Workers’ Experiences of Crises in the Delivery of Home Support Services to Older Clients
Bibliographic record
Abstract
In the provision of care to older clients, home support workers regularly confront, avert, and manage crises. Semistructured interviews were conducted to explore the nature, type, and management of crises from the perspective of home support workers (N = 118) of older persons in British Columbia, Canada. The delivery of home health care occurs within a context of unpredictability related to scheduling, time constraints, variability of client need, and changing work environments. These events are experienced by 91% of home support workers and range from a serious medical incident (e.g., fall, death) to an interpersonal dilemma (e.g., client refusal of service, argument between worker and family member). Home support workers use a variety of strategies to manage these incidents. The analysis of crises enables us to better understand how agency and care policies may be more responsive to circumstances that challenge care work in home health settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".