Catalytic agents? Lon Fuller, James Milner, and the lawyer as social architect, 1950–69
Bibliographic record
Abstract
In the 1949–50 academic year, James Milner studied with Lon Fuller at Harvard Law School. There, he was influenced by Fuller’s belief that law schools should aim to produce ‘social architects,’ graduates capable of solving individual and societal problems by wielding a variety of tools derived from diverse legal processes. In the years following his time at Harvard, as a professor at the University of Toronto Faculty of Law from 1950 to 1969, Milner sought to develop and implement the social architect ideal, through his scholarship, teaching, and casebook writing in contract law and land planning, his presidency of the Association of Canadian Law Teachers, and through curricular initiatives within the faculty. Despite Milner’s efforts, his attempts to bring Fuller’s social architect ideas never flourished at the University of Toronto. This article details Milner’s attempts, illuminating him as a key intellectual figure at the University of Toronto Faculty of Law, and reflects on the factors of historical contingency that led to the failure of these ideas to take hold.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.049 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".