Contested Concepts: Equality and Dignity in the Case-Law of the Canadian Supreme Court and South African Constitutional Court
Bibliographic record
Abstract
Ronald Dworkin draws a distinction between 'criterial' and 'interpretive' concepts. People share criterial concepts where they agree upon a definition that sets out criteria for the correct application of the term associated with the concept. Interpretive concepts such as justice function differently because it is possible to disagree about the criteria that define the concept. Equality is a prime example of an interpretive concept. Both the Canadian Supreme Court and South African Constitutional Court have attempted to give content to equality through dignity. However, dignity is likewise an interpretive concept. Far from lending clarity to equality, it simply opens the door to a range of further conceptions. The final part of the chapter explores the possibility that a more central role should be accorded to the principle of proportionality when adjudicating equality claims.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.036 | 0.054 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".