Bibliographic record
Abstract
This Chapter appraises the range and depth of Patrick Glenn’s scholarly legacy by exploring some of the many lessons that can be drawn from his opus magnum Legal Traditions of the World. To this purpose, the chapter will focus on three key notions underlying Glenn’s chefs-d’œuvre: Law, Tradition, and Conciliation. The argument is that Glenn’s findings have in multiple ways enlightened the understanding of what the law is (outside and also inside the West), as well as the relentless dynamics within and between legal traditions. Through these findings, Glenn has also provided us – his friends, colleagues, readers – with a powerful intellectual tool to pursue his conciliatory dream towards a world of tolerance and diversity.
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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 | 0.027 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.059 |
| Scholarly communication | 0.016 | 0.048 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 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".