PATHWAYS TO PRECARIOUSNESS: CANADA’S INTENTIONAL FAILURE OF MIGRANT AND UNDOCUMENTED CARE WORKERS
Bibliographic record
Abstract
In this report, we, the research team, are going to consider the policies that come together to create an exploitative and precarious labour conditions for migrant care workers, who are predominantly financially challenged racialized women. We have conducted a systematic narrative synthesis analysis of the policies that are relevant to migrant care workers. In our consideration of these myriad policies, we will present a narrative that emerges in the coordinated design of these policies. The narrative that has emerged presented a journey to precariousness through a heightened likelihood of human rights violations that is facilitated by a network of policies and practices. We identify policies and practices that obscure care workers and the conditions of their labour, as well as the discriminatory impact of various policies and practices that support devaluing and delegitimizing the identities and labour of care workers. Finally, we consider the ways in which multiple policies and practices come together to create significant authorities with the capacity to surveil, restrict, and punish workers. When the erasures, devaluing, and heightened authority come together, a “synergy of failures”1 emerges with the outcome of unreasonable limits to the autonomy and choice-making capacity of care workers, thus paving the way for human rights violations. We have presented the work of care workers, advocates and activists who have addressed the human rights violations which represent the lived experiences of the policies we have studied. These care workers, advocates, and activists have also provided important recommendations for changes in labour and immigration policies. We will present these recommendations through an upstream lens, exploring the root causes that these recommendations are responding to.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.071 | 0.031 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.004 | 0.010 |
| 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".