Reconceiving discretion: from discretion as power to discretion as dialogue
Bibliographic record
Abstract
This thesis articulates, and contrasts, the two conceptions of discretion that inform the case law on administrative discretion in Canadian law: discretion "as power" and discretion "as dialogue". I suggest that the latter conception provides the best explanation for the progressive trend which developed in the law of discretion over the last twenty-five years, whereby courts devised procedural and substantive constraints on the exercise of discretion while endorsing a posture of deference towards that kind of decision-making power. Moreover, I argue that the normative foundations for that conception of discretion can be found in a combination a relational theory exemplified in writings by J. Nedelsky, a democratic theory of the kind expressed by H. Richardson, and a vulnerability theory, articulated by J. Handler and L. Sossin. I argue further that a view of discretion as dialogue is justified under an attractive understanding of the rule of law and consequently contributes to the recognition of the legitimacy of the administrative state. Finally, my conception of discretion as dialogue favours the realisation of the legitimate projects of the welfare state while at the same time recognising a role for the rule of law in government.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.061 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".