Bibliographic record
Abstract
The obligation to report to a law society a breach by another lawyer of ethical standards has traditionally been confined to the most serious forms of violations, such as theft. The obligation has been expanded under the recent Federation of Law Societies Model Code, now in force in many provinces. Under Rule 7-1-3(e) of the Model Code there is an obligation to report conduct that raises a “substantial question” with respect to a lawyer’s honesty, integrity or competence. A combination of Rule 7-1-3(e) and the availability of detailed information on the activities of firm members may mean that those in management roles at law firms will increasingly be under an obligation to report matters which up to now have not been frequently reported. Curiously, Ontario has decided not to include the Model Code’s Rule 7-1-3(e) its new Rules. However, it is submitted that even given this absence, the fact that power to discipline is linked to the wide phrase “professional misconduct” means that law firms in Ontario are also obliged to report conduct of their members that raises a “substantial question” with respect to that member’s honesty, integrity or competence. Still, it would be better if Ontario’s Rules were amended to include the Model Code’s 7-1-3(e) and to make the issue more clear.
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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.009 |
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".