Bibliographic record
Abstract
Drawing on his factums in many constitutional cases, this article suggests that Joe was an early and consistent champion for substantive, procedural and remedial equality. The first part examines Joe’s commitment to substantive equality including his arguments for British Columbia in Andrews v. Law Society of British Columbia, his forward-looking approach to Indigenous rights and his commitment to authentic public law litigation that respected the disadvantaged. The second part examines Joe’s recognition that substantive equality cannot be achieved without procedural equality that gives disadvantaged litigants the equal benefit of procedural rules that too often favour governments. It examines Joe’s arguments and impact with respect to public interest standing, court fees, advanced costs, special costs and statute of limitations. The third part examines how Joe argued against remedies that deprived disadvantaged groups of immediate and effective remedies. Joe’s vision of public law litigation — what he defended as the “public good of adjudication” — is an important legacy that should continue to be advanced. Joe understood that the promised land of substantive equality also requires procedural and remedial equality.
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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.056 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.019 | 0.022 |
| 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".