Tu m'as donné ta boue et j'en ai fait de l'or ou l'écriture poétique en classe de langues est-elle transgression ?
Bibliographic record
Abstract
Notre propos souhaite éclairer la notion de transgression dans le cadre des cours de langues avec l'aide des outils d'analyse du philosophe humaniste Paul Ricœur. Le jeu sémantique en donnant l'impression aux apprenants de sortir du sillon scolaire permet-il de penser soi-même comme un autre, d'ouvrir des axes de réflexion et de créativité dans le respect du Cadre Européen de Référence pour les Langues ? From rags to riches or transforming mud into gold : how and why poetry writing in the language classroom is a form of transgression? Abstract: Our analysis aims at enriching the notion of transgression with the analytical tools of the philosopher-cum-humanist Paul Ricœur. We may wonder if the semantic work at play with words giving learners the impression to walk out of the commonly established path allows to think oneself as another and to open new vistas for learners in the respect of the Common European Framework of Reference for Languages?
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".