From illegalised migrant toward permanent resident: assembling precarious legal status trajectories and differential inclusion in Canada
Bibliographic record
Abstract
Precarious legal status trajectories (PLSTs) are marked by periods without state authorisation and/or forms of temporary authorisation. They are temporally prolonged and directionally unpredictable, and may be spatially, juridically and substantively discontinuous. Their complexity poses challenges for researchers interested in the relationship between changes in legal status and differential inclusion. We examine the trajectories of illegalised Anglo-Caribbean and Latin American migrants living in Canada in the mid-2000s who applied for one or both of two humanitarian legal status adjustment mechanisms to obtain permanent residence: late refugee claims and applications on humanitarian and compassionate grounds. Despite sharing early illegalisation, we find regional racialised and gendered differences in their PLSTs. We present a framework for understanding how different trajectories are populated, and how the somewhat unpredictable outcomes of adjudications may lead to further applications and a reorganisation of PLSTs. We conceptualise PLSTs as assembled through (1) colonial legacies and histories of migration that contribute to racialised humanitarian deservingness, (2) state policies and humanitarian adjudication procedures, and (3) everyday encounters between migrants and other social and institutional actors. Our analysis shows how these elements come together and generate variable PLSTs and multi-dimensional differential inclusion.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".