In the Aftermath of R v Pham: A Comment on Certainty of Removal and Mitigation of Sentences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This comment discusses the findings of the review of 63 sentencing decisions made in the 4-year period immediately following the R v Pham decision.The main objective of the study is to explore how courts have been applying Pham -specifically how their construction of the inadmissibility process impacted the weight given to collateral immigration consequences and whether it led to slight mitigation of sentences.The study reveals some inconsistencies in judicial approach to the certainty of removal and its use as a factor in sentence mitigation.It is hoped that these findings will prompt both courts and defence counsel to become more cognizant of the nuances of the inadmissibility regime and strive to develop a more principled framework for consideration of these consequences in sentencing.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it