De la prise en compte des problèmes socio-écologiques à l’évolution des principaux courants de recherche en éducation relative à l’environnement dans la francophonie
Bibliographic record
Abstract
Au cours des 20 dernières années, les problèmes socio-environnementaux et leurs conséquences néfastes se sont à la fois très largement multipliés et sont entrés dans les agendas politiques, économiques et juridiques. Ces changements se reflètent bien évidemment dans les recherches francophones du domaine de l’éducation relative à l’environnement (ERE). Nous allons présenter trois axes qui caractérisent désormais ce champ de recherche : les recherches qui se réfèrent à la construction d’un rapport à l’environnement, celles qui portent sur l’éducation à la citoyenneté et enfin, celles qui s’inscrivent dans le cadre de l’éducation au développement durable.
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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 | 0.075 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".