| Title |
Moving Toward Integration? Effects of Migration on Ethnoracial Segregation Across the Rural-Urban Continuum
|
|---|---|
| Published in |
Demography, June 2016
|
| DOI | 10.1007/s13524-016-0479-5 |
| Pubmed ID | |
| Authors |
Richelle L. Winkler, Kenneth M. Johnson |
| Abstract |
This study analyzes the impact of migration on ethnoracial segregation among U.S. counties. Using county-level net migration estimates by age, race, and Hispanic origin from 1990-2000 and 2000-2010, we estimate migration's impact on segregation by age and across space. Overall, migration served to integrate ethnoracial groups in both decades, whereas differences in natural population change (increase/decrease) would have increased segregation. Age differences, however, are stark. Net migration of the population under age 40 reduced segregation, while net migration of people over age 60 further segregated people. Migration up and down the rural-urban continuum (including suburbanization among people of color) did most to decrease segregation, while interregional migration had only a small impact. People of color tended to move toward more predominantly white counties and regions at all ages. Migration among white young adults (aged 20-39) also decreased segregation. Whites aged 40 and older, however, showed tendencies toward white flight. Moderate spatial variation suggests that segregation is diminishing the most in suburban and fringe areas of several metropolitan areas in the Northeast and Midwest, while parts of the South, Southwest, and Appalachia show little evidence of integration. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 57% |
| Panama | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 66 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 27% |
| Student > Doctoral Student | 8 | 12% |
| Professor > Associate Professor | 5 | 8% |
| Professor | 4 | 6% |
| Researcher | 4 | 6% |
| Other | 14 | 21% |
| Unknown | 13 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 36 | 55% |
| Economics, Econometrics and Finance | 7 | 11% |
| Business, Management and Accounting | 3 | 5% |
| Psychology | 1 | 2% |
| Environmental Science | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 16 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 78. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2017.
All research outputs
#465,414
of 22,876,619 outputs
Outputs from Demography
#122
of 1,858 outputs
Outputs of similar age
#10,256
of 343,019 outputs
Outputs of similar age from Demography
#2
of 19 outputs
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