Analyse des enjeux relatifs au vivant dans les programmes scolaires français et québécois
Bibliographic record
Abstract
Dans le contexte des adaptations apportées aux programmes qui répondent notamment aux avancées technoscientifiques qui modifient nos représentations et nos rapports au vivant, nous avons étudié les programmes scientifiques de la France et du Québec sous trois volets : la caractérisation du vivant, les approches éthiques du vivant et, enfin, les méthodologies scientifiques et techniques pour aborder le vivant. Nous observons dans les deux cas une similitude des connaissances scientifiques envisagées avec une prise en compte de la « mondialisation » et des préoccupations touchant l’avenir de la planète. De façon plus particulière, nous remarquons des nuances dans les progressions, dans certaines attentes en termes de construction de rapport au vivant, dans l’intégration d’un questionnement éthique et des variantes sur les méthodes proposées.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".