RÉGULATION ÉMOTIONNELLE ET ALEXITHYMIE : DES PRÉCURSEURS DES CONDUITES ALIMENTAIRES À RISQUE
Bibliographic record
Abstract
Même si l’association entre l’alexithymie et les troubles de la conduite alimentaire (TCA) est établie, on comprend mal comment une personne en vient à développer des traits de personnalité alexithymiques qui, à leur tour, prédisent les TCA. En s’inspirant de modèles psychanalytiques, cette étude approfondit les connaissances actuelles en testant deux stratégies de régulation émotionnelle comme prédicteurs de cette relation: la suppression expressive et la réévaluation cognitive. Il était attendu que la suppression constante d’une émotion prédise positivement les traits alexithymiques (indicateur de dérégulation émotionnelle), qui à leur tour, prédiraient positivement les symptômes TCA. Inversement, il était suggéré que l’usage de la réévaluation cognitive prédise négativement les traits alexithymiques et donc les symptômes TCA. Les séquences hypothétiques ont été confirmées.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".