Research on Military-Political Factors in the Transition of the Financial Center in the Sichuan-Chongqing Area Before the Anti-Japanese War
Bibliographic record
Abstract
In the modern times, a major event was the transition of the financial center in the Sichuan-Chongqing area, which was caused by the fact that Chongqing was opened as a commercial port. The transition process was basically completed before the Anti-Japanese War. Academic circles have conducted in-depth studies from some factors such as Chongqing’s geography and transport, but the researches on the military-political factors in the transition are seldom made, especially on “the War of Two Warlords Surnamed Liu”, namely, war between two warlords of Liu Xiang and Liu Wenhui, before the unification of Sichuan Government, resulting in the establishment of Chongqing financial advantages; in addition, the research on how the Nanjing Government selected and established Chongqing as the financial center of the home front is less conducted. As a matter of fact,before “the War of Two Warlords Surnamed Liu”,Chongqing-centered financial circles have the advantages, but are insufficient to cover and radiate the Chengdu-centered financial circles.The ultimate victory of Liu Xiang military-political group played a pivotal role in the long-term transition, thereafter, Chiang Kai-shek group expelled Liu Xiang group out of the nest of Chongqing because of dual political scheme of “suppressing the communist and intending on Sichuan”, furthermore, strived to establish Chongqing as the financial center of the Anti-Japanese War and the founding of the state. Finally, the goal has come true through the baptism of the Anti-Japanese War.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".