Colleen Keller and Julie Fleury. Health Promotion for the Elderly. Thousand Oaks, CA: Sage, 2000.
Bibliographic record
Abstract
RÉSUMÉ Health Promotion for the Elderly, avance des connaissances scientifiques au sujet des effets des comportements problématiques et des faits connus sur l'efficacité des interventions de promotions santé au sein des personnes âgées. Le tout est bien organisé, toutefois, le livre connaît quelques restrictions. Par exemple, le livre est surtout basé sur une littérature et des expériences américaines, il est déjà périmé dans certains aspects, il semble embrasser une définition limitée de la promotion santé et les sujets qui devraient faire l'objet d'une recherche moderne (p. ex. la sexualité, l'invalidité, les politiques et l'alphabétisation) sont absents ou minimisés. La prochaine édition pourrait être plus complète si ces restrictions sont adressées.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".