Bibliographic record
Abstract
This chapter examines how Canada has treated accompanying family members of migrants during the COVID-19 pandemic taking, examining both quantitative data and qualitative counternarratives. In particular, it employs as a case study the experiences of the spouses of study- and work-permit applicants who were largely stuck abroad, neither able to travel to Canada nor apply for permanent residency, during much of the pandemic. I argue that Canada’s pandemic border policies reinforce a restrictive “colour line” on family-based migrants from the Global South by negatively affecting their mental health and by deepening systemic racism. This notwithstanding, both legal and policy structures in Canada have impeded family-based migrants from challenging these border policies by failing to provide accessible legal remedies and policy lenses that take into account racism and mental health. Leaning on the lived experiences of three family-based migrants during the pandemic, I show how social science evidence, and deconstructing the pandemic through both data and lived experience, is important in drawing out the adverse, inequitable impact of pandemic border policies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".