Place-Making through Media: How Media Environments Make a Difference for Long-Term Care Residents’ Agency
Bibliographic record
Abstract
This paper explores the unique relationships care home residents have with communication media. Drawing on findings from an ethnographic case study at a long-term care site in British Columbia, Canada, I describe how care home residents’ everyday media practices are intertwined with their negotiations of longstanding attachments and new living spaces. The research draws connections between the spatiotemporal contexts of media use and residents’ experiences of social agency. Long-term care residents in this research were challenged to engage with the wider community, maintain friendships, or stay current with events and politics because their preferred ways of using communication media were not possible in long-term care. The communication inequalities experienced by care home residents were not simply about their lack of access to media or content but about their inability to find continuity with their established media habits in terms of time and place. While most research about communication media in care homes has been intervention oriented, this research suggests that long-term care service and funding policies require greater attention to create flexible, diverse, and supportive media environments.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".