Cumulative Disempowerment: How Families Experience Older Adults’ Transitions into Long-Term Residential Care
Bibliographic record
Abstract
Although emerging research links family experiences with long-term residential care (LTRC) transitions to structural features of health care systems, existing scholarship inadvertently tends to represent the transition as an individual problem to which families need to adjust. This secondary qualitative analysis of 55 interviews with 22 family members caring for an older adult engages a critical gerontological lens. A concept of cumulative, structural empowerment informs this analysis of families' experiences across a broad continuum of older adults' moves into LTRC. Leading up to transitions, families have little power over home care services, and family members have little control over their involvement in care provision. Some families respond by making choices to refuse publicly provided service options, therein both resisting and reinforcing broader relations of power. Expectations for family involvement in LTRC placement decisions were incongruent with some families' experiences, reinforcing a sense of powerlessness compounded by the speed with which these decisions needed to be made. A broad temporal analysis of transitions highlights LTRC transitions as a process of cumulative family disempowerment connected to broader formal care structures alongside emphases on aging in place and familialism that characterize LTRC as the option of last resort.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| 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".