Réalisation d’une recherche sur les compétences lectorales des élèves et les pratiques d’enseignement en lecture : choix, apports, limites et compromis méthodologiques
Bibliographic record
Abstract
Cet article présente les choix méthodologiques d’une recherche qui porte sur la description des compétences lectorales au fil de la scolarité obligatoire. La recherche s’articule autour de deux volets autonomes et complémentaires. Le premier s’intéresse à la progression des compétences en lecture des élèves de quatre pays (Belgique, France, Québec, Suisse) en prenant appui sur un questionnaire rempli par les élèves de 9-10 ans, 12-13 ans et de 15-16 ans à la suite de leur lecture d’une nouvelle de Romain Gary. Le second volet documente les pratiques d’enseignement de cette nouvelle. Nous décrivons ici nos outils de collecte et d’analyse des données, puis nous les soumettons à la discussion afin de montrer les apports et les limites des choix méthodologiques sur les résultats qu’ils produisent.
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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 | 0.200 | 0.241 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".