Evidence map›Paper›PMID 32935300›Full record

ArticleDemography2020

Income Segregation: Up or Down, and for Whom?

John R Logan, Andrew Foster, Hongwei Xu, Wenquan Zhang

Abstract read
In one paragraph

Article in Demography, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

John R LoganDepartment of Sociology, Brown University, Box 1916, Providence, RI, 02912, USA. john_logan@brown.edu.
Andrew FosterDepartment of Economics, Brown University, Providence, RI, 02912, USA.
Hongwei XuDepartment of Sociology, Queens College, CUNY, Queens, NY, 11367-1597, USA.
Wenquan ZhangDepartment of Sociology, University of Wisconsin-Whitewater, Whitewater, WI, 53190-1790, USA.

Funding

Science/Technical CoreP2CHD041020 · NICHD · BROWN UNIVERSITY · PI ZHENCHAO QIAN · 2016 to 2026
$7.6M
Investigating and Extending Bayesian Methods for Small Area EstimationR21HD078762 · NICHD · BROWN UNIVERSITY · PI LOGAN, JOHN R · 2014 to 2015
$442k
NICHD NIH HHS P2C HD041020NICHD NIH HHS R21 HD078762
6 · The paper itself

Abstract

Reports of rising income segregation in the United States have been brought into question by the observation that post-2000 estimates are upwardly biased because of a reduction in the sample sizes on which they are based. Recent studies have offered estimates of this sample-count bias using public data. We show here that there are two substantial sources of systematic bias in estimating segregation levels: bias associated with sample size and bias associated with using weighted sample data. We rely on new correction methods using the original census sample data for individual households to provide more accurate estimates. Family income segregation rose markedly in the 1980s but only selectively after 1990. For some categories of families, segregation declined after 1990. There has been an upward trend for families with children but not specifically for families with children in the upper or lower 10% of the income distribution. Separate analyses by race/ethnicity show that income segregation was not generally higher among Blacks and Hispanics than among White families, and evidence of income segregation trends for these separate groups is mixed. Income segregation increased for all three racial groups for families with children, particularly for Hispanics (but not Whites or Blacks) in the upper 10% of the income distribution. Trends vary for specific combinations of race/ethnicity, presence of children, and location in the income distribution, offering new challenges for understanding the underlying processes of change.

Indexed as

Family CharacteristicsBiasHumansIncomeRacial GroupsResearch DesignSocial SegregationUnited StatesIncome segregationMeasurement biasNeighborhoodsSampling bias

Identifiers

PMID32935300
PMCPMC7606787

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.