La participation des aînés à des activités de bénévolat: Une revue systématique
Bibliographic record
Abstract
CONTEXT: Volunteer work can be a very significant form of social participation for seniors. It can also provide seniors with important physical and psychological health benefits. This explains why occupational therapists and other health care professionals, as well as community workers who are concerned with healthy aging, appeal to seniors to volunteer in health promotion and community support However, the recruitment and ongoing involvement of seniors as volunteers is often challenging. OBJECTIVE: A systematic review of the literature was undertaken to enlighten practitioners working in this domain. The objective was to identify factors that influence seniors' participation in volunteer work. METHOD: Six bibliographic databases were searched using key words. RESULTS: A total of 27 relevant papers were retrieved and allowed an identification of a series of factors that could influence seniors' participation in volunteer work, namely personal factors, environmental factors, and occupational factors. IMPLICATIONS: This analysis leads to practical guidelines for facilitating the recruitment and maintenance of seniors' engagement in volunteer work.
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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".