Bibliographic record
Abstract
The nation-state has typically been employed as the primary unit for political analysis in conventional international relations theory. However, since the end of the Cold War, transnational issues such as climate change along with a growing number of multinational corporations and international organizations are challenging the limits of that analytical model. This is especially true in the Arctic where indigenous organizations have reframed the region as a distinct territory that transcends national political boundaries. In Canada, the Inuit have remapped the Arctic along cultural lines in an effort to ensure all Inuit benefit from future policy implementation. At the international level, the Inuit are promoting a concept of the Arctic based on cultural cohesion and shared challenges, in part to gain an enhanced voice in international affairs. The Inuit are also utilizing customary law to ensure their rights as a people will be upheld. What is occurring in the Arctic is an unparalleled level of indigenous political engagement. The Inuit are "remapping" the Arctic region and shaping domestic and international policy with implications for the circumpolar world and beyond. This paper explores the unique nature of Inuit political engagement in the Arctic via spatial and policy analysis, specifically addressing how the Inuit are reframing political space to create more appropriate "maps" for policy implementation and for the successful application of international customary law.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".