Comparative Perspectives on Lawyer Regulation: An Agenda for Reform in the United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Regulation shapes every area of modern economic life. Getting regulation right-knowing when it is necessary, what it should accomplish,and what form it should take-is a critical part of policymaking in every society.Developing an effective oversight structure requires a complex analysis of each society's particular historical, cultural, and legal foundations.Regulation of the practice of law is no different, although it has received surprisingly little public attention in the United States and Canada.That is not for lack of problems, and other countries with similar legal systems, such as Australia and England and Wales, have begun to do better at addressing common oversight failures.This Article explores why problems in American and Canadian legal regulation persist, and identifies reform strategies that build on recent innovations from abroad.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it