Digital Leadership Relationships Among School Administrators with the Effectiveness of Academic Work in the New Normal Era
Bibliographic record
Abstract
This research article aims to 1) study the digital leadership of educational institution administrators under the Sukhothai Primary Educational Service Area Office, Area 2, Thailand 2) study the effectiveness of academic work in the new normal era of administrators under the Sukhothai Educational Service Area Office, Area 2, Thailand. Sukhothai Primary Educational Service Area Office 2, Thailand and 3) study the relationship between digital leadership of school administrators and academic work effectiveness in the new normal era under the Sukhothai Primary Educational Service Area Office 2, Thailand. This is quantitative research. The sample group is educational institution administrators. and academic teachers of affiliated educational institutions Sukhothai Primary Educational Service Area Office 2, 230 people. The research tool is a questionnaire on digital leadership of school administrators and academic effectiveness in the new normal era. It is a 5-level rating scale questionnaire. Data is analysed using basic statistics to find the average. and standard deviation and the relationship was analysed using the Pearson correlation coefficient. The results of the research found that 1) the digital leadership of educational institution administrators under the Sukhothai Primary Educational Service Area Office, Area 2, Thailand is overall at a high level; 2) academic work effectiveness in the new normal era of administrators under the district office Sukhothai Primary Educational Service Area Office 2, Thailand, overall is at the highest level, and 3) the relationship between digital leadership of school administrators and academic work effectiveness in the new normal era under the Office of Sukhothai Primary Educational Service Area 2, Thailand, was found. that there is a statistically significant relationship at the .01 level
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".