Bibliographic record
Abstract
Many representations and narratives about the Arctic and Arctic politics carry misconceptions and flawed generalisations. Usually, the term ‘Arctic’ is used as an unproblematized – by default – geographical frame, without considering why this particular ‘Arctic’ framing was chosen and what this choice entails. Yet, considering geographical framing is important as the very choice behind it already carries a political agenda. This paper argues that focussing on the interplay between the different ‘scales’ of the Arctic can shed light on the politics of Arctic scales and resulting discourses. To that end, I analysed every Arctic strategy published by both Arctic and non-Arctic actors. I concentrated on strategies that specifically focused on the Arctic region as a whole, to draw comparisons from these framings. Using thematic analysis, I examined how the Arctic is construed and how the scale at which Arctic issues are framed comes with political consequences. In doing so, I wish to underline the interplay scales and underlying political processes. I conclude by stressing that recognising and attending to the production of ‘scale’ as an inherently political process greatly improves our understanding of regional politics.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".