Bibliographic record
Abstract
t is striking how often, over the last decade-and-a-half, women have led successful popular uprisings against dictatorships in Asia. Corazon C. Aquino in the Philippines (1986), Benazir Bhutto in Pakistan (1988), Khaleda Zia and Sheikh Hasina Wajed in Bangladesh (1990) and Megawati Sukarnoputri in Indonesia (1998) inspired and organized mass protests against non-democratic regimes. They then guided precarious transitions to democracy. Aquino was the Philippines' first president after the Marcos dictatorship. Bhutto served twice as prime minister in the post-Zia era in Pakistan. Khaleda Zia and Sheikh Hasina have alternated as prime minister since the end of military rule in Bangladesh. Megawati, who was initially elected vice president, succeeded to the Indonesian presidency after accusations of corruption and mismanagement led the upper house to dismiss Abdurrahman Wahid from office in July 2001. Moreover, women currently lead two democratic movements involved in ongoing struggles against authoritarianism. In Burma (which the military dictatorship has renamed Myanmar), Aung San Suu Kyi remains the country's most important oppositionist despite the 1998 massacre of protesters, the junta's refusal to recognize her party's overwhelming victory in the May 1990 elections, and her long house arrest. In Malaysia, Wan Azizah Wan Ismail leads a new opposition party and was a major figure in the opposition 199899 reformasi movement that attempted to unseat the long-reigning prime minister Mahathir Mohamad.
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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 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".