Bibliographic record
Abstract
Marie-Eve Bradette est professeure adjointe au Département de littérature, théâtre et cinéma et titulaire de la Chaire de leadership en enseignement sur les littératures autochtones au Québec -Maurice-Lemire.Elle est détentrice d'un doctorat en littérature comparée de l'Université de Montréal.Dans le cadre de sa thèse, pour laquelle elle a obtenu la médaille d'or de la Gouverneure générale du Canada (2021), elle s'est intéressée à la mise en scène des théories et des épistémologies du langage et à leur résurgence dans les littératures autochtones écrites en français et en anglais sur les territoires réclamés par le Québec et le Canada.Ses recherches actuelles, amorcées grâce à l'obtention d'une bourse Banting pour la poursuite d'un stage postdoctoral à l'Université de Régina, abordent les
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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 | 0.003 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.456 | 0.237 |
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".