Bibliographic record
Abstract
In a characteristically learned and provocative essay, Professor Matthew Finkin, one of the organizers of this symposium, has raised the question of whether "legal scholarship," properly understood, encompasses the contributions of such hybrid, dissident, and essentially non-doctrinal approaches as law and economics, critical legal studies, critical race theory, and feminism.'He concludes that it does not.This controversy is no less important to legal academics than, say, the Albigensian heresy to theologians (and not very different, either).However, it is unlikely to be resolved in the present context.Nor am I persuaded that it should be or that binary distinctions between law/non-law and scholarship/non-scholarship are either possible or useful.I will, therefore, resist any temptation to cast out and publicly execrate charlatans, sectarians, and schismatics and will treat "legal scholarship" as a broad church that welcomes all who choose to identify with it.That said, I am grateful to Professors Sanford Jacoby and Matthew Finkin for their invitation to reflect on the existence of a Canadian "national tradition" in labor law scholarship.I was involved some years ago in an attempt to construct a general taxonomy of Canadian legal scholarship.2 Much has happened since then to legal
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.087 | 0.026 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 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".