Legal Ethics Versus Political Practices: The Application of the Rules of Professional Conduct to Lawyer-Politicians
Bibliographic record
Abstract
Canadian legal ethics has paid little attention to how the rules of professional conduct for lawyers apply to lawyer-politicians – that is, politicians who happen to be lawyers. This article addresses this issue with reference to what Canadian case law and commentary do exist, supplemented by more plentiful American materials. It proposes a distinction between conduct that is politically expedient and conduct in which lawyer-politicians’ duties as lawyers come into apparent conflict with their duties of office. Canadian case law reveals three conflicting approaches to this latter category: that the duties of a lawyer prevail, that the duties of a politician prevail, and that the two sets of duties must be balanced in the circumstances. The article then considers the legal barriers and policy considerations that may limit law societies’ discipline of lawyer-politicians. It ends by considering potential approaches and solutions, concluding that law societies should regulate lawyer-politicians’ conduct but should balance the professional obligations of those lawyers against their responsibilities as holders of public office. It also emphasizes that lawyer-politicians who do not want to be held to this standard should surrender their law licenses.
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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 | 0.022 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.103 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".