Earth system law: Exploring new frontiers in legal science
Bibliographic record
Abstract
The Anthropocene requires of us to rethink global governance challenges and effective responses with a more holistic understanding of the earth system as a single intertwined social-ecological system. Law, in particular, will have to embrace such a holistic earth system perspective in order to deal more effectively with the Anthropocene's predicaments. While a growing number of scholars have tried to reimagine law and legal scholarship in a more holistic way, these attempts remain siloed. What is required is a shared epistemic framework to enable and enhance collaborative intradisciplinary and interdisciplinary research and co-learning that go hand in hand with thorough transdisciplinary stakeholder engagement. We argue that the nascent concept of earth system law offers such an overarching epistemic framework. This article serves as an invitation to fellow explorers from various legal fields, other disciplines, and from a wide range of stakeholders to explore new frontiers in earth system law. Our aim is to further stimulate the study of earth system law, and to encourage collaboration and co-learning in a fertile epistemic space that we share.
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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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.067 |
| Scholarly communication | 0.015 | 0.037 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".