Bibliographic record
Abstract
Le but de cet article est de fournir un cadre de référence pour étudier l’implantation réussie des politiques et leurs effets attendus en matière d’évaluation en classe. Les recherches dans ce domaine soulèvent de nombreuses questions sur l’articulation des politiques et des pratiques en évaluation en plus d’identifier de nouvelles problématiques. Plus particulièrement, cet article cherchera à déterminer quels principes gouvernent le passage réussi des politiques aux pratiques en matière d’évaluation et comment y parvenir. L’article conclut que la mobilisation des savoirs théoriques et d’expérience est au coeur de la jonction réussie des politiques et pratiques. Il s’interroge sur l’efficacité des modèles hiérarchiques de transmission entre politiques et pratiques et émet l’hypothèse qu’il pourrait être plus profitable d’étudier comment politiques et pratiques peuvent faire oeuvre commune et se construire dans un processus d’évaluation équilibrée et de professionnalisation des réformes des systèmes éducatifs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.068 | 0.191 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".