Neither-nor: career success of women in an Arab Middle Eastern context
Bibliographic record
Abstract
Purpose – Few studies examine the career success of women in the Arab Middle East. With that in mind, the purpose of this paper is to explore the conceptualizations of the career success of women managers in Lebanon. Drawing on the individual, behavioral, and structural approaches, this study also investigates the women’s approaches to career success. Capitalizing on the institutional theory (IT), the current investigation accounts for the complexity of the local context by illustrating how a diverse set of socio-cultural values and norms, institutional constraints, and individual agency impact the overall experience of career success among Arab women. Design/methodology/approach – This study is exploratory in nature and draws on a qualitative approach. In-depth, face-to-face, open-ended interviews were conducted with women managers across the managerial hierarchy in a wide range of industries, sectors, and organizations. Findings – The findings suggest that the Lebanese women managers’ career success was not conceptualized exclusively using the objective or the subjective measures. Rather, it was conceptualized on a continuum between these measures, thus challenging the rigid objective/subjective dichotomy in the context of Lebanon. The results also suggest that the career success of these women managers is better predicted and explained by the individual and behavioral approaches than by the traditional, structural approach. This empirical work sheds light on the gendered working conditions that women experience and how they capitalize on their individual agency to survive the hegemonic masculinity embedded in their workplaces, along with the inequalities that it promotes. Originality/value – This study is the first to explore the conceptualizations and the determinants of the career success of women managers in Lebanon. However, the originality of this paper is not only limited to its contribution to the limited research on the careers of Arab women; it also extends to its usage of various approaches to predict career success as well as to adapt IT as a theoretical framework for capturing the myriad of factors that impact women’s careers and success. The originality of this study also lies in advancing the theoretical concept of hegemonic masculinity into studies looking at Arab women’s career experiences by shedding some light on how the reproduction of gender, gendered working practices, and agency impact their career success.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".