The Dean Who Went to Law School: Crossing Borders and Searching for Purpose in North American Legal Education, 1930–1950
Bibliographic record
Abstract
This article is about the making of modern legal education in North America. It is a case study of the lives of two law schools, the University of Alberta, Faculty of Law and the University of Minnesota Law School, and their respective deans, Wilbur Bowker and Everett Fraser, in the decades surrounding the Second World War. The article follows Bowker’s unorthodox route to Alberta’s deanship via his graduate training under the experimental “Minnesota Plan” — Fraser’s long-forgotten effort to place public service at the centre of American legal education. In detailing an overlooked moment of transition and soulsearching in North American legal education, this article underlines the personalities, ideologies, circumstances, and practices that combined to forge the still dominant model of university-based legal education across the continent. Highlighting the movement of people and ideas, this study corrects a tendency to understand the history of law schools as the story of single institutions and isolated visionaries. It also reveals the dynamic ways in which law schools absorbed and refracted the period’s ideological and political concerns into teaching practices and institutional arrangements. In bold experiment and innate conservatism, personal ambition and institutional constraints, and, above all else, faith in the power of law and lawyers, the postwar law school was born.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.025 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".