Identity and Federalism: Understanding the Implications of Daniels v. Canada
Bibliographic record
Abstract
“As the curtain opens wider and wider on the history of Canada’s relationship with its Indigenous peoples, inequities are increasingly revealed and remedies urgently sought” … “This case represents another chapter in the pursuit of reconciliation and redress in that relationship”. With these words Justice Abella set the tone of Daniels v. Canada (Indian Affairs and Northern Development) (“Daniels”); a decision that restates settled law, reframes core elements of Indigenous identity, and contributes to the recent resetting of the framework for how the federal and provincial governments approach reconciliation with Indigenous peoples. On its face, Daniels is not so much new law, but rather a restatement of the law which raises more questions requiring further judicial guidance. The Court declined to make two of the three declarations requested by the appellants on the grounds that the law was already clear and settled. The remaining issue, a request for a declaration that non-status Indians and Métis peoples were included in the definition of ‘Indian’ for the purposes of section 91(24) of the Constitution Act, 1867, was only partially contested, with the Crown (as respondent) conceding the inclusion of non-status Indians during oral arguments.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.026 | 0.024 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| 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".