Bibliographic record
Abstract
Aim: When we look to existing literature to discover trends and predictions concerning volunteering among older people, we find that extant literature does not mention physically demanding labour as a component of the volunteer activity among older adults.While volunteering refers to any activity where time is freely given to benefit another individual, group or cause, voluntary activity among older people is most often associated with people-facing, community service activities such as Meals on Wheels.This original research investigates the motivators for physically demanding labour among older volunteers.Method: Semi-structured were conducted with eighteen volunteers, aged between 70 and 91 years, whose volunteer activity at a Sydney-based maritime museum appears to be outside the norm for their age group.The interviews were transcribed and the data were analysed using a grounded theory approach.The raw data were reduced to concepts through open coding and logical groups of concepts were classified as categories.Via axial coding, the categories were initially integrated based on their relationships and then through the storyline and identification of core categories. Results:The participants in this study were aged from 70 to 91 years.At the time of this study, the duration of their voluntary contribution to the maritime museum was between 6 and 39 continuous years.Analysis of the concepts expressed in the participants' interviews allowed identification of a number of categories: among them are adjustment, alignment, self esteem and continuity.The story line or descriptive narrative that articulates the central theme of this study is as follows:An interest in ships led these volunteers to the maritime museum.The museum provides the opportunity to continue using the skills for which they were trained.These older volunteers have responsibility, control, and a sense of purpose.They also enjoy rewarding mental and physical activity with a network of like-minded people.They are working hard to enable the maritime museum to continue in its current role, thus ensuring that the historic vessels are maintained and are fully operational, allowing future gen-erations a priceless insight into Australia's maritime history.The analytic label continuity integrates most of the categories derived from the current analysis.For this paper, the researcher has focused on this core category. Conclusion:The need for continuity in important areas of the lives of this group of older people is a major motivator behind the physically demanding volunteer activity that each performs.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.666 | 0.466 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".