Evidence map›Paper›PMID 38178923›Full record

ArticleHousing policy debate2023

Segmented information, segregated outcomes: Housing affordability and neighborhood representation on a voucher-focused online housing platform and three mainstream alternatives.

Chris Hess, Rebecca J Walter, Ian Kennedy, Arthur Acolin, Alex Ramiller, Kyle Crowder

Abstract read
In one paragraph

Article in Housing policy debate, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Chris HessKennesaw State University.
Rebecca J WalterUniversity of Washington.
Ian KennedyRice University.
Arthur AcolinUniversity of Washington.
Alex RamillerUniversity of California-Berkeley.
Kyle CrowderUniversity of Washington.

Funding

Scientific/Technical CoreP2CHD042828 · NICHD · UNIVERSITY OF WASHINGTON · PI SARA R. CURRAN · 2017 to 2026
$6.3M
T32 Data Science and Demography Training BSSRT32HD101442 · NICHD · UNIVERSITY OF WASHINGTON · PI Zack W Almquist, SARA R. CURRAN · 2020 to 2026
$2.0M
NICHD NIH HHS P2C HD042828NICHD NIH HHS T32 HD101442
6 · The paper itself

Abstract

Online platforms have become an integral component of the housing search process in the United States and other developed contexts, but recent studies have demonstrated that these platforms offer uneven representation of different neighborhoods. In this study, we use listings covering the largest 50 U.S. metropolitan areas to assess how GoSection8, a platform uniquely focused on affordable housing and voucher-assisted households, compares with "mainstream" alternatives of Craigslist, Apartments.com and Zillow. Through descriptive and regression analyses of the housing and neighborhoods represented on these websites and a new way of measuring the distribution of rental housing opportunities, we advance a multisource perspective on the role of online information exchanges in housing search processes. Specifically, we find that GoSection8 and mainstream alternatives capture spatially-segmented information about housing markets, with GoSection8 ads representing units that are more affordable but also more constrained to higher-poverty neighborhoods where assisted households are already concentrated. The findings suggest that disadvantaged households are potentially funneled toward high-poverty, isolated neighborhoods by the operation of stratified information systems available for online housing searches.

Indexed as

housing platformshousing policyhousing searchneighborhood stratificationresidential segregation

Identifiers

PMID38178923
PMCPMC10766102

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.