Mary Lee Hummert and Jon F. Nussbaum (Eds.). Aging, Communication and Health: Linking Research and Practice for Successful Aging. Mahwah, NJ: Lawrence Erlbaum, 2001.
Bibliographic record
Abstract
RÉSUMÉ Ce livre rédigé est le résultat de dialogue et de discussions suivant la Troisième conférence internationale sur la communication, le vieillissement et la santé, tenue en 1996. Le livre reflète le thème de la conférence et affirme la conviction que la communication est un lien essentiel dans la promotion de la santé et du vieillissement réussi. Les écrits proviennent de personnes érudites, de réputations internationales et de disciplines variées. Les rédacteurs ont divisé le livre en trois sections, chacune mettant au premier plan un aspect unique d'une relation réussi entre la communication, la santé et le vieillissement. Ce livre est une ressource clé pour les académiques intéressés à la communication et au vieillissement. De plus, chaque chapitre se termine avec des suggestions utiles afin de lier la recherche à la pratique. Ce livre est une ressource précieuse pour les prestataires en service de santé qui travaillent au sein d'une clientèle âgée
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.017 |
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".