Bibliographic record
Abstract
Depuis quelques annees, l’image associee au phenomene du vieillissement est plus positive : on parle de « bien vieillir », de « vieillissement reussi » ou de « vieillir en sante ». Aucun consensus ne se degage encore sur ce concept provocateur et stimulant. Dans cette synthese des principaux ecrits, nous presentons un point de vue sur les acceptions et modeles du « bien vieillir ». Ainsi, il apparait que le contenu du concept varie en fonction du contexte culturel, de la perspective des acteurs et selon les approches. Plusieurs modeles sont aussi identifies : les uns, unidimensionnels, envisagent le bien vieillir sous l’angle d’un domaine scientifique particulier ; les autres, multicriteres, adoptent une perspective plus large. Les determinants les plus souvent evoques par ces modeles sont les facteurs psychosociaux, c’est-a-dire les traits de personnalite, les ressources personnelles et sociales. Il demeure toutefois qu’aucun modele n’integre encore toutes les dimensions et tous les determinants potentiels du « bien vieillir ».
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".