Counting Outsiders: A Critical Exploration of Outsider Course Enrollment in Canadian Legal Education
Bibliographic record
Abstract
In response to anecdotal concerns that student enrollment in "outsider" courses, and in particular feminist courses, is on the decline in Canadian law schools, the authors explore patterns of course enrollment at seven Canadian law schools. Articulating a definition of "outsider" that describes those who are members of groups historically lacking power in society, or traditionally outside the realms of fashioning, teaching, and adjudicating the law, the authors document the results of quantitative and qualitative surveys conducted at their respective schools to argue that outsider pedagogy remains a critical component of legal education. The article situates the numerical survey results against both a critical review of the literature on outsider legal pedagogy and detailed explanations of student decision-making in elective courses drawn from student survey responses. Notwithstanding the diversity of the faculties surveyed, the authors conclude the article by highlighting some of the shared and significant findings of the research, paying attention to various identity-based, institutional, and external factors influencing critical course engagement in Canadian law schools today.
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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 | 0.021 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.041 | 0.021 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| 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".