Segregation;
social frontiers;
neighbourhood boundaries;
social cohesion;
crime;
neighbourhood conflict;
INTERGROUP CONTACT;
BAYESIAN-INFERENCE;
SOCIAL TECTONICS;
CRIME;
MODELS;
DIVERSITY;
PREJUDICE;
COHESION;
LONDON;
RATES;
D O I:
10.1111/tesg.12316
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
'Social frontiers' - places of sharp difference in social/ethnic characteristics between neighbouring communities - have largely been overlooked in quantitative research. Advancing this nascent field first requires a way of identifying social frontiers in a robust way. Such frontiers may be 'open' - an area may contrast sharply with a neighbourhood in one direction, but blend smoothly into adjacent neighbourhoods in other directions. This poses some formidable methodological challenges, particularly when computing inference for the existence of a social frontier, an important goal if one is to distinguish true frontiers from random variation. We develop a new approach using Bayesian spatial statistical methods that permit asymmetries in spatial effects and allow for spatial autocorrelation in the data. We illustrate our method using data on Sheffield and find clear evidence of 'open' frontiers. Permutations tests and Poisson regressions with fixed effects reveal compelling evidence that social frontiers are associated with higher rates of crime.
机构:
Univ Vita Salute San Raffaele, Fac Filosofia, Via Olgettina,58, I-20132 Milan, ItalyUniv Vita Salute San Raffaele, Fac Filosofia, Via Olgettina,58, I-20132 Milan, Italy