Interweaving Jurisdictions: A Critical Examination of Legal Authority, Sentencing, and Deportation
Bibliographic record
Abstract
Abstract The statutory authorities to remove and to review appeals of removal assigned in the Immigration and Refugee Protection Act (IRPA) exist in a complicated, interweaving relationship with the legal power to sentence held by judges of the criminal court. Judges do not retain the legal authority to decide on removal. Judges do, however, hold the jurisdiction to consider deportation at sentencing. The practice of judicial jurisdiction in turn has potentially significant effects for subsequent practices of jurisdiction under the IRPA, including where judges use their legal power to apply sentences protecting permanent residents from removal and/or losing their right of appeal. Despite these important jurisdictional connections, how judicial authority to consider deportation is enacted has not received scholarly examination. This paper draws from an analysis of case law and interviews to address this gap, tracing how judges practice their jurisdiction when sentencing permanent residents.
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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 | 0.025 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.028 | 0.056 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| 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".