L’art populaire : un outil d’éveil identitaire chez l’apprenant iranien
Bibliographic record
Abstract
Actuellement la vague d’émigration des jeunes Iraniens a provoqué un état conflictuel dans le contexte de l’enseignement et de l’apprentissage du français en Iran. Loin d’arriver à un enrichissement, l’apprenant iranien lors du choc culturel, se trouve dans une position d’acceptation absolue de la culture occidentale ; ce qui mènerait une démarche interculturelle, s’adressant dans sa première phase à l’identité de soi, vers un échec. Cette recherche consiste à voir où se trouve l’origine de cet échec menant à une crise identitaire et comment, à l’aide d’une démarche pratique, l’art populaire dans le cadre du théâtre expérimental pourrait créer un espace d’éveil identitaire implicite chez l’apprenant iranien. Popular art: an identity awaking tool on the part of the Iranian learner Currently the wave of immigration of young Iranians has caused a state of conflict in the context of teaching and learning French in Iran. When the Iranian learners confront the cultural shock, far from becoming a cultural enrichment, they find themselves in a position of absolute acceptance of Western culture, which would lead to an intercultural approach, addressing itself to identity in its first phase, then to a complete failure. This research tries to see the origin of this failure which results in an identity crisis and also to see how the use of popular art in the framework of an experimental theatre could create a space of implicit awakening in the identity of the Iranian language learner.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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; 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".