Evidence map›Paper›PMID 36864137›Full record

ArticleNature human behaviour2023

Partisans' receptivity to persuasive messaging is undiminished by countervailing party leader cues.

Ben M Tappin, Adam J Berinsky, David G Rand

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Scaling language model size yields diminishing returns for single-message political persuasion.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  11. Article
  12. Persuading partisans.Nature human behaviour · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Ben M TappinDepartment of Political Science, Massachusetts Institute of Technology, Cambridge, MA, USA. benmtappin@gmail.com.ORCID http://orcid.org/0000-0002-3826-8016
Adam J BerinskyDepartment of Political Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
David G RandSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-8975-2783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is widely assumed that party identification and loyalty can distort partisans' information processing, diminishing their receptivity to counter-partisan arguments and evidence. Here we empirically evaluate this assumption. We test whether American partisans' receptivity to arguments and evidence is diminished by countervailing cues from in-party leaders (Donald Trump or Joe Biden), using a survey experiment with 24 contemporary policy issues and 48 persuasive messages containing arguments and evidence (N = 4,531; 22,499 observations). We find that, while in-party leader cues influenced partisans' attitudes, often more strongly than the persuasive messages, there was no evidence that the cues meaningfully diminished partisans' receptivity to the messages-despite them directly contradicting the messages. Rather, persuasive messages and countervailing leader cues were integrated as independent pieces of information. These results generalized across policy issues, demographic subgroups and cue environments, and challenge existing assumptions about the extent to which party identification and loyalty distort partisans' information processing.

Indexed as

CognitionCuesDissent and DisputesHumansPersuasive CommunicationSurveys and QuestionnairesUnited States

Identifiers

PMID36864137

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.