Lawyering at the Intersection of Public Law and LegalEthics: Government Lawyers as Custodians of the Ruleof Law
Bibliographic record
Abstract
Government lawyers are significant actors in the Canadian legal profession, yet they are largely ignored by regulators and by academic scholarship. The dominant view of lawyering fails to adequately capture the unique role of government lawyers. Government lawyers are different from other lawyers by virtue of their role in creating and upholding the rule of law Most accounts of government lawyers separate public law duties of government from ethical duties of lawyers; for example, acknowledging the "public interest" role ofgovernment lawyers but asserting that this has no impact on their ethical duties as lawyers. Instead of this compartmentalized approach, this article advocates a unified vision of the roles and responsibilities of government lawyers. Examining the role of government lawyers should start byrecognizing that they operate at the intersection of public law and legal ethics. Government lawyers are not simply lawyers working in the public sector Nor are they simply public servants who happen to be lawyers. They are both lawyers and public servants at the same time. This creates unique tensions, problems and responsibilities for government lawyers. Government lawyers do owe a higher ethical duty than other lawyers which is explained through the concept ofgovernment lawyers as custodians of the rule oflaw. Existing forms of regulation are adequate for public protection but insufficient in public law terms to address concerns regarding the exercise of public power Additional forms of accountability should be created including the development of specific codes of conduct for government lawyers, proactive disclosure and the creation of an Office of Professional Responsibility within federal and provincial departments of justice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.040 | 0.057 |
| Scholarly communication | 0.033 | 0.025 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.017 | 0.022 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".