The Effect of School Principals’ Distributed Leadership Behaviours on Teachers’ Organizational Commitment
Bibliographic record
Abstract
The purpose of the study is to explore the effect of school principals’ distributed leadership behaviours on teachers’ organizational commitment in the views of teachers employed in high schools. The study is a descriptive research designed as a correlational survey model and the research population consists of teachers in high schools in the provincial centre of Diyarbakır, a large city in south-eastern Turkey. The study is conducted with 275 teachers, selected by simple random selecting method. In the research, conducted in the views of high school teachers, descriptive statistics are employed to determine the distributed leadership behaviours of the participant principals and the teachers’ organizational commitment levels and a regression analysis is used to predict the participant teachers’ organizational commitment arising from the distributed leadership behaviours of the school principals. As a result of the study, the distributed leadership behaviours of the school principals are found at a high level in the following factors: open leadership, school culture, employee involvement and dynamics, whereas the teachers’ organizational commitment levels are found low in the compliance factor but as for identification and internalisation factors, they are found high. Moreover, it is determined that teachers’ organizational commitment can be statistically predicted from school principals’ distributed leadership behaviours.
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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 | 0.003 | 0.010 |
| 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 | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".