Bibliographic record
Abstract
This article goes behind stereotypes of Muslim veiling to ask after the representational structure underlying these images. I examine the public debate leading to the 2004 French law banning conspicuous religious signs in schools and French colonial attitudes to veiling in Algeria, in conjunction with discourses on the veil that have arisen in other western contexts. My argument is that western perceptions and representations of veiled Muslim women are not simply about Muslim women themselves. Rather than representing Muslim women, these images fulfill a different function: they provide the negative mirror in which western constructions of identity and gender can be positively reflected. It is by means of the projection of gender oppression onto Islam, and its naturalization to the bodies of veiled women, that such mirroring takes place. This constitutes, I argue, a form of racialization. Drawing on the work of Fanon, Merleau-Ponty and Alcoff, I offer a phenomenological analysis of this racializing vision. What is at stake is a form of cultural racism that functions in the guise of anti-sexist and feminist liberatory discourse, at once posing a dilemma to feminists and concealing its racializing logic.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.045 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".