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Exploring the Goodhart thesis at a local scale: neighbourhood social heterogeneity and perceptions of quality of life in the British Crime Survey John.

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Presentation on theme: "Exploring the Goodhart thesis at a local scale: neighbourhood social heterogeneity and perceptions of quality of life in the British Crime Survey John."— Presentation transcript:

1 Exploring the Goodhart thesis at a local scale: neighbourhood social heterogeneity and perceptions of quality of life in the British Crime Survey John Mohan (University of Southampton) Liz Twigg (University of Portsmouth) Joanna Taylor (University of Portsmouth)

2 Diversity not disadvantage? “There is evidence that the more diverse an area is in racial terms, the less likely its residents are to feel that they trust each other. This is an important argument and it is important that we examine it” (David Blunkett, 2004)  David Goodhart: “one of the central dilemmas of political life in developed societies: sharing and solidarity can conflict with diversity”  Alesina and La Ferrara: heterogeneity reduces civic engagement and social capital: “natural aversion to heterogeneity”  Putnam – 41 communities in USA – diversity associated with reduction in social capital

3 British studies: disadvantage not diversity?  Ford: relationship between local ethnic diversity and support for welfare policies. Found no relationship between diversity and attitudes to welfare.  Letki: no independent effect for diversity on dimensions of social capital and trust; socioeconomic status more influential.  Pennant: no statistically significant relationship between diversity and civic participation or volunteering.  Heath and Laurence: crime and disadvantage more significant as predictors of cohesion than ethnicity or heterogeneity

4 Key research questions Are there associations between ethnic neighbourhood heterogeneity and three dimensions of life satisfaction, namely: (1) Perceptions of social disorganisation (2) People’s use of public space (3) Perceptions of social cohesion

5 Measuring heterogeneity  Area typology (shares of different ethnic groups) – Heath and Laurence  Indicators of degree of mixing (e.g. Theil, Herfindahl)  Indicators of isolation – e.g. probability that someone from a particular ethnic group meets one of their own group

6 The British Crime Survey (BCS)  Stratified and clustered random sample of adults living in private households about their experiences of crime in the previous 12 months  First sweep 1982 – continuous since 2001/02  Most recent sweep 2006/07 – sample size c47,000, response rate 75%  Primarily designed to capture ‘the dark figure of crime’  Also asks many questions on people’s perceptions of their neighbourhood social environment  Many studies employing bivariate analysis, some logistic regression but very few taking advantage of the clustered design for multi-level modelling

7 (1) Perceptions of social disorganisation How much of a problem is… …abandoned or burnt-out cars …noisy neighbours or loud parties …people being drunk or rowdy in public places …people using or dealing drugs …teenagers hanging around on the street …rubbish or litter lying around …vandalism, graffiti and other deliberate damage to property

8 (1) Perceptions of social disorganisation How much of a problem is… …abandoned or burnt-out cars …noisy neighbours or loud parties …people being drunk or rowdy in public places …people using or dealing drugs …teenagers hanging around on the street …rubbish or litter lying around …vandalism, graffiti and other deliberate damage to property 3=very big problem 2=fairly big problem 1=not very big problem 0=not a problem at all Σ >10 defined as ‘high levels of perceived ASB’

9 (2) People’s use of public space How safe do you feel walking alone [in this area] after dark? How often do you usually walk alone [in this area] after dark? (3) Perceptions of social cohesion This is a close-knit community People in this neighbourhood are willing to help their neighbours This is a place where people from different backgrounds get on well together

10 Independent variables from the BCS  Socio-demographic information  Individual  Household  Attitudinal data such as newspaper readership  Experiences of victimisation  Interviewers’ independent assessments of the area  Geodemographic classifications such as ACORN

11 Adding value Independent variables from other sources In conjunction with the Home Office trialling attaching Lower Level Super Output Areas to the 2006/07 sweep of the BCS Attach Census data Calculate measures of heterogeneity Attach Index of Multiple Deprivation – e.g., crime domain Hierarchical dataset Multilevel modelling

12 Analytical strategy Key questions:- 1.Do attitudes vary between places after allowing for individual and area characteristics (but not measures of heterogeneity)? 2.Does this pattern alter when we add in measures of neighbourhood heterogeneity? 3.Is the impact of ethnic heterogeneity the same for all types of place (by region and typology) 4.Are there interactions between individual characteristics (e.g. individual ethnicity) and ecological measures of heterogeneity

13 Modelling strategy  Data are clustered (hierarchical in nature)  People, nested within Primary Sampling Units (PSUs) within Police Force Areas  Simultaneous modelling of individual and area characteristics  Appropriate to use multilevel approaches  Dependent variables will usually be binary outcome  Multilevel logistic regression models (logits and Odds Ratios, CIs)

14 Multilevel approaches  Allow us to identify the spatial level at which variation is occurring (individual, small or large area)  How is the variation apportioned across these geographies?  How much of this variation is being explained by individual characteristics and area level variables (including neighbourhood heterogeneity)  Importantly we can explore ‘cross level interactions’ (e.g. individual ethnicity * neighbourhood heterogeneity)

15 Estimating and Assessing Models  Assess significance of fixed and random elements of the models  Also use MCMC methods on final models  Estimate Pseudo R 2 (including % correct predictions) - help us gauge relative importance of individual and area level variables

16 Potential difficulties  Attaching census data (and hence measures of heterogeneity) at LSOA  ‘Neighbourhood’ equates to LSOA or PSU  LSOA not part of the clustered design of BCS  Mismatch of PSU/LSOA coterminosity  Not yet sure of the extent of this problem  Cross-classified model?

17 Exploring the Goodhart thesis at a local scale: neighbourhood social heterogeneity and perceptions of quality of life in the British Crime Survey Any questions?


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