Catégorisations discursives représentées dans les bilans de formation en travail social
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Formation et profession 30(1) 2022 1 sum Cet article, qui porte sur les crits professionnels produits en formation, prsente les donnes empiriques, et fournit les premires analyses d'une recherche mene en 2018 sur la pratique valuative des bilans de fin de formation des ducateurs Spcialiss (S) Montpellier (France). Les bilans en question, rdigs par les formateurs accompagnant les tudiants dans leur parcours, intgrent un dispositif de professionnalisation appliqu l'IRTS (Institut Rgional du Travail Social). Les auteurs dcrivent le contexte sociohistorique dans lequel s'inscrit cette recherche, pour analyser un panel d' crits et ce qu'ils impliquent en matire de catgorisations discursives, en partie prtablies, d'intgration dans le mtier.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it