Female labor force participation in the Middle East and North African Countries: constraints and levers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract

 
 
 Despite the importance of the subject, few researches have attempted to explain the female labor force participation (FLFP) in MENA region. This research tries to exploring the geopolitical, social, ethnic and economic levers or constraints that facilitate or bloc women’s access to the labor market. A quantitative approach based on data analysis was performed through the review of the World Bank statistics related to women participation in the labor market in MENA region. Data analysis revealed that the studied labor market was marked by an overall positive progress of the presence of female workers. However, this evolution is still considered very low and slow in comparison with world standards. The research also revealed huge disparities in the level of progress of the FLFP among the studied countries. The disparities observed were interpreted in correlation with the religious, economic, political, social and cultural aspects.
 
 
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it