USING ARTISTIC TAPESTRIES TO EXPLORE STUDENTS’ ATTITUDES TOWARD OLDER ADULTS AND THE AGING PROCESS
Bibliographic record
Abstract
In Ontario, Canada, the Ontario College of Social Workers and Social Service Workers governs and regulates the practice of both the social work and social service worker professions. Aging demographics imply the need for more gerontology trained social work and social service worker professionals, yet students’ interest in the field of aging remains low. The purpose of this arts-based study was to explore twenty undergraduate social work and social service worker students’ attitudes toward older adults and the aging process in the course of their gerontology setting field placement learning. We developed an arts methodology inviting student participants’ to engage in creating two themed mixed media art tapestries, over the course of five weeks. Video recordings captured the group processes and the evolution of the tapestries capturing a number of aging themes. Overall, the supportive group environment helped participants deepen their understanding of aging and the life-course. The tapestry creations provided an innovative outlet for sharing positive personal and professional perceptions and experiences regarding older adults and aging. We report results from two focus groups (conducted post tapestry completion) that capture students’ experiences regarding participation in the study and the meaning that the tapestries held for them. Also highlighted are facilitation recommendations identified by the students as essential to a successful tapestry experience. This research was supported by a grant from the Faculty of Arts, Humanities and Social Sciences (FAHSS), University of Windsor, Windsor, ON.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".