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Record W4417431309 · doi:10.1111/pops.70100

How leading climate movement advocates perceive collective gridlock in social change advocacy

2025· article· en· W4417431309 on OpenAlexaff
Janquel D. Acevedo, Ava Disney, Kelly S. Fielding, Catherine E. Amiot, Matthew J. Hornsey, Fathali M. Moghaddam, Emma F. Thomas, Stewart Sutherland, Susilo Wibisono, Winnifred R. Louis

Bibliographic record

VenuePolitical Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversité du Québec à Montréal
FundersAustralian Research Council
KeywordsGridlockCollective actionClimate changeSocial movementHostilityPolitical economy of climate change

Abstract

fetched live from OpenAlex

Abstract Despite mass mobilization efforts, most countries are failing to meet their internationally agreed 2030 goals to mitigate climate change, representing a failure of the climate movement to achieve their key aspirations. Most research on failure and collective action examines one‐off failures but does not address lasting failure. We conceptualize this ongoing failure as collective gridlock: times in social change advocacy where insufficient progress is caused by antagonistic intergroup stalemates, preventing groups from achieving shared goals and addressing joint problems. We used semi‐structured interviews with climate movement leaders ( N = 28) to explore collective gridlock and the processes that may be associated with it. Most advocates believed they were in gridlock as they perceived insufficient progress toward their movement's goals. Evidence for the proposed processes of attrition, group norms of purity and intransigence, moral conviction, hostility toward the outgroup, radicalization, and perceived counter‐mobilization emerged in the interviews. Contrary to expectations, climate movement leaders also reported a need to build coalitions and compromise, and they also discussed negative well‐being as an outcome of collective gridlock. The current study contributes to our understanding of persistent failure in the climate movement and its implications for social change advocacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.796
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.447
GPT teacher head0.531
Teacher spread0.083 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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