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Does Information Change Attitudes Toward Immigrants?
Open accessAbstract
Strategies aimed at reducing negative attitudes toward immigrants are at the core of integration policies. A large literature shows that misperceptions about the size and characteristics of immigrants are common. A few studies implemented interventions to correct innumeracy regarding the size of the immigrant population, but they did not detect any effects on attitudes. We study whether providing information not only about the size but also about the characteristics of the immigrant population can have stronger effects. We conduct two online experiments with samples from the United States, providing one-half of the participants with five statistics about immigration. This information bundle improves people’s attitudes toward current legal immigrants. Most effects are driven by Republicans and other groups with more negative initial attitudes toward immigrants. In our second experiment, we show that treatment effects persist one month later. Finally, we analyze a large cross-country survey experiment to provide external validity to the finding that information about the size of the foreign-born population is not enough to change policy views. We conclude that people with negative views on immigration before the intervention can become more supportive of immigration if their misperceptions about the characteristics of the foreign-born population are corrected.
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“A study that compared different information treatments found that Republicans raised their support for legal immigration only when they were informed about characteristics of the immigrant population and not only about its size (Grigorieff et al., 2020).”
From Factual belief polarization between Democrats and Republicans: source or epiphenomenon of ideological and affective polarization? (2024) · cites this paper as Grigorieff et al., 2020
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Metadata
- Authors
- Grigorieff, A., Roth, C., & Ubfal, D.
- Affiliations
- University of Oxford (GB)
- University of Warwick (GB)
- Abdul Latif Jameel Poverty Action Lab (US)
- Corresponding author
- Grigorieff, Alexis
- Roth, Christopher
- Ubfal, Diego
- Venue
- Demography
- Publisher
- Duke University Press
- Published
- 2020-06-01
- Volume
- 57
- Issue
- 3
- Pages
- 1117-1143
- ISSN
- 0070-3370 (ISSN-L)
- 1533-7790
- OpenAlex
- W3036844501
- Cited by
- 254
- References
- 57
- Citations by year
- 2026: 36 · 2025: 39 · 2024: 60 · 2023: 36 · 2022: 37 · 2021: 30 · 2020: 9
- FWCI
- 39.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Demography (publishedVersion)
- PubMed (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Archivio istituzionale della Ricerca - Bocconi (submittedVersion)
- Funders
- University of Oxford
- European Commission (608109)
- Università Bocconi
- Uppsala Universitet
- Economic and Social Research Council ([SSD/2/2/16])
- Topics
- Social Sciences › Sociology and Political Science › Migration, Refugees, and Integration
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Sociology and Political Science › Migration and Labor Dynamics
- Keywords
- attitudes toward immigrants, immigration policy, information interventions, migrant characteristics, immigrant population size, partisanship, Republican voters, treatment persistence, public opinion change, integration policy
- MeSH terms
- Adult, Attitude, Emigration and Immigration, Female, Humans, Male, Politics, Socioeconomic Factors, United States, Knowledge, Policy
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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