FORUM: LAW, EMPIRE, AND GLOBAL INTELLECTUAL HISTORY: AN INTRODUCTION
Bibliographic record
Abstract
In recent years, there has been a deepening convergence between scholarship on global intellectual history and on legal history. To take just one example, a recent book on international law, by Arnulf Becker Lorca (2014), carries “global intellectual history” in its subtitle—a stance related to the author's emphasis on the constitutive role in the field of non-European legal actors. A sustained reflection on the convergence between legal studies and global intellectual history, however, still remains a desideratum, at least in the sense that we do not yet have even a basic platform where scholars with different space/time and (trans-) cultural specialization come together to reflect on how studying legal concepts gains from global intellectual history. This forum, which results from a conference organized at Heidelberg University in 2016, attempts a preliminary intervention here. The introductory remarks are not meant to be conclusive; they invite responses.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
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".