Bibliographic record
Abstract
This paper explores challenges women leaders encounter in independent schools in Canada as they pursue the ultimate role of principal, amid structural barriers in professional and personal life, and the strategies women use to mitigate these challenges.Theories of gender, identity, career, and social justice leadership form the conceptual framework.Data is drawn from a qualitative study involving 14 female educational leaders from 2018.Findings indicate participants experienced second-generation gender bias limiting their advancement, and that social expectations played a significant role in participants' career trajectories.This is problematized using a critical lens in the discussion, contributing to a broadening theoretical understanding of obstacles faced by women leaders in independent schools and recommendations for supporting their career climb. Purpose/ObjectivesThe purpose of this study was to investigate challenges women leaders encounter in the male-dominated contexts of independent school leadership, and to examine the structural biases and gender-specific challenges that suggest a slower, interrupted, and often incomplete ascension through leadership ranks to the role of principal.The study's guiding research question was How do women faculty in independent schools enter and advance to school leadership positions?It sought to investigate barriers, strategies women employ to advance, and organizational facilitators that encourage women into leadership during this climb.It uses the findings of a recent qualitative study of women in leadership in independent schools in Canada, drawing on teacher-leader perspectives from four provinces and supplementing the data with interviews with national association directors and executive recruiters.It questions the reasons for women's disproportionately low representation in top leadership roles in these schools, explores opportunities for new ways of envisioning the role of principal, and suggests opportunities for
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".