‘I wouldn't choose this work again’: Perspectives and experiences of care aides in long‐term residential care
Bibliographic record
Abstract
AIMS: To provide insight into the everyday realities facing care aides working in long-term residential care (LTRC), and how they perceive their role in society. DESIGN: A qualitative ethnographic case study. METHODS: Data were collected over. 10 months of fieldwork at one LTRC setting [September 2015 to June 2016] in Western Canada; semi-structured interviews (70 h) with 31 care aides; and naturalistic observation (170 h). Data were analysed using reflexive thematic analysis. RESULTS: The findings in this work highlight the underpinned ageism of society, the gendered work of body care, and the tension between the need for relational connections - which requires time and economic profit. Four themes were identified, each relating to the lack of training, support, and appreciation care aides felt about their role in LTRC. CONCLUSION: Care aides remain an unsupported workforce that is essential to the provision of high-quality care in LTRC. To support the care aide role, suggestions include: (i) regulate and improve care aide training; (ii) strengthen care aides autonomy of their care delivery; and (iii) reduce stigma by increasing awareness of the care aide role. IMPACT: What problem did the study address? The unsupportive working conditions care aides experience in LTRC and the subsequent poor quality of care often seen delivered in LTRC settings. What were the main findings? Although care aides express strong affection for the residents they care for, they experience insurmountable systemic and institutional barriers preventing them from delivering care. Where and on whom will the research have impact? Care aides, care aide educators, care aide supervisors and managers in LTRC, retirement communities, and home care settings.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.020 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".