From Census Tracts to Local Environments: An Egocentric Approach to Neighborhood Racial Change.

Area of Science:

• Urban Studies
• Sociology
• Geographic Information Systems (GIS)

Background:

• Traditional neighborhood studies use census tracts, which may not accurately reflect residents' experiences or the scale of neighborhood dynamics.
• Census tracts can be insensitive to proximity effects and residents' perceptions of their local environment.

Purpose of the Study:

• To propose and validate an egocentric neighborhood approach for analyzing racial change.
• To examine neighborhood racial diversity and composition using a more spatially precise and experience-based method.

Main Methods:

• Developed an egocentric neighborhood analysis using GIS and census block data.
• Redistributed race-specific population counts into 50m x 50m cells.
• Calculated proximity-adjusted racial composition for nested local environments of varying sizes.

Main Results:

• Documented increasing exposure to neighborhood racial diversity from 1990-2000 across 40 metropolitan areas.
• Found that the magnitude of diversity exposure changes varied by local environment size and racial group.
• Demonstrated that changes in diversity exposure are influenced by the overall diversity of the metropolitan area.

Conclusions:

• Egocentric neighborhoods offer a more nuanced understanding of neighborhood racial change than census tracts.
• The spatial scale of analysis significantly impacts findings on diversity exposure.
• Individual experiences of neighborhood racial composition are heterogeneous and depend on multiple factors.