N. Chappell, E. Gee, L. McDonald, and M. Stones. Aging in Contemporary Canada. Toronto: Prentice Hall, 2003.
Bibliographic record
Abstract
Aging in Contemporary Canada est un bel ajout à la documentation canadienne en gérontologie sociale. Logiquement organisé, l'ouvrage nous propose des discussions actuelles et critiques des recherches disponibles et ce, dans un style simple et cohérent. Il comporte cinq parties : introduction, points communs et diversité, santé et bien-être, institutions sociales et politique sociale. Dans l'ensemble, l'ouvrage présente un examen fouillé et à jour des dimensions importantes du vieillissement au Canada. Il intègre avec succès macro-théories et données empiriques aux dimensions micro- ou individuelles du vieillissement. Son approche critique permet au lecteur de déconstruire la perception traditionnelle de la vie des personnes âgées au Canada. Le lecteur est encouragé à poser des questions, s'attendre à du changement et assumer que ce changement résultera de l'interaction dynamique de valeurs et intérêts concurrents. Ce livre est une lecture obligatoire pour mes étudiants et étudiantes; il les stimule comme d'autres livres n'ont pu le faire.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".