Intégrer la culture au jugement sur la performance : l’impossible position de l’évaluateur sensible
Bibliographic record
Abstract
Cet article expose les dilemmes éthiques rencontrés par les évaluateurs lorsqu’ils jugent de la valeur des services éducatifs autochtones. Il se fonde sur notre pratique en évaluation et l’analyse d’articles scientifiques et des directives du gouvernement canadien ainsi que sur les rapports produits dans le cadre de consultations publiques. Nous esquissons d’abord les grands enjeux de la transmission culturelle dans les écoles autochtones, puis nous présentons les principes qui guident l’éthique professionnelle de l’évaluation et nous dressons un portrait des approches préconisées dans les communautés autochtones. À la lumière des informations présentées, nous abordons les limitations de ces approches, notamment en ce qui a trait à leur faisabilité et aux conditions systémiques qui en réduisent la portée.
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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 | 0.135 | 0.173 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.057 |
| Scholarly communication | 0.030 | 0.020 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".