Bibliographic record
Abstract
Globalization and technology have changed the practice of law in dramatic ways. This is true not only in the U.S. and Canada, but around the world. Global regulatory trends have begun to emerge as lawyer regulators have had to respond to new developments. In 2012, Australian regulators Steve Mark and Tahlia Gordon and the author, who is a U.S. academic, documented some of these global trends in lawyer regulation. See Laurel S. Terry, Steve Mark, & Tahlia Gordon, Trends and Challenges in Lawyer Regulation: The Impact of Globalization and Technology, 80 Fordham L. Rev. 2661 (2012), https://works.bepress.com/laurel_terry/95/. Their article concluded that regulators face issues in common regarding “who” is regulated, “what” is regulated, “when” and “where” regulation occurs, “how” it occurs, and “why” it occurs. The current article examines Canadian lawyer regulation in light of the global trends Terry, Mark, and Gordon previously identified. The current article asks whether there is evidence in Canadian lawyer regulation of these same who-what-when-where-why-and-how issues. The article concludes that these trends are indeed present in Canada and explains why it is important for Canadian lawyers, regulators, clients, and other stakeholders to be aware of these global trends. The article also addresses the issue of whether these trends matter in a jurisdiction such as Saskatchewan that is not a global financial center on the order of New York, London or Toronto. The answer the article provides is “yes” – these trends are relevant to Saskatchewan and to jurisdictions throughout the world that care about lawyer regulation.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.038 | 0.002 |
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".