Policy Changes and Reason Analysis of Bureaucratization of Native Officers in Guizhou in Qing Dynasty
Bibliographic record
Abstract
Throughout the whole Qing Dynasty, there had been great twists and changes of the bureaucratization of native officers in Guizhou area—with the changes in military and political situations, it had gone through several different policy periods of appeasement in Shunzhi period, the active flow-changing of Wu Sangui, resumption of conciliatory policy in Kangxi period, the comprehensive and all-dimensional native officers bureaucratization in Yongzheng period and the policy rehabilitation of Koreans, Miao nationalities and frontier in Qing Dynasty. As the important strategic pivot, the policy changes of bureaucratization of native officers in Guizhou stands for an epitome for the minority policy at boarders under the domination of central regime for the great unity, the changing reasons of which are not only closely related with the objective military and political situations, but also related with the ruling styles of the emperors themselves. The national strategies of the mainland-frontier integration of Qing Dynasty were constant; the phased policy changes of bureaucratization of native officers were only different in manners and measures. It is just in this phased changes and gradually forwarding process that the bureaucratization of Guizhou realized the general goal of matching politics, economics and culture with the mainland.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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) | 0.002 | 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".