Personal support workers and the labour market
Bibliographic record
Abstract
This chapter analyses the labour market for Personal Support Workers (PSWs). It focuses on Canada as an illustrative case. The literature suggests that, while it is helpful to consider the PSW labour market as a whole from a neo-Weberian perspective, it is better thought of as a series of sub-markets – comprising the hospital, long-term care, and home and community care sectors. These may differ in terms of such factors as wages, benefits, hours worked and working conditions, as well as in the socio-demographic characteristics of PSWs working in each care sector. To the extent that sectoral differences in PSW characteristics affect labour supply behaviours and outcomes – as, for example, in creating differences in the proportion of PSWs nearing retirement age – the heterogeneous nature of the PSW labour market is an important consideration in resource planning. The chapter also explores how PSWs compare to other health professions such as nursing, and makes select references to the international PSW literature in charting a forward course.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".