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Measuring Disorder: Observer Bias in Systematic Social Observations at Streets and Neighborhoods
Authors:E M Hoeben  W Steenbeek  L J R Pauwels
Institution:1.Institutions, Inequalities, and Life Course Program (IIL), Amsterdam Institute for Social Science Research (AISSR),University of Amsterdam,Amsterdam,The Netherlands;2.Netherlands Institute for the Study of Crime and Law Enforcement (NSCR),Amsterdam,The Netherlands;3.Department of Criminology, Penal Law and Social Law,Ghent University,Ghent,Belgium
Abstract:

Objectives

The present study focuses on Systematic Social Observation (SSO) as a method to investigate physical and social disorder at different units of analysis. The study contributes to the aggregation bias debate and to the ‘social science of ecological assessment’ in two ways: first, by presenting a new model that directly controls for observer bias in ecological constructs and second, by attempting to identify systematic sources of bias in SSO that affect the valid and reliable measurement of physical and social disorder at both street segments and neighborhoods.

Methods

Data on physical disorder (e.g., litter, cigarette butts) and social disorder (e.g., loitering adults) from 1422 street segments in 253 different neighborhoods in a conurbation of the greater The Hague area (the Netherlands) are analyzed using cross-classified multilevel models.

Results

Neighborhood differences in disorder are overestimated when scholars fail to recognize the cross-classified data structure of an SSO study that is due to allocation of street segments to observers and neighborhoods. Not correcting for observer bias and observational conditions underestimates the disorder–crime association at street segment/grid cell level, but overestimates this association at the neighborhood level.

Conclusion

Findings indicate that SSO can be used for measuring disorder at both street segment level and neighborhood level. Future studies should pay attention to observer bias prior to their data collection by selecting a minimum number of observers, offering extensive training, and collecting information on the urban background of the observers.
Keywords:
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