Egyptian women supervisory empowerment behaviors on well-being outcomes
Bibliographic record
Abstract
Purpose This paper aims to examine the relationship of perceived supervisor empowerment behaviors and feelings of personal empowerment with important work and well-being outcomes in a sample of Egyptian women managers and professionals. Design/methodology/approach Data were collected from 155 managerial and professional women using anonymously completed questionnaires. Respondents were relatively young; had university educations; had the short job and organizational tenures; held various levels of management jobs; and worked in a range of functions. All measures used here had been used and validated previously by other researchers. Findings Work outcomes included job satisfaction, career satisfaction, work engagement, work-family and family-work conflict, emotional exhaustion/burnout, life satisfaction and intent to quit. Both perceived levels of supervisory/leader empowerment behaviors and self-reported feelings of empowerment had significant relationships with the majority of work and well-being outcomes. Research limitations/implications Data were collected using self-report questionnaires with the small risk of response set and common method biases. Second, all data were collected at one point in time making it challenging to address issues of causality. Third, all respondents came from the two largest cities in Egypt, Cairo and Alexandria; thus, the extent to which our findings would generalize to managerial and professional women and men is indeterminate. Fourth, it was not possible to determine the representativeness of our sample as well. Practical implications Practical implications of these findings along with future research directions are offered. Practical applications include training supervisors on empowerment behaviors, and training all employees on the benefits of personal empowerment and efficacy and ways to increase them. Social implications A number of ways to increase levels of empowerment of both front-line employees and managers have been identified. These include increasing employee participation in decision-making, delegating authority and control to these employees, creating more challenging work roles through job redesign, leaders sharing more information and leaders providing more coaching and mentoring to their staff. At the micro level, increasing levels of employee self-efficacy through training and more effective use of their work experiences will increase personal empowerment and improve work outcomes. Originality/value Relatively little research has been undertaken on women in management and human resource management in Egypt.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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; both teacher heads agree on what is shown here.
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".