Evidence map›Paper›PMID 42561024›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Implicit biases change more slowly in larger cities.

Andrew J Stier

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 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

1 author.

Andrew J StierThe Santa Fe Institute, Santa Fe, NM 87501.ORCID 0000-0002-2863-5978

Funding

National Science Foundation (NSF) BCS-2438783
6 · The paper itself

Abstract

Implicit biases remain a contributor to discrimination despite widespread endorsement of equality. Although there has been a large-scale reduction in sexuality, race, and skin tone biases in the past two decades, there is a current shortage of quantitative theories that describe how and why biases change. Here, I present a theory of implicit bias change, which focuses on changes in exposure due to cultural information and how the speed of these changes varies geographically. This model makes counterintuitive predictions when compared with previous findings, including 1) that biases change more slowly in larger cities and 2) that one-off interventions are less effective in larger cities. I confirm these predictions using 14 million tests of implicit biases from U.S. residents over 14 y and experimental data from 1,150 individuals. Documenting the typical timescales and patterns that govern implicit bias change is an important step toward designing interventions that can facilitate further reductions in biases and prevent biases from increasing.

Indexed as

Bias, ImplicitCitiesHumansUnited Statescitiescultural informationimplicit cognitionurban scaling

Identifiers

PMID42561024
PMCPMC13462937

What OpenQuestion holds

Textmetadata
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.