Effects of political identity activation and inaccurate metaperceptions on attitudes toward wolves

Polarization between groups can undermine durable conservation outcomes. Activating group identities (i.e., an individual's sense of self derived from membership in a group) can exacerbate differences, especially when people hold inaccurate perceptions of their peers and rivals. In conservation contexts, the dynamism of identity and its varying influence on attitudes and outcomes is underexplored. We conducted 2 randomly controlled experiments among residents of U.S. states with wolves (n = 2296) to investigate these dynamics in a conservation context. Results from Study 1 showed group identity activation (political identity, specifically) and inaccurate metaperceptions distorted attitudes toward gray wolves (Canis lupus) and deepened differences between people. Results from Study 2 showed a simple in-group metaperception correction attenuated this effect by reducing assumptions of polarization and limiting the effects of identity fusion. These results demonstrate the opportunity for conservation policy makers and practitioners to avoid activating identities assumed to be associated with conflict and instead counter false narratives that exaggerate division. Correcting inaccurate metaperceptions and designing identity-informed communication strategies may help bolster support for conservation goals and reduce avoidable conflict.

Authors

Institutions

Publication Details

Journal
Conservation Biology
Published
2026-01-06
DOI
https://doi.org/10.1111/cobi.70212
Citations
1
Primary Topic
Social and Intergroup Psychology
Type
article
Field-Weighted Citation Impact
55.57

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of political identity activation and inaccurate metaperceptions on attitudes toward wolves

Alexander L. Metcalf, Justin W. Angle
1 citations
Conservation Biology
Social and Intergroup Psychology
55.57
article

Effects of political identity activation and inaccurate metaperceptions on attitudes toward wolves

Alexander L. Metcalf, Justin W. Angle
article en
1 citations

Abstract

Polarization between groups can undermine durable conservation outcomes. Activating group identities (i.e., an individual's sense of self derived from membership in a group) can exacerbate differences, especially when people hold inaccurate perceptions of their peers and rivals. In conservation contexts, the dynamism of identity and its varying influence on attitudes and outcomes is underexplored. We conducted 2 randomly controlled experiments among residents of U.S. states with wolves (n = 2296) to investigate these dynamics in a conservation context. Results from Study 1 showed group identity activation (political identity, specifically) and inaccurate metaperceptions distorted attitudes toward gray wolves (Canis lupus) and deepened differences between people. Results from Study 2 showed a simple in-group metaperception correction attenuated this effect by reducing assumptions of polarization and limiting the effects of identity fusion. These results demonstrate the opportunity for conservation policy makers and practitioners to avoid activating identities assumed to be associated with conflict and instead counter false narratives that exaggerate division. Correcting inaccurate metaperceptions and designing identity-informed communication strategies may help bolster support for conservation goals and reduce avoidable conflict.

Conservation Biology
University of Montana (US)
University of Montana
Life in Land
Openalex Percentile: Top 1%
Social and Intergroup Psychology
55.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.