Legal Scholars Engaging with Social Anthropology: Hardships and Gains
Bibliographic record
Abstract
Abstract This special issue of the German Law Journal showcases through concrete examples the conceptual and methodological toolbox that social anthropology has to offer and the added value of applying an anthropologically informed approach to legal thinking, argumentation, and practice. The contributions address a wide variety of highly topical, controversial social issues that are at the heart of the human condition, including gender recognition for non-binary people, family disputes brought before international courts, non-majoritarian language use in administrative settings, forced migration, and the impact of climate change and infrastructural development on local communities worldwide. This introduction outlines the research program into which the contributions gathered here fit; the choice of topics; and finally, the challenges the authors face in the process of integrating their intellectual encounter with anthropology into their reflections on law. The article concludes that taking recourse to anthropology can help jurists trained in state law to develop a more refined understanding of today’s societal complexity and challenges and, ultimately, to reach more nuanced, sensitive, and just decisions.
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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 | 0.044 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.019 | 0.069 |
| Scholarly communication | 0.033 | 0.032 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".