Leadership and information technology in higher education : a qualitative study of women administrators
Bibliographic record
Abstract
This study examines issues related to women's leadership and administrative roles in higher educational settings where information technologies have a prominent function. In so doing, it addresses a relatively new area in leadership. The study focuses on four main questions: Are there parallels between feminist leadership styles and a new evolving field for leaders in technology? Is there something about technology that lends itself to female leadership styles? Has technology helped validate women's styles of leadership? What does that mean to women entering the field now? Six women administrators, interviewed over a three-month period spoke on such issues as formal and informal relationships, collaborative team building, and getting the job done. This qualitative study focuses on educational leadership as a process rather than a product, and strives to gain a deeper understanding of the day-to-day experiences and leadership practices of women administrators in education. Drawing from feminist research studies, organizational theory and studies on women in educational leadership, the study offers to expand the existing discourse in educational leadership by documenting the ways this particular group of women practice leadership.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".