Evaluation of Implementation Principal Leadership Management During the Covid-19 Pandemic
Bibliographic record
Abstract
This research is aimed to investigate and evaluate the implementation of principal leadership management during the pandemic of Covid-19. The Covid-19 outbreak in various countries has changed the traditional face-to-face learning pattern to online learning. Changes in face-to-face learning patterns to online learning must be followed by changes in work patterns for the principal as a manager. The question is, has the principal implemented leadership management following the standards required to carry out online learning during the COVID-19 pandemic? This evaluation study uses a discrepancy model (gaps), which determines the differences in the implementation of principal leadership management with the standards in the work guidelines of principals during the COVID-19 pandemic. The evaluation results concluded that the principal's leadership management implementation was not following the standards, that had implications for the quality of online learning implementation and student learning outcomes. Further research regarding the effectiveness of principal leadership management still needs to be done to improve school management in online learning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".