Tinkering While the Arctic Marine Environment Totters: Governance and the Triple Polar Crisis$
Bibliographic record
Abstract
After describing how the marine environment is tottering in the face of the triple environmental crisis, this article explores the limited governance progressions at the global and regional levels in addressing the threats of pollution, climate change and biodiversity loss in the especially vulnerable Arctic. For pollution, key limitations include slow and arduous processes to add chemicals for control under the Stockholm and Rotterdam Conventions and reliance at the regional level on a fragmented array of pollution studies and projects but without specific region-wide legally binding pollution standards. For climate change, the world is not on track to meet the Paris Agreement’s temperature targets which is especially problematic for the Arctic cryosphere while the Arctic Council has largely been limited to providing general statements of concern and aspirational calls for enhanced climate mitigation and adaptation actions. For marine biodiversity losses, a pan-Arctic network of marine protected areas has yet to be developed and various implementation challenges surround the Agreement to Prevent Unregulated High Seas Fisheries in the Central Arctic Ocean including the need to ensure adequate financial, human resource and technical support. The paper concludes by highlighting some promising future governance directions. They include: the conclusion of a global treaty on plastic pollution; implementation of a new Global Framework on Chemicals – For a Planet Free of Harm from Chemicals and Waste; expected further clarifications from international tribunals on State responsibilities to address climate change; and regional implementation of the Kunming-Montreal Global Biodiversity Framework and the new agreement under the UN Convention on Law of the Sea on the conservation and sustainable use of marine biological diversity of areas beyond national jurisdiction.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".