Government supported women’s leadership development programmes: a case study of Dubai.
Bibliographic record
Abstract
Since its inception in 1971, the United Arab Emirates’ (UAE) government has undertaken to develop the capabilities of its citizens (nationals), in order to satisfy the country’s need for rapid economic growth. One of the seven Emirates, Dubai, has played an integral role in implementing this national objective by leading associated initiatives. Consequently, the government of Dubai emphasizes the importance of developing its people through human resources programmes that focus on specific demographic groups, such as women, and specific aspects of human development, with leadership being an important segment. The purpose of this study is to examine women’s leadership in the UAE. Specifically, this study attempts to explore the characteristics and behaviours of a group of women leaders who were the first candidates of the UAE Women Leadership Development Programme (UAE WLDP) in Dubai. \nThe study included an on-line survey that was sent to a sample of 35 women leaders. Demographically, all of the respondents were aged between 25 and 35 years. Most of the women were unmarried and held degrees of higher education, specifically from a business background. The survey indicated that respondents believed they practiced a combination of the four categories of leaders’ behaviours: pragmatist, visionary, motivator, and facilitator. Finally, they rated their managerial potential and management performance as very good. \nThe respondents reported that one of the major challenges they faced at work was gender discrimination and issues related to work-family balance. A quarter of the women indicated that they felt some kind of gender-bias towards them. Respondents suggested policies or interventions that could be undertaken in order to improve their performance as leaders. \nThe study concluded that government sponsored leadership programmes enhance the abilities of women who were already progressing in their chosen fields. It highlights other areas in which the government could intervene to improve the capabilities of women in leadership. Overall, although good progress has been made, more could be done to benefit the national population using programmes of this nature.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".