Women Entrepreneurship Development in Yemen: The Role of Decision-Making Empowerment
Bibliographic record
Abstract
This research was conducted to examine the impact of decision-making empowerment on women entrepreneurship development in Yemen. Two dimensions of decision-making empowerment were used; economic decision making, and household decision-making empowerment. This study employed the quantitative approach and the method of collecting data was the online-questionnaire. The targeted sample size of this study was 200 business women in Yemen and the response rate was 96.5%. The results of the correlational analysis show that there is a clear strong positive correlation between decision-making empowerment and women entrepreneurship development. In addition, the two dimensions; economic decision making, and household decision-making have a significant relationship with women entrepreneurship development. The results of the regression analysis reveal that decision-making empowerment has a significant impact on women entrepreneurship development and the economic decision-making empowerment and household decision-making empowerment were explaining women entrepreneurship development. It can be concluded that empowering women by allowing them to participate in economic and household decision-making appears to be one of the important factors for developing women's entrepreneurship in particular, which in turn will help reduce poverty as well as achieve economic growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".