The impact of gender, family, and work on the career advancement of Lebanese women managers
Bibliographic record
Abstract
Purpose The purpose of this paper is to address the research gap on Lebanese women managers and to demonstrate how gender, work, and family factors influence the career advancement of women managers. Design/methodology/approach The research is qualitative in nature. A total of 32 in‐depth face‐to face interviews were conducted with 32 women managers. Findings Interview data reveal that Lebanese women managers do not perceive gender‐centered factors as obstacles to career advancement. The women in the study used different terms to describe the impact of gender, work, and family factors on their career progression to those found in existing literature. Their responsibilities towards their families were not perceived as barriers hindering their career progress. In addition, their personality traits, aspirations for management, levels of educational attainment and work experience, and family‐related factors were also not perceived as inhibiting their careers. Practical implications The paper provides new practical insights into the relationships and the interconnections between Arab society, women, and their managerial careers. A strong theme is the significant role ofWasta, the reliance and dependence on social connections versus personal education and achievements to achieve career progress, in enhancing career progression and how gender is less of a criterion in the presence ofWasta. Originality/value This paper contributes to the limited knowledge about women and 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) | 0.003 | 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".