Research on Ethnic Identity of Zhuang Ethnic in Red River Basin of Guangxi
Bibliographic record
Abstract
The Questionnaire on Ethnic Identity of Zhuang Ethnic in Red River Basin of Guangxi is formulated based on Multi-Ethnic Identity Questionnaire Design of Phinney, integrated with the results of previous interviews to Zhuang Ethnic, 490 samples with different gender, ages, regions, occupations and educations were randomly selected in this questionnaire research. It is found in the research that 50-year-olds rank highest on the identity degree of the ethnic identity and the dimension of sense of ethnicity belonging, 20-year-olds rank lowest; farmers rank highest on the identity degree of the dimension of sense of ethnicity belonging, public sector staffs rank lowest; secondary and polytechnic education group ranks highest on the identity degree of the dimension of sense of ethnicity belonging, primary education group ranks lowest; there is no difference among the remaining. Effectively intensifying the ethnicity education of Zhuang Ethnic and enhancing the cultural heritage protection of Zhuang Ethnic perhaps will be the effective ways to change the unsatisfactory situation of heritage of current ethnicity culture.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".