Silenced Complaints, Suppressed Expectations: The Cumulative Effects of Home Care Rationing
Bibliographic record
Abstract
In many Western welfare jurisdictions, publicly provided home care is being eroded and its provision increasingly individualized. These shifts are of a particular significance for older women, a group for whom supportive home care has been an important buttress against the social and physical jeopardies of old age. A longitudinal, qualitative study of such women in Ontario, Canada, spanned the implementation of managed competition in home care and a period of rapid privatization and service rationing. Study participants experienced cuts and, stemming from increasingly precarious employment conditions in the home care workforce, inconsistent care providers. These changes generated distress, insecurity, and isolation in participants' lives. This article explores how their complaints about insufficient care were silenced: by fear, hopelessness, and the cultural injunction to put a stoic and selfless face on the limitations of old age. Their accounts reveal how large material and discursive shifts and state restructuring come to penetrate identity, feeling, and speech. This examination of the silencing of complaint at home care's front lines reveals the cumulative effects of rationing; it also illuminates how, if heard, service users' voices can inform collective struggles to resist the degradation of home care and reposition older people in relation to the state.
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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 | 0.009 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".