L’heuristique de la peur au fondement de l’agir écocitoyen critique, créatif et bienveillant
Bibliographic record
Abstract
L’éducation relative à l’environnement (ERE) invite à penser et construire un monde respectueux de l’environnement et soucieux de l’équité sociale. Cependant, on tend à la limiter le plus souvent à la transmission de connaissances technoscientifiques oubliant aussi bien ses dimensions socioaffective, critique, créative et prospective que ses fondements éthiques. Notre intention est de trouver, dans le champ de la philosophie, un mode de penser et d’agir à même d’accompagner l’ERE, surtout lorsqu’il s’agit d’amener les jeunes et les adultes à aiguiser leur sens de la responsabilité, à reconquérir leur identité individuelle et collective et à reconstruire la trame qui les relie au monde. Notre travail montre que l’heuristique de la peur, telle que mise en évidence par Hans Jonas peut stimuler ce pouvoir d’agir écocitoyen. Au moyen d’analyses herméneutique et critique, nous montrerons comment une telle approche peut contribuer à une éducation à l’environnement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".