Pour une sémiotique sociale en terrain scolaire : explorer et enrichir les compétences visuelles, émotionnelles et numériques chez les adolescents
Bibliographic record
Abstract
Omniprésente dans les pratiques communicationnelles des adolescents, l’image est un « objet polyvalent » (Féroc-Dumez, 2019) dont la dimension émotionnelle et éthique notamment est régulièrement soulignée comme un enjeu éducatif primordial. Je transpose en contexte scolaire une méthode en sémiotique sociale (Saemmer, Tréhondart et Coquelin, 2022) favorisant l’introspection idéologique et l’esprit critique en situation d’interprétation de l’image. Une expérimentation auprès de collégiens permet de mettre en lumière les potentialités de la sémiotique sociale comme dispositif pédagogique auprès d’adolescents tant sur le plan de l’acquisition d’outils sémiotiques que d’outils réflexifs. Elle les transforme en « interprètes-impliqués » tout en permettant de traiter certaines questions vives de société, comme les stéréotypes liés au genre ou aux codes en vigueur sur les plateformes numériques.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".