An Agreement on Enhancing International Arctic Scientific Cooperation: Only for the Eight Arctic States and Their Scientists?
Bibliographic record
Abstract
At the Arctic Council’s Iqaluit Ministerial Meeting in April 2015, the eight Arctic States decided to extend the mandate of the Task Force on Enhancing Scientific Cooperation in the Arctic (SCTF) in order to work toward a legally binding agreement on scientific cooperation. Based on the Oslo Draft of February 2015, this paper finds that the Agreement may improve the legal environment for Arctic science beyond current international law, including the law of the sea. The Agreement would lower the hurdles heretofore identified in international Arctic scientific cooperation, for example, the difficulties in accessing research areas and research facilities; and, the delays in border crossing procedures for entry and exit of scientists and their equipment and materials. Such an agreement is a good idea and should be promoted. However, non-Arctic States and their scientists may have an issue because the improved legal environment that is sought may benefit only the eight Arctic States and their scientists. In effect, the Agreement may create a two-category system where non-Arctic States and their scientists do not benefit from such improved environment. This paper examines whether they have substantial interests recognized under international law or by the Arctic scientific community by which they can claim certain benefits of the Agreement. We argue that the degree of benefits to non-Arctic States and their scientists under the Agreement should be commensurate with the degree of substantial interests accorded them by international law and by the Arctic scientific community.
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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 | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".