Educational Leadership in Post-Colonial Contexts: What Can We Learn from the Experiences of Three Female Principals in Kenyan Secondary Schools?
Bibliographic record
Abstract
Leadership matters in the engagement and achievement of students. Much of the research in this area has emanated from western contexts and there is a growing demand for research and knowledge generated from emerging areas of the world. This qualitative study through the use of narratives, examines the experiences of three female secondary school principals in Kenyan secondary schools to gain deeper insights into leadership practices and theorizing within a post-colonial context such as Kenya. Utilizing a decolonizing education and social justice leadership discursive framework the tensions and complexities of their leadership practices are explored. Educational leaders in developing countries face problems that are uniquely different from their counterparts in Western countries and as such leadership practices and theorizing must be contextualized. Findings of the study support existing research on the perpetuation of colonized approaches to education, existence of a “managing” view of leadership, tensions in practice regarding the manifestation of social issues in schools, and the need for leadership development grounded in Kenyan knowledge and experiences. While these findings can inform leadership discourses and practices, further research is warranted on a larger scale with greater diversity of participants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".