Perceived organizational barriers to women's career advancement in Lebanon
Bibliographic record
Abstract
Purpose The purpose of this paper is to address the research gap on Lebanese female managers and to examine female managers' perceptions of their organizations in relation to women's career progression. Design/methodology/approach The research was quantitative in nature. A survey questionnaire was used to collect data from 450 female managers. Measures included personal and demographic characteristics, organizational culture, organizational practices, organizational networks, mentoring and role modeling, tokenism, and the usage ofwasta. Findings Descriptive statistics and analysis of variance were used to explain the results. The results reveal that female managers perceive their career progression to be affected by organizational culture, practices, and networks, while mentoring and tokenism were shown to be less critical. In addition, the women in this sample perceivedwastato be a powerful determinant. Practical implications The findings contribute to a wider appreciation of the implicit barriers to women's career development and retention, will help organizations engage with the diversity agenda in this region and provide a better understanding of how these companies and their members can make progress, will help inform managerial interventions to make managers better able to make the most of the issues faced, and will help organizations make a much more concerted effort to manage junior female managers through helping them accelerate in their progression and development. Originality/value The paper contributes to the limited literature on women in management in Lebanon as well as the Middle Eastern region in general.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".