Benefits of volunteering on resilience with aging: a case study
Bibliographic record
Abstract
As the study of volunteering among older adults continues to evolve, questions related to the benefits of volunteering are of growing interest. Volunteering may create opportunities to develop resilience in older adults as it can serve as a coping strategy. This case study explored the perceived benefits of volunteering on resilience and various dimensions related to aging among elderly volunteer dancers. In this qualitative study, 13 volunteer performers of Korean traditional dance were recruited for in-depth interviews. The analysis of the transcripts generated five themes related to the benefits of volunteering that were unique to older volunteers: (1) finding a sense of self-worth through serving others, (2) finding a sense of purpose, (3) experiencing gratitude, (4) renewing a younger self, and (5) building companionship. The findings revealed that regular volunteering promoted the experience of resilience in the face of the challenges associated with aging.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".