A ‘career shift’? Bounded agency in migrant employment pathways in the aged care and early childhood education and care sectors in Australia
Bibliographic record
Abstract
Unlike many countries in Europe and North America, Australia does not directly recruit migrants to work in frontline aged care and early childhood education and care (ECEC). However, employment data shows that a large proportion of people working in these two care sectors are migrants. Little is known about how migrants make their way into the ECEC and aged care sectors in Australia. Drawing on qualitative interviews with migrants working in three cities, this paper explores the pathways of migrants into care work in Australia. It uses the concept of bounded agency to illustrate how migrants articulate agency within constrained employment opportunities. It finds that participants experience a heavily constrained sense of agency upon arrival in Australia due to lack of skills recognition and English language proficiency. Our data shows that, over time, participants mobilise existing resources – and acquire new ones – to develop new frames for action that culminate in what they describe as a ‘career shift’ into employment in formal care settings. Our data sheds new light on the way in which migrant care workers, through this process, are able to negotiate a sense of agency and pursue employment preferences, within a context of constraint.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".