Transnational Law as Socio-Legal Theory: The Challenges for “Law in Context” in a Divided World
Bibliographic record
Abstract
An earlier version of this paper was presented at the occasion of the 40th Anniversary of the Baldy Center for Law and Social Policy at the University of New York at Buffalo, School of Law. In tribute to the legendary contributions by the Baldy Center and its members and affiliates over the years, the paper both revisits and engages some of the core areas and orientations of the scholarship, policy and advocacy work that has been carried out as part of the largely U.S. centered Law & Society Movement (LSM) over the past decades. The paper offers a number of contextualizations in which law & society scholarship should be seen, when adopting a comparative and transnational perspective. In that regard, the paper draws connections with postcolonial legal studies, critical legal advocacy and critical work on financial capitalism.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.084 |
| Scholarly communication | 0.022 | 0.027 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".