Bibliographic record
Abstract
ABSTRACT Recent scientific studies suggest that the destabilisation of the earth's climate and biodiversity loss are not separate, but interdependent phenomena. In this context, some have proposed the creation of a ‘Global Safety Net’ of ecoregions that should be preserved to stop further biodiversity loss, preventing at the same time the growth of CO2 emissions produced by deforestation and allowing natural carbon removal. In this article, I suggest that a first step to achieve this might be to replace permanent sovereignty over natural resources in these areas with permanent guardianship. I propose to take some inspiration from a model that has already been implemented over an entire continent with a fair degree of success. In 1959, the Antarctic Treaty froze the sovereign claims of seven countries over Antarctica. However, these countries plus 47 others today have been remarkably successful at jointly preserving the continent for peace, science, and the protection of the environment, especially since the signature of the Environmental Protocol in 1991. After outlining some principles that could give form to a Global Environmental Protocol for Ecoregions, I address a series of objections and offer some concluding remarks.
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.
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 | 0.018 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.055 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".