Constructing Rights of Nature Norms in the US, Ecuador, and New Zealand
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Governments around the world are adopting laws granting Nature rights. Despite expressing common meta-norms transmitted through transnational networks, rights of Nature (RoN) laws differ in how they answer key normative questions, including how to define rights-bearing Nature, what rights to recognize, and who, if anyone, should be responsible for protecting Nature. To explain this puzzle, we compare RoN laws in three of the first countries to adopt such laws: Ecuador, the US, and New Zealand. We present a framework for analyzing RoN laws along two conceptual axes (scope and strength), highlighting how they answer normative questions differently. The article then shows how these differences resulted from the unique conditions and processes of contestation out of which each law emerged. The article contributes to the literature on norm construction by showing how RoN meta-norms circulating globally are infused with differing content as they are put into practice in different contexts, setting the stage for international norm contestation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it