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Updated: May 7, 2026
12:27
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Identifying and Bounding Ethnic Neighborhoods
John R Logan1, Seth Spielman, Hongwei Xu
1Brown University.
Urban Geography
|September 17, 2013
Summary
This study introduces three new methods for identifying ethnic neighborhoods using 1880 Newark, NJ, resident data. No single method is best; the choice depends on the researcher
Area of Science:
- Urban Studies
- Historical Geography
- Computational Social Science
Background:
- Identifying ethnic neighborhoods is crucial for urban studies.
- Traditional methods often rely on arbitrary administrative units.
- Novel approaches are needed to define neighborhood boundaries based on population composition.
Purpose of the Study:
- To present and evaluate three novel methods for identifying ethnic neighborhoods.
- To utilize detailed historical residential data for neighborhood analysis.
- To explore the utility of street segments as the basic unit of analysis.
Main Methods:
- A variation of k-functions with cluster analysis for pattern detection.
- An energy minimization algorithm adapted from digital image processing.
- A Bayesian approach applied to spatial demographic data.
Main Results:
- All three methods produced roughly similar neighborhood maps.
- Methodological choices and investigator criteria significantly influence results.
- No single method emerged as universally superior.
Conclusions:
- Researchers should explore diverse methodological approaches for neighborhood identification.
- The optimal method for defining ethnic neighborhoods depends on conceptualization and empirical application.
- Continued innovation in spatial analysis techniques is encouraged.
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