Bibliographic record
Abstract
In convergence with the global norm toward more proportional representative electoral systems, many countries in East Asia have adopted quota strategies to address women's political underrepresentation (Franceschet, Krook, and Piscopo 2012; Krook 2009). Taiwan, South Korea, Singapore, and Japan provide ideal case studies to investigate the impact of these efforts. While these countries share similar economic development, educational levels, and Confucian communitarian ethos, their experiences and progress on empowering women vary. For example, the level of women's legislative representation in the region ranges from a low of 8.1% in Japan to a high of 33.6% in Taiwan. And while Taiwan and South Korea embarked on constitutional reforms in the 1990s and introduced candidate quotas or reserved seats to guarantee women's legislative representation at all levels, Singapore and Japan have resisted legislating quotas but instead set 30% women parliamentarians as targets of party strategies. This collection of papers explores this intraregional variation with a comparative view on the origins and impact of quotas on women's political life. Specifically, we trace the origins of quota adoption and how they interact with the existing electoral and party institutions to improve women's legislative numbers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".