Defying the Law of the Land: The Lawyer's Role in Civil Disobedience in Canada
Bibliographic record
Abstract
A lawyer’s role in relation to the issue of civil disobedience is far from settled. Lawyers advocate for values such as “truth” and “justice;” however, they are also instructed to respect the rule of law and the legislature’s role in creating laws and policy. Due to the tension between values and law, lawyers must choose which clients to represent as well as determine what constitutes effective counsel. The Charter of Rights and Freedoms adds another complex dimension to this dilemma because of the fine line between “civil disobedience” and the assertion of Charter rights through test case litigation. It is easy to look back at historical moments, such as the civil rights movement, and recognize when civil disobedience is justified. However, we do not always have the luxury of hindsight, and we must not deny that there are legitimate reasons to practice civil disobedience today. The legal history of Dr. Henry Morgentaler is an example of the juxtaposition between advocacy and policy. Throughout his legal battles, Dr. Morgentaler was labelled a criminal who performed civil disobedience, but who is now highly regarded as someone who fought for Charter rights. Therefore, with competing obligations to one’s client, fellow lawyers, and the public in general, lawyers must chart their own ethical course in these matters.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.072 | 0.019 |
| Scholarly communication | 0.021 | 0.004 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.012 | 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".