Comparative law at the heart of immigration law: Criminal inadmissibility and conjugal immigration in Canada and the United States
Bibliographic record
Abstract
Abstract Immigration law is necessarily a comparative legal practice in at least three aspects: (i) comparing a would-be immigrant’s criminal history to the destination state’s criminal laws; (ii) comparing an immigrant’s diplomas and education to the destination state’s educational system; and (iii) comparing immigrants’ marriages and intimate relationships to domestic family law regimes. For all of these questions, the methodological dilemmas of comparative law are repeated within immigration law. This article is an overview of all the comparative methods used in North American immigration laws since the 1880s, for evaluating criminal records and intimate partnerships. The methods range from plain translations to complex systemic comparisons. Over the last 130 years, almost all methods had some, either good faith or strategic use; with the biggest transformations happening in the comparison of marriages. Effectively, private international law has been replaced by a separate “immigration marriage law,” which has globalized at astonishing speed.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.026 | 0.020 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".