From Caregiver to Personal Support Worker: Canada's Caregiver Programs and Labour Market Segmentation Among Filipina Women in Toronto
Bibliographic record
Abstract
The lowest rung of the Canadian healthcare system is occupied by those categorized as personal support workers (PSWs). Despite their important contributions to Canada’s healthcare system, this work is stigmatized, devalued and characterized by multiple dimensions of precarity. It is also a labour segment that is increasingly differentiated by gender, race, and citizenship, with Filipina immigrants accounting for 30% of immigrants in this workforce. Recent scholarship has drawn connections between Canada’s Live-in Caregiver Program (LCP) and the overrepresentation of Filipina immigrants in PSW roles. While these studies demonstrate how most caregiver migrants eventually transition out of caregiving, many remain in a narrow set of low-wage, “low-skilled” occupations, with PSW work emerging as a notable choice. By centering the experiences of Filipina PSWs in Toronto who migrated to Canada as live-in caregivers, this thesis explores how the caregiver-to-PSW pathway is constituted in the local labour market and within the lifeworlds of Filipina former caregivers. Using a feminist economic geography framework, this research calls attention to: 1) the social and institutional mechanisms that construct a pathway towards PSW labour; and 2) the racialized and gendered discourses that construct idealized PSW subjectivities and the ways in which they overlap with notions of Filipina identity. Key theoretical concepts include the social embeddedness of labour markets, embodiment and interpellation, and citizenship. I situate this research within the wider institutional landscape of Canada’s temporary migrant caregiver programs and the gendered politics of transnational labour migration in the Philippines to illustrate the context in which Filipina women come to view PSW work as a viable and suitable post-caregiver program career.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.022 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".