Bibliographic record
Abstract
Recent years have seen the unfolding of an increasingly fierce Methodenstreit, a battle of method, in legal scholarship. The battle revolves around competing conceptions of legal science – about its proper research object, theory and method. Some describe this development as an empirical turn (e.g. Shaffer and Ginsburg 2012), thereby referring to the apparently growing group of scholars from both within and outside law turning away from traditional doctrinal and towards novel empirical approaches to the legal field. Much is at stake in this battle. In the first instance, conflicting truths about law and the legal field. But this soon leads to changes on the ground. Ultimately, a successful empirical turn will significantly reshape the contours of legal education, which due to the size and importance of the legal profession will affect broader society. Nevertheless, the empirical turn is poorly understood. Discussions are marred by weak conceptualizations of “the empirical”, and by strong bipartisan sentiments pro et con. This puts discussion at a frustrating standoff that cannot be remedied merely with more first-order empirical or doctrinal legal scholarship. What is required is a critical and reflective meta-study of the empirical turn as such. This in turn requires a combination of a philosophical analysis of what is or should meant by terms such as empirical and turn, with an empirical analysis of the actual scope of the alleged empirical turn and of the factors driving it. Logically, the former is a precondition of the latter and this contribution aims to provide such an analysis. Proceeding a priori and building on previous work (Holtermann 2019; Holtermann and Madsen 2016a; 2016b), the contribution aims to provide the conceptual framework necessary for an understanding of what is or can reasonably be meant by the empirical turn in legal scholarship, and for a subsequent empirical study of its scopes and of its drivers and inhibitors.
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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 | 0.036 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.007 | 0.101 |
| Scholarly communication | 0.019 | 0.044 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".