Challenges to Women’s Participation in Senior Administrative Positions in Iranian Higher Education
Bibliographic record
Abstract
In the last three decades, growth in the education of women in Iran has led to a significant increase in demand for women professionals and administrators in Iranian universities. However, the path to the top is not easy and numerous challenges must still be overcome. This study explored the challenges of women’s participation in senior administrative positions from the perspective of Iranian women administrators in higher education. Data were collected based on semi-structured interviews with 20 women academician in administrative positions. Thematic analysis was conducted to examine the themes that emerged to represent their experience and perspective. The findings indicated that challenges ranged from organizational to societal and individual factors. Individual factors were related to personality traits such as work-family balance issues and a lack of self- confidence. At the organizational levels, difficult relationships at work and the old boys’ network, and organizational practices were perceived to be a hindrance, while at the societal level, gender role stereotypes and social attitudes towards women were viewed as key challenges to the participation of women in senior administrative positions. The implication for women who aspire to the top position of organizations is that they should be aware of and understand the visible and invisible challenges in relation to their career advancement.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".