REALITIES AND CHALLENGES OF EDUCATIONAL REFORM IN THE PROVINCE OF QUÉBEC: EXPLORATORY RESEARCH ON TEACHING SCIENCE AND TECHNOLOGY / RÉALITÉS ET DÉFIS DE LA RÉFORME SCOLAIRE QUÉBÉCOISE : UNE ÉTUDE EXPLORATOIRE DE L’ENSEIGNEMENT DE LA SCIENCE ...
Bibliographic record
Abstract
Exploratory and descriptive research was conducted in a secondary school to reveal the realities and difficulties of the implementation process that awaits teachers under Quebec’s Educational Reform. A team of teachers agreed to be observed while simulating implementation one year ahead of other schools. Results underscore the importance of in-service training, of an implementation plan, and of the level of professionalism. Analysis tends to indicate that the Quebec implementation experience is not uncommon. REALITES ET DEFIS DE LA REFORME SCOLAIRE QUEBECOISE : UNE ETUDE EXPLORATOIRE DE L’ENSEIGNEMENT DE LA SCIENCE ET DE LA TECHNOLOGIE Une recherche exploratoire et descriptive qui a ete menee dans une ecole secondaire illustre les realites et les difficultes relatives au processus d’implantation chez les enseignants qui vivent la reforme scolaire quebecoise. Une equipe d’enseignants a consenti a faire l’objet d’observations alors qu’ils tentaient une implantation anticipee du programme de science et technologie (premier cycle) au secondaire, une annee avant l’implantation officielle. Les resultats obtenus reaffirment l’importance de la formation continue, de l’existence d’un plan l’implantation et de la professionnalisation enseignante. L’analyse tend egalement a montrer que l’experience d’implantation quebecoise n’est pas fondamentalement differente de celle qui a ete conduite ailleurs.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".