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METROPOLITAN, URBAN, AND RURAL COMMUTING AREAS: TOWARD A BETTER DEPICTION OF THE UNITED STATES SETTLEMENT SYSTEM
Abstract
Discontent with the current definition of metropolitan areas and the lack of differentiation within nonmetropolitan territory provided the incentive for the research presented here. Census tracts rather than counties were used as the building blocks for assignment of tracts, not just to metropolitan areas, but also to larger towns (10,000 to 49,999) and to smaller urban places (2,500 to 9,999). The analysis used 1990 census-defined urbanized areas and tract-to-tract commuter flows. Results include a modest shift of population from metropolitan to nonmetropolitan, as well as a significant reduction in the areal size of metropolitan areas, disaggregation of many areas, and frequent reconfiguration to a more realistic settlement form. [Key words: metropolitan, urban-rural, commuting.]
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Cited by
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Hart, L. G., Larson, E. H., & Lishner, D. M. (2005) · American Journal of Public Health · doi:10.2105/ajph.2004.042432 · Cited by 964
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Metadata
- Authors
- Morrill, R., Cromartie, J., & Hart, G.
- Venue
- Urban Geography
- Publisher
- Informa UK Limited
- Published
- 1999-11
- Volume
- 20
- Issue
- 8
- Pages
- 727-748
- ISSN
- 0272-3638 (ISSN-L)
- 1938-2847
- OpenAlex
- W2063743138
- Cited by
- 354
- References
- 0
- FWCI
- 5.23
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: METROPOLITAN, URBAN, AND RURAL COMMUTING AREAS: TOWARD A BETTER DEPICTION OF THE UNITED STATES SETTLEMENT SYSTEM. https://app.cochat.ai/papers/10.2747/0272-3638.20.8.727
- The paper
- Morrill, R., Cromartie, J., & Hart, G. (1999). METROPOLITAN, URBAN, AND RURAL COMMUTING AREAS: TOWARD A BETTER DEPICTION OF THE UNITED STATES SETTLEMENT SYSTEM. Urban Geography. https://doi.org/10.2747/0272-3638.20.8.727
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
