Toleration, Synthesis or Replacement? The ‘Empirical Turn’ and its Consequences for the Science of International Law
Bibliographic record
Abstract
Abstract One of the most striking trends in contemporary international law (IL) scholarship is the turn to empirical research methods. Some see this as sign of progress, whereas others call for caution or even show hostility. With a view to the future of IL scholarship, however, all sides in this at times heated debate seem to have considerable problems keeping a clear focus on the key question: What are the implications of this empirical turn in terms of philosophy of legal science, of the social understanding of IL, and, not least, of the place of doctrinal scholarship after the allegedWende? What is needed, we argue, in order to answer this question is not yet another partisan suggestion, but rather an attempt at making intelligible both the oppositions and the possibilities of synthesis between normative and empirical approaches to law. Based on our assessment and rational reconstruction of current arguments and positions we outline a taxonomy consisting of the following three basic, ideal-types in terms of the epistemological understanding of the interface of law and empirical studies: toleration, synthesis and replacement. This tripartite model proves useful with a view to teasing out and better articulating implications of and interrelations between positions. As such the model: i) provides a framework to better situate arguments about the role of empirical studies in IL; ii) helps identify real epistemological stakes in order to overcome ‘trench wars’ – or worse: absence of dialogue and genuine argument; and iii) thus ultimately contributes to the development of a genuine basic science-of-law.
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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 | 0.072 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.004 | 0.107 |
| Scholarly communication | 0.028 | 0.053 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".