Study on the Distribution of Compulsory School Teacher’s Resources in Guizhou
Bibliographic record
Abstract
The student-teacher ratio of compulsory schools in Guizhou has declined. The student-teacher ratio of junior middle schools is higher than that of primary schools. The student-teacher ratio of urban schools is the highest of all. The teachers’ educational level of compulsory schools in Guizhou is higher than before. The structure of teachers’ professional titles is unreasonable in that the proportion of teachers with high professional titles is too low. The workload of teachers is too heavy to meet the demand of diversified running of schools in Guizhou. To improve the quantity and quality of teachers in rural compulsory education schools, as well as the the compulsory education quality in Guizhou, it is necessary to take the following measures: optimizing the authorized size of compulsory school teachers, approving the student-teacher ratio, continuing to implement the Special Contracted Teachers’ Policy, reforming the evaluating policy of the professional titles and recruiting caretakers and so on.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".