Bibliographic record
Abstract
Purpose In response to the growing need for educational leaders who possess ethical, critical and reflective qualities, a training program was developed based on ethics as a reflective critical capacity and on Starratt's three‐dimensional model. This paper aims to describe the impact of the program on ethical decision making and on educational leaders’ ethical competencies. Design/methodology/approach A three‐year action‐research study was conducted with three groups of educational administrators, totalling 30 participants. Mixed methods were used for data collection: a pre‐ and post‐training questionnaire, individual semi‐structured interviews and group interviews. The questionnaire data were analyzed using SPSS software and interview data were analyzed using thematic analysis. Findings Results from the pre‐test indicate that, prior to the training program, participants rarely possessed all three ethical dimensions. Post‐test results show how participants experience a significant readjustment process characterized by three different stages which have been called the transformative cycle. Qualitative results show the impact of the training program on improved ethical awareness, judgement structuring, a sense of responsibility, and overall professional conduct. No significant difference is observed between male and female participants but statistically significant differences are found according to number of years of experience and to work situation. Practical implications Developing sound ethical expertise appears to be promising in training future educational administrators and in improving their leadership skills. Originality/value This study is original in many aspects. Theoretically, it is based on a self‐regulated rather than hetero‐regulated approach to ethics and calls for descriptive rather then normative foundations to ethical leadership. With regard to its methodology, it used mixed methods adapted to action research as well as original data collection instruments.
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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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".