Bibliographic record
Abstract
et les Mtis. Par contre, l'article 35(2) ne dfinit pas qui est, proprement parler, Mtis, alors que de nombreuses lois dfinissent assez clairement qui peut tre considr membre des Premires Nations (Loi sur les Indiens de 1867) ou Inuit (Renvoi sur les Eskimos de la Cour Suprme de 1939). Comme les gouvernements, tant fdral que provinciaux, ont laiss aux diverses cours lgales la tche d'laborer une ventuelle dfinition, ceci a fait en sorte que, depuis plus de trente ans, toute la question de qui peut se prvaloir du statut de Mtis a t judiciarise outrance. Pour compliquer davantage la situation, il existe galement au Canada plusieurs milliers d' Indiens noninscrits , c'est--dire des Autochtones non reconnus par la Loi sur les Indiens, des gens qui vivent hors rserve ou, encore, des individus qui, comme les Mtis, sont d'ascendance mixte, mais qui ne se reconnaissent pas comme Mtis 1 .
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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; both teacher heads agree on what is shown here.
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".