Evidence map›Paper›PMID 41585595›Full record

ArticleComputational urban science2026

Exploring contemporary public perceptions of historical redlining practices in the United States.

Yujian Lu, Xi Gong, Guiming Zhang, Christopher P Brown, Yolanda C Lin, Yan Lin

Abstract read
In one paragraph

Article in Computational urban science, 2026. 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.

Yujian LuDepartment of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM 87131 USA.
Xi GongDepartment of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802 USA.ORCID 0000-0001-7899-6213
Guiming ZhangDepartment of Geography & the Environment, University of Denver, Denver, CO 80210 USA.
Christopher P BrownDepartment of Geography & Environmental Studies, New Mexico State University, Las Cruces, NM 88011 USA.
Yolanda C LinDepartment of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM 87131 USA.
Yan LinDepartment of Geography, The Pennsylvania State University, University Park, PA 16802 USA.

Funding

WOMEN'S CANCERS RESEARCH PROGRAMP30CA118100 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Yolanda Sanchez · 2005 to 2026
$57.1M
UNM Metals Exposure and Toxicity Assessment on tribal Lands in the Southwest (METALS) Superfund Research ProgramP42ES025589 · NIEHS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI HUDSON, LAURIE G · 2017 to 2025
$16.4M
The Population Research Institute: Development CoreP2CHD041025 · NICHD · PENNSYLVANIA STATE UNIVERSITY, THE · PI Sarah Damaske · 2016 to 2026
$9.0M
Role of open dumping and open burning of solid waste in the generation of microplastics and products of incomplete combustion on tribal landsP50MD015706 · NIMHD · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI MACKENZIE, DEBRA · 2020 to 2024
$6.8M
Pilot Project CoreP30ES032755 · NIEHS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI FENG, CHANGJIAN (JIM) · 2022 to 2025
$5.2M
UNM Climate Change and Health for the Alliance and Novelty of Geospatial and Exposure Science (CHANGES) CenterP20NR021824 · NINR · UNIVERSITY OF NEW MEXICO · PI CERRATO, JOSE MANUEL · 2024 to 2024
$3.8M
NCI NIH HHS P30 CA118100NICHD NIH HHS P2C HD041025NIEHS NIH HHS P30 ES032755NIEHS NIH HHS P42 ES025589NIMHD NIH HHS P50 MD015706NINR NIH HHS P20 NR021824
6 · The paper itself

Abstract

Redlining is a discriminatory practice of systematically denying loans or mortgages to residents in specific neighborhoods based on racial or ethnical composition. In current literature research, there is a lack of understanding of the public perceptions of impacts of historical redlining practices at large geographic scales. Although some social groups and organizations conducted surveys or interviews to obtain public perceptions of it on small groups of people in certain areas, our knowledge of the impacts of redlining is limited and may reflect bias. This study used geotagged tweets from 2011 to 2023 to investigate public perceptions of redlining practices in U.S. counties. Multiscale geographically weighted regression (MGWR) was performed to explore both spatial heterogeneity and varying scales of associations between percentage of redlining-related geotagged tweets with negative sentiment and potential explanatory shaping factors in U.S. counties. Counties with a higher average household size, a higher percentage of people aged 45+, a lower homeownership rate, and a higher mobile home percentage have a significant association nationwide with more negative-sentiment expression in redlining-related tweets. However, counties with a lower insurance coverage are less likely to express negative sentiment in redlining-related tweets in some eastern U.S. counties, indicating a local significant association. The findings help people better understand the relationship between public perceptions of redlining practices and potential shaping factors. This study's methodology can also be applied to investigate public perspectives or perceptions on other controversial social topics.

Indexed as

GISMultiscale geographically weighted regression (MGWR)Public perceptionsRedliningSocial media

Identifiers

PMID41585595
PMCPMC12827292

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.