Challenges of caring for the aged: Attracting and retaining aged care assistants in Western Australia
Bibliographic record
Abstract
Abstract Objectives To report on the attraction and retention challenges concerning Aged Care Assistants (ACAs) in the state of Western Australia (WA) and to identify the related specific ‘push‐and‐pull’ factors. Methods A self‐administered survey resulted in a 20.2% response rate (79/391) from nine WA residential aged care facilities. The key purpose of the survey was to explore the reasons why ACAs might remain in their jobs or leave for other occupations. The χ2 test was employed to determine statistically significant associationsbetween intention to stay in the job and each of the independent variables. Results Those who were younger, casually employed and working in urban areas were more likely than their counterparts to state their intention to leave their workplace in the next year. Conclusion In line with the national emphasis on the attraction and retention of ACAs, the findings reported here have the potential to inform future strategies in residential aged care facilities in WA.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".