Enseigner en contexte de pandémie : quelles différences entre les professeurs du primaire, du secondaire et de l’université?
Bibliographic record
Abstract
Enseigner en contexte de pandmie : quelles diffrences entre les professeurs du primaire, du secondaire et de l'universit ? Formation et profession 28(4 hors-srie), 2020 sum Lors de la pandmie lie de COVID-19 du printemps 2020, les enseignants ont t contraints d'assurer la continuit pdagogique en rinventant leur enseignement en dehors de la classe. Par consquent, le recours aux outils numriques s' est avr incontournable. Cette recherche value, travers une enqute adresse 847 enseignants de langue vivante trangre ou rgionale exerant dans des tablissements franais, si le niveau d' enseignement desdits enseignants a un effet sur l'anxit qu'ils ressentent, sur leur sentiment d' efficacit personnelle, ainsi que sur leurs perceptions et usages des outils technologiques en contexte de confinement.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".