Bibliographic record
Abstract
n this companion volume to the collection of interviews in Volume I on the Great Transition in Legal Education Manitoba 1 , the editors have prepared a collection of documents.The aim is to provide the reader with the opportunity to read directly, over the course of a century, the thoughts of leaders of the profession and of the law school as they reflect on the past and future of legal education.There is a saying that "policy is personnel".The most influential factor in the calibre of a law school are its professors and students: not its curriculum, not its physical plant.The first document in this edition, "Full-Time Teachers, Recorders & Librarians of the Manitoba Law School and of the Faculty of Law, University of Manitoba", provides a list of the full-time teachers of the law school from it earliest years to the present day. 2 The excerpts from the Canadian Bar Association debates from almost a century ago illustrate that the debate between university based education and apprentice training is nothing new. 3 The CBA reports recommended that one follow the other.The content of the discussions reinforces the contention of Ecclesiastes that there is nothing new under the sun.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.419 | 0.207 |
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".