Fictions d’enfants, fictions d’élèves. Rencontres avec des sculptures contemporaines en 6e
Bibliographic record
Abstract
Si tous les enfants sont capables d’exprimer, à l’écrit comme à l’oral, des ressentis et des jugements qui témoignent de compétences esthétiques, ils se révèlent, comme élèves à profils socialement contrastés, inégalement compétents à leur donner la forme qu’attend l’école dans sa façon de traiter les objets du monde. Cet article le montre en s’appuyant sur une enquête auprès d’enfants de deux classes de sixième découvrant des sculptures modernes et contemporaines au jardin des Tuileries. L’étude de ce qu’ils disent des œuvres, à la lumière de deux appuis théoriques croisés, l’un issu de la didactique et l’autre de la sociologie des apprentissages, permet de mieux comprendre ce qui peut faire difficulté, pour une partie d’entre eux, quand ils sont élèves, plus précisément dans le cadre du cours de français.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".