The Comparison of Gender Distribution among School Principals and Teachers in Taiwan, Japan, and South Korea
Bibliographic record
Abstract
In 2008, OECD released one multi-national report about one important survey of its twenty-two member countries, the title of this report is “Improving School Leadership: Volume 1 Policy and Practice”. This report analyzed one specific common trend of its members, which is the “unique gender divide among school principals and teachers”. That meaning of this phenomenon is, in the context of school education in some OECD countries, the ratio of female teachers among all teachers is much higher than male teachers. However, the contrast point is, the ratio of female school principals is significant lower than male principals. This phenomenon is especially significant in the East Asia countries. For example, the percentage of female school principals is significantly lower than male principals when we observed the longitudinal trend in Taiwan. In Japan, the ratio of female teachers in primary schools is 62.7% and the ratio of female teachers in junior high schools is 54.8%, but the ratio of female primary school principals in Japan is only 17.9% of the total principals. When we look at the ratio of female principals in junior high schools in Japan, it is even lower; the ratio is only 5%. Therefore, the main purpose of this study is to explore the unique gender divide among school principals and teachers in Taiwan, Japan, and South Korea. The research methods include document analysis and descriptive statistical analysis. The statistical data is collected from Ministry of Education in Taiwan, Japan, and South Korea. The supplemental data is collected from OECD dataset. This study compares the gender distribution among school teachers and principals in these three countries. In the last section of this study, we discuss the findings and their relationships with social cultures in Taiwan, Japan, and South Korea. Policy and practice implications are offered to rethink the hindrance of female teachers’ promotion. How to enhance female teachers’ participation in school leadership is another important issue for future studies.
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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 | 0.001 | 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".