Bibliographic record
Abstract
egislative intent, the Supreme Court has said, is the "polar star" of standard of review analysis. 1 After the Supreme Court's spring 2009 decision in Khosa 2 though, the star still needs more focus.In this decision, a 7-1 majority of the Court upheld an immigration tribunal's decision to reject an application for an exemption from a removal order.Khosa was the last chapter in a human drama that started with a fatal street race on Vancouver's Marine Drive.It is an ongoing chapter in another story, the debate about the nature of judicial review of administrative action.The majority judges in Khosa disagreed as to whether section 18.1(4) of the Federal Courts Act 3 is sufficient to establish the relevant standard of review, or whether it must be supplemented by the common law standard of review principles in the 2008 decision in Dunsmuir. 4 The Vancouver street race ended when a car driven by Mr. Sukhvir Singh Khosa, an eighteen-year-old landed immigrant, struck and killed an innocent pedestrian.Mr. Khosa was convicted of criminal negligence and ordered deported back to India, his country of birth.This prompted a wide-ranging exchange about the relationship between judicial review and legislative intent.Neither of the majority approaches seems entirely satisfactory to me, but the debate in Khosa suggests some ideas for improvement.To show why, I will note briefly the facts and the immediate questions in this case, and then look in more depth at the key underlying question of the relationship between common law review on one hand, and review codes and other legislative provisions, on the other.Then I will offer some suggestions for adding coherence to standard of review analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".