Bibliographic record
Abstract
In the past two decades comparative law scholars have rediscovered the importance of the debate on method. For a long time left in the background as a by-product of the old controversy on the epistemic status of the discipline, the ‘struggle for the methods’ has experienced a sudden revival. But does it really make sense to keep on engaging in a wearying confrontation among the various possible paradigms, once one recognizes that, as Patrick Glenn observed, ‘the history of comparative law is not one of adherence to a methodological norm but rather one of deviation and variety’? It makes sense, indeed, because ‘eclecticism’ as a theoretical perspective is itself the sign of the times and cannot strive for universal validity. Looking back at the history of comparative law, one is struck by the circumstance that throughout the formative era, the idea that obtained most credit in European intellectual circles was the opposite one, namely that ‘there is a comparative method’ (rectius: ‘Comparative Method’, as it was once written). This chapter is aimed at bringing back to light some distinctive traits of the original discourse on the ‘comparative method’ and highlighting the importance of the ‘scientific paradigm’ for the acceptance of comparative law as an autonomous subject of legal research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.006 | 0.056 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".