Race, Courts and Tribunals: Emerging Doctrines and Their Impact
Bibliographic record
Abstract
Critical Race theorists were attracted to the CLS movement because it challenged liberal concepts about the" neutrality" and" objectivity" of law and because it recognized the fact that law legitimates existing" maldistributions" of wealth and power. However, in the end, Critical Race theorists rejected CLS because of its refusal or inability to recognize the central role that race and racism play in law, as well as the movement's failure to give credit to the experiences of people of colour. Critical Race theorists also rejected the CLS view of rights discourse and its disinclina-tion to use law as a tool against oppression and subordination. This book documents how Canadian Critical Race theorists are beginning to develop a body of thought designed to move us beyond theory to practical applications. Canadian Black lawyers and others are gradually beginning to seriously consider the role of race in litigation and to de-velop effective" Critical Race Litigation"(CRL) strategies to address the issue. As demonstrated by cases such as R. v. RDS (1994), R. v. Parks (1993), R. v. Williams (1998) and R. v. Cole (D)(1996),'these strategies are increasingly placing issues of race before the Canadian courts.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.016 | 0.125 |
| Scholarly communication | 0.032 | 0.028 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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".