Near and far, with heart and hands: The impact and value of carework in the context of refugee policy and settlement
Bibliographic record
Abstract
Canadian immigration policies show clear preference for economic immigration over more care-based immigration programs, such that some immigrants are constructed as contributing to society and others as dependent. Refugee women, who are more likely to be caregivers and less likely to be employed outside the home (Statistics Canada, 2010), are constructed primarily as care receivers. The value of their carework in their homes, in their communities, and transnationally is ignored. The ethics of care framework, together with scholarship emerging on carework, indicate that carework has been unjustly devalued in society. This study examines the intersection of care and Canadian migration policy in the lives of refugee women as they negotiate various caregiving roles. A thematic analysis of in-depth interviews with six women who migrated to Canada as refugees was conducted. These interviews show that refugee women engage in meaningful carework that contributes positively to the lives of those around them, demonstrating their own resiliency and agency. Canadian policies do not adequately recognize the value of care activities, and therefore their contributions go unrecognized and undervalued. If the true benefits and value of care were recognized, this would have an impact on Canadian immigration policy and refugee women, as caregivers, would be recognized as valuable and contributing members of society.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.035 | 0.041 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| 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".