“Pernicious [E]ffects”: Discretionary Decision-making in Queer Immigration to Canada
Bibliographic record
Abstract
Over the past sixty-five years, Canada’s official attitude towards queer immigration has undergone dramatic changes, from overt exclusion to ostensible welcome. However, discretionary decision-making has remained a constant component of the evolving immigration frameworks affecting queer immigrants, with negative repercussions for queer applicants. From 1952 to 2017, queer immigration to Canada has been plagued by arbitrariness, unaccountability, unpredictability, and administrative scope for discriminatory exercises of discretion by decision-makers, resulting in harms that range from stress and vulnerability to unjust exclusion. In charting future courses to improve immigration outcomes for queer applicants and refugee claimants who seek to join us on Indigenous lands, care should be taken to strike the right balance between making it easier for individuals to fit into the categorical boxes that will allow them to join us in ‘being here to stay’, and questioning the categories, arbitrary geopolitical lines, and presumptions about legitimate decision-making authority on which Canada’s immigration system currently rests.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.026 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".