Increasing Women’s Political Participation in Lebanon: Reflections on Hurdles, Opportunities and Hope
Bibliographic record
Abstract
Lebanon stands out in the Middle East for its relative political openness, religious freedom, and the academic and professional achievements of Lebanese women. Yet, paradoxically, it has one of the lowest rates of women’s political participation in the region. This paper is the result of an initiative undertaken by the Lebanese government in July 2012 to increase women’s political participation. Through this initiative, sex-segregated workshops on women’s political empowerment were held for male and female representatives of Lebanon’s political parties. The goal was to start a productive conversation that would ultimately lead to progress from the 2012 status quo of women constituting only three percent of the National Parliament of Lebanon. In this paper, we will describe the process and content explored during the women’s political empowerment workshops. Opportunities to affect change of the current level of women’s participation will be highlighted and conclusions will be drawn to aid similar initiatives.
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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 | 0.000 | 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 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".