A lack of collective efficacy in neighborhood is associated with social and physical disorder and related anti-social actions. It is less clear, however, whether collective efficacy in neighborhood also enhances prosocial, other-regarding behavior. We studied this association by employing the Lost Letter Technique in a large-scale field experiment. Our data stem from 1,240 letters dropped in a representative sample of 110 Dutch neighborhoods, combined with neighborhood data based on a survey of residents (SSND2, n=996) and information provided by Statistics Netherlands. We distinguish between two conditions (1) location of the lost letter, that is, behind a car's windshield wiper on the sidewalk; and (2) type of addressee, that is, a Dutch name or a Turkish/Moroccan name. When we decompose collective efficacy into social cohesion and shared expectations of social control, we find that shared control expectations clearly matter for the rate of posted letters. Social cohesion has no effect. Furthermore, a high percentage of non-Western residents, high residential mobility, and a relatively low local income level are negatively related to the rate of posted letters.
This paper considers the quantitative assessment of ecological settings such as neighborhoods and schools. Available administrative data typically provide useful but limited information on such settings. We demonstrate how more complete information can be reliably obtained from surveys and observational studies. Survey-based assessments are constructed by aggregating over multiple item responses of multiple informants within each setting. Item and rater inconsistency produce uncertainty about the setting being assessed, with definite implications for research design. Observation-based assessments also have a multilevel error structure. The paper describes measures constructed from interviews, direct observations, and videotapes of Chicago neighborhoods and illustrates an “ecometric” analysis—a study of bias and random error in neighborhood assessments. Using the observation data as an illustrative example, we present a three-level hierarchical statistical model that identifies sources of error in aggregating across items within face-blocks and in aggregating across face-blocks to larger geographic units such as census tracts. Convergent and divergent validity are evaluated by studying associations between the observational measures and theoretically related measures obtained from the U.S. Census, and a citywide survey of neighborhood residents.
