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Record W4416093774 · doi:10.1017/rep.2025.10040

The Mobilizing Effects of Islamophobic Discrimination in Europe and North America

2025· article· en· W4416093774 on OpenAlexaboutno aff
Aubrey L. Westfall

Bibliographic record

VenueThe Journal of Race Ethnicity and Politics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsIslamophobiaPoliticsMainstreamPerceptionCitizenshipRacismDemocracyPrejudice (legal term)

Abstract

fetched live from OpenAlex

Abstract Discriminatory encounters are commonplace for Muslims living in the West. How do these experiences impact the political behaviors of Muslims within these societies? Scholars have examined the effects of Islamophobia on Muslims’ civic engagement and found mixed results. Some researchers argue that discrimination triggers demobilizing psychological processes, while others contend that discriminatory experiences motivate active citizenship as a corrective to injustice. Still others suggest that distinct experiences with discrimination mobilize differently. This article engages with original survey data from Canada, France, Germany, the UK, and the US to explore whether and how individual experiences with societal and political discrimination, and perceptions of group discrimination, influence Muslims’ political activities. It reveals that societal, political, and group discrimination are associated with greater breadth of mainstream political activities, while experiences with political discrimination and perceptions of group discrimination correlate with protest activities. These results suggest that Muslims discern the specific nature of discriminatory experiences and respond accordingly through democratic means.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.013
GPT teacher head0.302
Teacher spread0.290 · 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 designQualitative
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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