From Attorney General to Backbencher or Opposition Legislator: The Lawyer’s Continuing Duty of Confidentiality to the Former Client
Bibliographic record
Abstract
This note uses a recent incident from Manitoba to reflect on the professional duty of confidentiality owed to the Crown by a former Attorney General as lawyer. The duty of confidentiality survives the lawyer-client relationship. As a fiduciary, the lawyer cannot disclose or use the client’s confidential information for her own benefit or the benefit of a third party, or against the client. These obligations constrain the former Attorney General in her conduct as an opposition legislator and suggest that she should not accept an appointment as Justice critic for her caucus. While parliamentary privilege protects the former Attorney General who breaches these obligations in the legislature from professional consequences, as an opposition legislator she is particularly vulnerable to consequences within the legislature.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.012 | 0.017 |
| Insufficient payload (model declined to judge) | 0.008 | 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".