Rôle des représentations sociales sur le vieillissement cognitif incarné et situé : l’exemple du passage à la retraite
Bibliographic record
Abstract
Aging is a complex process characterized by physical, psychological, and social changes. The interactions between these different aspects are naturally explained by embodied and situated approaches to cognition that offer a global, integrated, and unified understanding of aging. They propose a dynamic cognition emerging from the interaction of sensory-motor perceptions (embodied aspect) and the context of the present situation (situated aspect). However, very few studies have focused on this situated aspect of cognition in the study of cognitive aging. Yet, aging is also a social process, associated with many representations, often negative, that have effects on health and cognition. Stereotype embodiment theory proposes that representations of aging are internalized by everyone over time, gradually modifying intrapersonal behaviors. This article proposes that the cognitive changes observed in aging are partly the result of physical changes, related to repeated behavioral changes, caused by the effect of representations of aging. However, unlike other forms of stigmatization, the factors of belonging to the social group of the elderly are neither clear nor static. Only the transition to retirement seems to constitute a key stage in social aging. Therefore, the transition to retirement represents a unique situation to study the impact of a major social and physical context change on cognitive functioning. It would act as a catalyst for the effect of representations of aging by marking the social transitions toward aging and retirement. Different perspectives of applied research are also discussed, around prevention interventions and preparation for retirement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".