The Incorporation of Government Lawyering in the Teaching of Legal Ethics in Canadian Law Schools
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Government lawyers, and the specific legal ethics issues that arise in their practices, remain largely overlooked in Canadian legal education. The authors argue that government lawyering should be better incorporated into legal ethics curricula in law schools, for both practical and conceptual reasons. Most importantly, understanding issues unique to government lawyering helps students better understand core concepts in legal ethics, and thus better prepare for the practice of law both in the public and private sectors. While law teachers face serious challenges in incorporating government lawyering into legal ethics education, many of those challenges can be confronted and ameliorated. The authors conclude that the incorporation of government lawyering into the teaching of legal ethics in law schools should be embraced by law teachers in order to better prepare their students for practice, given that ethics and professionalism lie at the core of the legal profession.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it