Remote control? Chinese satellite infrastructure in and above the Arctic global commons
Bibliographic record
Abstract
Abstract China is expanding its Arctic presence by developing infrastructure in the global commons that intersect with the region. Operations in outer space, the deep sea and cyberspace minimise the need for terrestrial footholds and generate data, a virtual resource. To analyse the epistemic and geopolitical consequences of developing the Arctic global commons as a vertically and digitally integrated volume, we examine a critical form of Chinese ‘remote infrastructure’: optical, synthetic aperture radar, and navigation satellites. We argue that first, by generating data about the Arctic, these instruments turn China into a regional knowledge producer. Second, as remote observations outnumber field observations, Chinese polar science may shift the regional balance of knowledge towards spaceborne and marine observations. Third, China's emergence as an Arctic knowledge producer may motivate the state to contribute to regional governance as remote sensing and large‐scale, computationally intensive techniques become privileged decision‐making tools. To transcend the terrestrial and maritime fixes that predominate research on China and the Arctic, we call for greater attention to the influence of epistemic capacities on geopolitics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".