatie, Onderzoek en Analyse) for making these data available to us.
We applied hierarchical models to obtain correct standard errors of the contextual effects. Since our neighbourhoods are not randomly selected, the intra class correlations are not that informative. However, from Appendix C we learn that the variances at the higher levels are substantial. To a large extent this variance is due to composition effects.
Note that neither STATA nor R has a build in stepwise model selection procedure. We thank Rense Nieuwenhuis for the help during the estimation procedure in R. See http://www.rensenieuwenhuis.nl/ for the R script we used to come to our final models as presented in Table 2.
One plausible theoretical explanation that economic inequality is important at the country level but apparently not at lower contextual levels is that the effect of economic inequality at the country level is mainly driven by institutional fairness perceptions and not so much by the cultural dissimilarity that results from differences in economic resources. These perceptions of fairness may be forged mainly in national public spheres by political parties and the media and not in local environments such as neighbourhoods and municipalities.
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Tolsma, J., van der Meer, T. & Gesthuizen, M. The impact of neighbourhood and municipality characteristics on social cohesion in the Netherlands. Acta Polit 44, 286–313 (2009). https://doi.org/10.1057/ap.2009.6
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DOI: https://doi.org/10.1057/ap.2009.6