Work of Art, Art of Work: Artistic Literacy and Quality in Long-Term Dementia Care
Bibliographic record
Abstract
Abstract This paper shares results from a thematic analysis (Braun & Clarke, 2006) of semi-structured interviews with a purposive snowball sample of 15 leaders in dementia arts education and praxis from Canada, the United States and United Kingdom. Interviews were conducted as part of a multi-phased collaborative, interdisciplinary arts-informed research project that aimed to operationalize quality mental health and dementia care in long-term care (LTC) from a relational perspective, with a focus on LTC staff literacy. Artistic literacy that is cultivated through creative arts-making and public exhibiting was described by participants as crucial to supporting and promoting quality within long-term care. Quality was imagined as a work of art and operationalized in terms of artist competencies, capacities and conditions. Artists included LTC staff, residents and their family and friends. Our analysis identified five themes related to artistic literacy: space-making, validation, fostering community, means of engagement, vulnerability and resilience. Drawing on cultural sociology (Bourdieu, 1993, 1984) and aging studies theory (Basting, 2018), we consider and discuss the role of the arts in disrupting unexamined assumptions about quality in LTC and advancing innovation in LTC staff mental health and dementia care.
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.
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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".