Bibliographic record
Abstract
Islamic veiling has attracted a remarkable degree of international and domestic attention in the current political climate. While an increasing number of countries have enacted legislation to prohibit Muslim women from wearing Islamic veils, in some countries Muslim women are coerced into wearing traditional religious dress. Forced veiling is a crucial human rights issue, yet it has not been fully explored in existing legal literature. This study analyses forced unveiling and forced veiling, two completely different stories, simultaneously and with equal importance by centring on the concept of ‘personal autonomy’. It examines the implications of forced veiling on Muslim women’s right to respect for private life and right to freedom of religion. In the popular and political debates, three justifications are commonly invoked to justify bans on Islamic veils: social cohesion; public safety and security; and, gender equality. Through the viewpoint of John Stuart Mill’s harm principle, this research examines whether a State can legitimately regulate the wearing of Islamic veils on these grounds. This is therefore unique research as it is the first study of this kind and thus, demonstrates an original contribution to knowledge. This study explores and critically analyses the divergent approaches the European Court of Human Rights (hereinafter “the ECtHR”) and the United Nations (hereinafter “the UN”) have taken concerning legal bans on Islamic veils. The comparative study reveals that the ECtHR has given weak protection to the religious freedom of Muslim women who want to manifest their religion through the wearing of Islamic veils. Therefore, this thesis offers a systematic analysis as to what lessons the ECtHR can take from the UN to give effective protection to Muslim women’s religious freedom, and how the ECtHR can strengthen its proportionality analysis to determine whether a legal ban on wearing the Islamic veil is justified.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.042 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".