Transcending Boundaries in Legal Education: A Vehicle for Teaching Students to Think Critically
Bibliographic record
Abstract
Legal education has traditionally been defined by many boundaries. Characterized by taxonomic structures and doctrinal categories, legal education is, for the most part, still seen as inextricably linked to a particular political geography and state normativity. The purpose of this paper is to demonstrate the pedagogical benefits of shattering established boundaries in legal education. It will assess how teaching from multiple perspectives in an integrated curriculum inculcates critical thinking skills in students, better enabling them to question assumptions, uncover hidden assumptions, and graduate as independent and innovative legal thinkers. Focusing on the ‘transsystemic’ McGill Law Program, this paper will discuss the rewards of engaging students in an intellectually pluralistic and tradition-neutral legal curriculum, one that eschews silos and borders and focuses on creating agile and creative minds in future jurists who will be able to confront contemporary legal issues holistically and with a critical perspective.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".