Employees’ Attitude Toward Women Managers in the UAE: Role of Socio-Demographic Factors
Bibliographic record
Abstract
This study aims to understand and examine the relationship between socio-demographic factors and the attitudes toward women managers in the context of the United Arab Emirates (UAE). This research paper is an exploratory research and we have taken into consideration a basic framework to understand the relationship that exists among different factors responsible for different perceptions and attitudes toward women managers. The literature review has focused on the various overarching perspectives of women managers and the attitudes formed by different societal actors. The paper draws mainly from the Social Learning Theory of Albert Bandura (1977). A sample of 213 employees was drawn to understand the relationship. The respondents were administered the well-established (Women as Managers Survey) WAMS questionnaire to get responses on various dimensions. Multivariate Regression Analysis using SPSS 26.0 version was applied to analyze the data. The findings of the study are parallel to previous works such that age, work experience, and educational level found support to the hypothesized relationship whereas gender and marital status did not. Limitations and future direction along with practical implications and recommendations are also given to draw suitable inferences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".