Identity Captured by Law: Membership in Canada's Indigenous Peoples and Linguistic Minorities
Bibliographic record
Abstract
In Canada, indigenous peoples and official-language minorities benefit from certain rights that are not available to the rest of the population, but exactly who can claim membership in these groups remains a controversial issue. Protecting a group's culture and resources is often seen to be at odds with the freedom of individuals to claim membership in that group. In Identity Captured by Law, Sebastien Grammond explains how minority rights make identity legally relevant, providing a detailed account of struggles that have been fought concerning Indian status and admission to minority-language schools. Setting his analysis of the law in the wider interdisciplinary context of anthropology and political theory, Grammond assesses whether a group's membership rules are an accurate reflection of their ethnicity and are based on sound justifications of minority rights. He argues that membership rules do not violate equality rights if there is sufficient correspondence between the legal criteria that determine membership and the group's own cultural or relational conceptions of their ethnic identity. Comprehensive, interdisciplinary, and original in its comparison of indigenous people and linguistic minorities, Identity Captured by Law is an invaluable resource for legal and political scholars and students, as well as anyone interested in the controversies surrounding the legal recognition of identity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".