The textual organization of placement into long‐term care: issues for older adults with mental illness
Bibliographic record
Abstract
Arranging placement of older adults from hospital mental health units into nursing homes or assisted living facilities can be difficult and protracted. The difficulty in placing these individuals is often attributed to stigma; that is, personnel in nursing homes are reluctant to accept mentally ill older adults because of the fear of mental illness and violence. Using an institutional ethnographic approach, we argue the importance of exploring how nursing home access is organized, especially the institutional process of placement. Our study, examining the process of placing older adults from mental health units into nursing homes or assisted living facilities within a western Canadian city, reveals how three specific textual points within the institutional process of placement do not work well for older adults with mental illness. These textual points include: constructing the older adult as a 'placeable' person, the first-level match and the second-level match. After exploring why the three specific points in the process do not work well for mentally ill individuals, we reconsider the explanation of stigma, and then suggest implications for change.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".