Sustainable Leadership in Private International Schools: Lessons from Kuwait
Bibliographic record
Abstract
The rapid, global growth of the private international school sector has raised demand for qualified school administrators to lead schools in that sector. Many administrators hired into that sector face particular challenges when coming from public systems in other countries. The question is in what ways do gaps between the training and experience of recruits and the demands of the sector compromise the sustainability of effective leadership in private international schools. There are implications for policy development around training and support for leaders in this sector as, unlike many national public systems, it lacks a supply of specifically trained leaders. This article presents a qualitative study of semi-structured interviews with 17 international school leaders who moved from national public systems abroad to private international schools in Kuwait. The major themes that emerged in those interviews were the challenges faced by leaders in adjusting to differing governance structures, the business and marketing aspects of private international schools, and managing the transience of staff. A number of similar themes have been cited in research on international schools in other world regions, although some expressions of those themes are particular to Kuwait. This article concludes with a discussion of the need to provide sustainable norms for leadership across the international school sector, with training and support to help school leaders transition and work more effectively in the sector.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".