Mapping Attitudes Towards the Police at Micro Places

Abstract

Objectives: We demonstrate the utility of mapping community satisfaction with the police at micro places using data from citizen surveys conducted in 2001, 2009 and 2014 in one city.

Methods: In each survey, respondents provided the nearest intersection to their address. Using that geocoded survey data, we use inverse distance weighting to map a smooth surface of satisfaction with police over the entire city. We use spatial and multi-level regression models to estimate the effect of local violent crimes on attitudes towards police, controlling for other individual and neighborhood level characteristics.

Results: We demonstrate that there are no systematic biases for respondents refusing to answer the nearest intersection question. We show that hot spots of dissatisfaction with police do not conform to census tract boundaries, but rather align closely with hot spots of crime. Models predicting satisfaction with police show that local counts of violent crime are a strong predictor of attitudes towards police, even above individual level predictors of race and age.

Conclusions: Asking survey respondents to provide the nearest intersection to where they live is a simple approach to mapping attitudes towards police at micro places. This both provides more specific locations police may target interventions, as well as a theoretically important influence (violent crimes nearby) that impact attitudes toward the police.

Keywords: Micro Places, Legitimacy, Satisfaction with Police, Attitudes, Mapping