Navigating Uncertainties: Evaluating the Shift in Canadian Immigration Policies during the COVID-19 Pandemic
Bibliographic record
Abstract
Canada has a proactive immigration policy that invites individuals, mostly highly skilled ones, from around the world to make it their new home. The pandemic border closures severely affected the flow of immigrants from other countries, so the Canadian government turned to the temporary migrants who were already in the country and facilitated their transition to permanent status. Reviewing the relevant policy documents and analysing 22 semi-structured qualitative interviews with stakeholders in Ontario, we critically examine the impact of two transition measures: the amendments to Express Entry and the Temporary Residence to Permanent Residence Pathway Program. We also discuss the changes in the work permit program for international graduates. Moreover, we analyse Canadian migration management during the pandemic at three levels: the macro level (i.e., transition measures and attainment of national goals), the meso level (i.e., stakeholders' evaluations of the transition measures), and the micro level (i.e., stakeholders' perceptions of migrants' experiences with the transition measures).
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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 | 0.024 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.033 | 0.013 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".