Palliative Care Volunteers: Why Do They Do It?
Bibliographic record
Abstract
Two studies were conducted to examine people's motives for joining a palliative care volunteer program. To generate a pool of reasons for becoming a palliative care volunteer, previous studies of motivations relevant to palliative care were reviewed and interviews were conducted with 15 palliative care volunteers (Study 1). Combining the literature review and interviews, a total of 22 distinct reasons for volunteering were identified and used to create an Inventory of Motivations for Palliative Care Voluntarism (IMPCV). In Study 2, 113 palliative care volunteers responded to the IMPCV. "To help ease the pain of those living with a life-threatening illness" was rated as the most influential reason for becoming a palliative care volunteer. A principal components factor analysis was conducted on the IMPCV. It was decided that four factors adequately represented the items: Leisure, Personal Gain, Altruism, and Civic Responsibility.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 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 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".