What is Holding Back Full Feminist Solidarity with Muslim Women? The Epistemic Failures of White Liberal Feminism
Bibliographic record
Abstract
Despite the recent shift towards embracing anti-racism and intersectionality within the feminist movement in Quebec, Canada, support for Muslim women affected by secularism laws remains elusive. Our article seeks to understand what is still holding back a full feminist solidarity with Muslim women in Quebec by examining the limits of intersectional solidarity discourses from feminist groups officially positioning themselves in defence of Muslim women’s rights to wear religious symbols. We focus on the advocacy discourse against the Act Respecting the Laicity of the State (Law 21) led by the Fédération des femmes du Québec (FFQ), Quebec’s largest feminist coalition. We employ a theoretical framework combining feminist critical Muslim scholarship and critical epistemologies, which leads us to ask: How does the FFQ’s advocacy work against Law 21 mobilise an intersectional approach to defend Muslim women’s rights against nationalist and secular colonial narratives? What are the limits and blind spots of this advocacy work? Our analysis shows that despite FFQ’s declared political support for Muslim women’s rights and attempts to incorporate religion within an intersectional framework of domination, the organisation still failed to dismantle the deep-rooted idea of an inherent incompatibility between feminism and Islam and to consider Muslim women within its ranks as full feminist epistemic subjects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.064 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".