PROBING THE FRONTIERS OF ADMINISTRATIVE LAW
Bibliographic record
Abstract
This article seeks to discern trends emerging in several key decisions (Plaintiff M70/2011 v Minister for Immigration and Citizenship, Saeed v Minister for Immigration and Citizenship, Kirk v Industrial Relations Commission (NSW), Minister for Immigration and Citizenship v SZMDS, and Plaintiff M61/2010E v Commonwealth (M61)) in which the Court is arguably developing and clarifying its approach to judicial review in Australia. This is at a time when Australian administrative law is apparently diverging from other common law jurisdictions, such as the United Kingdom, New Zealand and Canada. In the cases discussed, the Court may be seen as working towards a rationale that justifies its development of a distinctively Australian jurisprudence. We seek to identify these emerging themes with a view to establishing whether they may be of some predictive value for future public law litigation. We first consider the themes becoming evident in Saeed, Kirk, SZMDS and M61 and then assess how Plaintiff M70 fits into the frame.
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 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 | 0.040 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.016 | 0.100 |
| Scholarly communication | 0.030 | 0.031 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".