A Situational Analysis of Women in Higher Education Leadership Positions in Kenya
Bibliographic record
Abstract
A Situational Analysis of Women in Higher Education Leadership Positions in Kenya Doctor of Philosophy (2019) Evelyn Jeruiyot Kipkosgei Department of Social Justice Education University of Toronto ABSTRACT Gender imbalance among senior university academics is an acknowledged problem in many countries, including Kenya. This thesis gives a situational analysis of women academics in senior leadership positions in institutions of higher education in Kenya. This study sought to determine the requisite attributes that propelled women to higher management positions in institutions of higher education in Kenya; to identify strategies adopted by women to attain leadership in higher education in Kenya; and to explore the lessons that can be drawn from the experiences of women in higher education leadership positions in Kenya. The research is anchored in feminist and leadership theories. The study uses data collected from 18 participants in senior leadership ranks derived through purposive and snowballing sampling technique across 32 public universities. A qualitative approach of in-depth semi-structured interviews aided by a questionnaire was used to collect primary data whereas secondary data was obtained by document analysis. Preliminary findings indicate that success largely depends on a combination of individual’s initiatives, institutional structures, and governmental interventions. Results indicated that women success in leadership positions at higher education institutions in Kenya is attributable to individual paradigm shifts, external networks, pro-women movements, and enforceable affirmative action plans. Strategies employed by women to attain leadership were identified as continuous education, determination and tenacity, performativity, goodwill, and the use of role models and mentors. Major attributes to emulate were: defining marks of leadership and identity, collaboration, spirituality, and performativity. It was concluded that women in this study merited their success since they possessed the required qualifications and experience. They had the ambition, drive, and patience to succeed against all odds. Going by their small numbers in managerial positions, there seems to be other underlying factors over and above qualifications that affect women career mobility. The study recommended an urgent and deliberate effort to address structural and sociocultural hurdles constricting the upward mobility of women. Recommendations include formulation of implementable affirmative action policies and introduction of egalitarianism in education curriculum. It is recommended that women get trained on to negotiation skills which exclude counterproductive confrontational approaches.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".