Mike Bender, Paulette Bauckham and Andrew Norris. The therapeutic purposes of reminiscence. Thousand Oaks, CA: Sage, 1999.
Bibliographic record
Abstract
RÉSUMÉ L'augmentation actuelle de l'attention critique portée à la théorie et à la pratique de la réminiscence ont incité Bender, Bauckham et Norris à fournir un guide concret sur les interversions dans ce domaine visant surtout les aîné(e)s vivant en établissement. Les auteurs présentent et examinent des exemples précis d'utilisation de la réminiscence dont l'analyse raisonnée, les groupes prioritaires, les résultats escomptés et les difficultés prévisibles. Le texte contient des conseils fondamentaux et pratiques sur l'organisation et l'animation de ces groupes sous la forme de directives précieuses pour les animateurs novices ou expérimentés. Les lacunes du débat théorique et les faiblesses méthodologiques et empiriques jurent quelque peu cependant avec la qualité d'ensemble du texte, surtout aux yeux des lecteurs qui s'intéressent à la recherche.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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".