Motivation, Personality and Well-Being in Older Volunteers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examined the effects of personality traits and motivation to volunteer on well-being as 107 older participants went through an intervention to increase volunteering. Three groups of volunteers, current, new, and former volunteers, participated. Participants were assessed four times on standardized measures of personality, health, motivation, and well-being: before and after a wait period, after volunteering, and at one year follow-up. There were no differences between pre, post and follow-up well-being. Regression analysis indicated that health, personality traits and motivation predicted well-being at pre-intervention. In contrast, after the intervention, regression analysis indicated that the interaction of higher neuroticism and greater motivation scores predicted lower well-being compared to other volunteers. One year follow-up results indicated that personality traits and health predicted well-being and that higher initial motivation predicted drop-outs while those continuing to volunteer increased their motivation scores.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it