Bibliographic record
Abstract
Quebec recently proposed legislation (Bill 94) that would require all individuals to reveal their face when seeking a government service. The proposed legislation particularly targets Muslim women who don the niqab. Underlying the present debate is an artificial dichotomy – a tension between a society’s interest in defining a common sense of citizenship and minority claims that seem inconsistent with the will of the majority. A Charter challenge – even if successful – would not fully address this underlying tension. In this paper, I argue that the heart of the present controversy relates to the need for a clear conception of Quebec identity. By considering the historical, social, ethnic, geographic and intrinsic significance of the French language, I argue that the French language, not secularism, is the key element of Quebec identity and facilitates a common sense of citizenship in Quebec. If a minority claim is capable of fitting within this conception of Quebec identity, then it poses no threat to Quebec citizenship, and thus, there should be no reason to exclude the claim – in this case the claim to wear the niqab when seeking a government service – from Quebec society.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".