De la permaculture à la permaéducation : une voie pour penser l’évaluation ?
Bibliographic record
Abstract
L’évaluation scolaire occupe une place centrale dans les systèmes éducatifs. Dans sa forme « traditionnelle », elle valorise les connaissances et savoir-faire spécifiques des élèves, au risque de négliger des apprentissages plus globaux et durables (compétences, etc.). Nous tentons ici de repenser l’évaluation à travers le prisme de la permaéducation. À l’instar de la permaculture, la permaéducation vise à développer une compréhension globale et intégrée de la complexité des systèmes écologiques, sociaux et économiques et de leurs changements. Nous montrerons que l’évaluation scolaire peut être adaptée pour tenir compte de cette complexité, tout en soutenant un épanouissement individuel et collectif.
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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 | 0.098 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.020 | 0.020 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".