Introduction: The Disenchantment of Critical Legal Thought?
Bibliographic record
Abstract
The topic of legal pluralism has puzzled the sociology of law since its origins. To quote an early example, the aim of Eugen Ehrlich was to grasp the “colourful diversity of living law.” Max Weber, too, made a distinction between law beyond the state, on the one hand, and state law, on the other, the latter being the formal object of normative legal science. The concept of legal pluralism, later formulated in order to capture this diversity, gave rise, as is well known, to a specific line of inquiry in the domain of law and society; it has found concrete expression particularly in the Journal of Legal Pluralism, published under this title since 1981, and has triggered energetic debates. Jean-Guy Belley has made a crucial contribution to these debates, in particular by writing the entry on “pluralisme juridique” for the Dictionnaire encyclopédique de théorie et de sociologie du droit, published 1988. Years before, he had begun an ambitious research undertaking centred on legal pluralism as a fundamental paradigm for jurisprudence, first with a doctoral dissertation under the supervision of Jean Carbonnier and later as a professor in contract law and sociology of law at McGill University. This scholarly relationship to legal pluralism developed first in the domain of sociology of law, through a comprehensive approach that culminated in 1998 with the publication of Le contrat entre droit, économie et société.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".