China in the Arctic: Assessing Positions of Arctic States towards increasing Chinese Presence
Bibliographic record
Abstract
The bachelor's thesis China in the Arctic: Assessing Positions of Arctic States towards increasing Chinese Presence deals with the issue of Chinese presence in the Arctic region. The thesis examines and compares the positions of individual Arctic states on this presence and its effects. Content analysis and a comparative method were used it the thesis, while the parameters of the comparison were the statements of the Arctic states on the Chinese factor in the Arctic (statements of representatives of these states and written statements), participation in summits organized by the People's Republic of China on the Arctic region, joint projects in areas and extent of mutual trade. The aim of the thesis is to divide the attitudes of the seven Arctic states into positive, negative or neutral. The conducted research according to all mentioned parameters defined the key points for this evaluation, which confirmed the hypothesis of the thesis. It is indeed possible to consider Russia as China's partner in the Arctic region, especially with regard to Russian proclamations and its cooperation in the region. The United States and Canada have taken a negative stance, both through their statements and by rejecting joint projects and not participating in Chinese summits. European countries, i.e. Finland, Sweden,...
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".