Impact of educational level on metaphor processing in older adults
Bibliographic record
Abstract
Résumé La capacité à comprendre le langage non littéral est une composante essentielle de notre communication quotidienne et un amoindrissement de cette capacité pourrait avoir un impact sur notre vie sociale ; très peu d’études ont cependant examiné la façon dont le niveau d’éducation affecte cette capacité chez les personnes âgées. Comprendre les métaphores, comme beaucoup d’autres énoncés non littéraux, produit une apparente nécessité d’aller par-delà de ce qui est littéralement dit pour appréhender l’intention de communication du locuteur et, par conséquent, le sens de ses énoncés. Le but de cette étude était d’évaluer l’effet du niveau d’éducation sur la compréhension des métaphores chez des individus âgés. Les participants âgés droitiers ont été évalués en utilisant un paradigme d’amorçage sémantique. Les résultats montrent que le niveau d’éducation des participants joue un rôle important dans le traitement de la métaphore.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".