Bibliographic record
Abstract
In 1996, the Ottawa Declaration established the Arctic Council (AC) with eight states, all of which have territory in the Arctic. The AC is the leading intergovernmental forum in terms of sustainable development and environmental protection in the Arctic. This forum promotes cooperation, coordination, and interaction among the Arctic States and among Arctic indigenous communities. The Netherlands became an Observer in 1998, whereas China joined the AC in 2013. Both states are concerned about the impact of climate change in the Arctic region and the different kinds of consequences it may have for their state. Both states contribute to the AC with scientific knowledge, and they participate in several Working Groups. Critical discourse analysis (CDA) helps explore and understand the meaning of the role of the Netherlands and China as Observers, leading to an answer to how both states use science diplomacy (SD) as a strategic tool and potentially revealing hidden agendas in terms of the nature of their economic interest. Although CDA did not unfold hidden agendas of both states, what can be said is that probably both states are using SD as a strategic tool to shift attention away from their own (economic) incentives.
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.084 | 0.039 |
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".