Bibliographic record
Abstract
Abstract It is frequently said that Australian administrative law does not have, and cannot accommodate, a doctrine of deference. These statements, from judges and commentators, tend to cite the High Court's decision in Corporation of the City of Enfield v Development Assessment Commission as authority. In that case, the High Court of Australia indicated that Australia's strict separation of powers, as manifested by the legality/merits distinction, does not allow courts to defer to administrative bodies in determining the meaning of ambiguous statutory provisions. Since Enfield, there have been considerable developments in the application, and theorisation, of deference across the common law world. This article examines developments in the UK and Canada, and argues that they show that there is no single ‘doctrine’ of deference – deference is applied in administrative law in a range of ways. I argue that some of the ways in which Canadian and UK courts apply deference are not dissimilar from the principles Australian courts already apply in reviewing executive action. I argue that Australian law may benefit from greater attention to, and wider application of, these deferential principles, in order to curb judicial intrusion into administrative discretion.
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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 | 0.043 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".