Diverse and inclusive high courts: a global and intersectional perspective
Bibliographic record
Abstract
Critical race feminists call attention to the ways in which multiple and overlapping forms of privilege and discrimination shape individual experiences and perspectives. In this article, we argue that judiciaries cannot be fully inclusive if their composition does not reflect a society’s intersecting sources of disadvantage. We consider intersectional inclusion on high courts from a comparative perspective. Most existing practices of representation on high courts promote the inclusion of groups as if they are internally homogenous. We explore the attempts at and successes of promoting intersectional inclusion in the context of the high courts of Canada and South Africa. Although the inclusion of marginalized subgroups such as black women has not been automatic in South Africa, its progress is further along than Canada in promoting intersectional diversity on the highest court.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.016 | 0.068 |
| Scholarly communication | 0.026 | 0.014 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.003 | 0.005 |
| 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".