Bibliographic record
Abstract
Austro-Hungarian Activities in China, 1894-1914 PhDr. Jan Kočvar My Ph.D. thesis evaluates Austro-Hungarian activities in China between 1894 and 1914, especially their political aspects. I would like to explain the nature of Austro-Hungarian contacts with China and their significance for the Dual Monarchy. The main source for my thesis was constituted by the materials in Haus-, Hof- und Staatsarchiv in Vienna. Austria-Hungary concluded diplomatic relations with China in 1869, but her position in China remained weak. After the Sino-Japanese War, the Far East became a focus of interest of the Great Powers, and in 1896 was appointed the first Austro-Hungarian Minister to China. During the Scramble for Concessions in late nineties, Austro-Hungarian navy conducted survey of Chinese littoral and contemplated an establishment of a naval base in China, but finally rejected this idea. Austro-Hungarian trade and other interests in China were too insignificant to justify such an action. The peak of Austro-Hungarian presence is connected with the Boxer Uprising of 1900. Austria-Hungary didn't contribute to its genesis. During the uprising, Austro-Hungarian sailors were fighting in besieged Legation Quarter in Beijing, as well as in the metropolitan province of Zhili. Thereafter, Austro-Hungarian diplomacy took...
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".