Evidence map›Paper›PMID 41792127›Full record

ArticleNature communications2026

How common depictions of wealth distributions can bias people to underestimate inequality.

Jonathan E Bogard, Colin West, Craig R Fox

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Jonathan E BogardWashington University in St. Louis, St.Louis, MO, USA. bogard@wustl.edu.ORCID http://orcid.org/0000-0002-2700-7427
Colin WestUCLA, Anderson School of Management, Los Angeles, CA, USA.
Craig R FoxUCLA, Anderson School of Management, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0001-9057-112X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Economic inequality is a critical issue in elections and legislating, so having an informed electorate is vital to sensible policymaking. Unfortunately, misperceptions about the true extent of inequality abound. Here, we demonstrate that the most prevalent formats for representing economic distributions tend to dampen viewer impressions of inequality. We begin by showing that the most popular newspaper portrayals of inequality contain potentially biasing features. Next, in nine experiments (N = 3599 U.S. adults), we explore how these common representations of inequality evoke biased impressions and we test methods to mitigate these biases. Specifically, we document two biases in how people evaluate economic distributions. First, people are under-sensitive to differences in the size of identified population groups (e.g., top 1% vs. top 10%) such that their judgments become distorted by arbitrary ways in which a population is divided (partition dependence). Second, people's judgments under-weight information about intermediate groups relative to the most- and least-wealthy groups (middle neglect). We test ways to mitigate these biases and conclude by proposing presentation guidelines that promote more accurate impressions.

Indexed as

Socioeconomic FactorsAdultBiasFemaleHumansJudgmentMalePoliticsUnited States

Identifiers

PMID41792127
PMCPMC13125609

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.