Rematch: Islamic Politics, Mobilization, and the Indonesian Presidential Election
Bibliographic record
Abstract
Indonesia’s 2019 presidential election brings a rematch between incumbent Joko Widodo and Prabowo Subianto, though against a backdrop of increasingly active conservative Islamic movements. Analyses of this contest — as well as of contemporary Indonesian politics more generally —are often based on assumptions around which constituencies matter and which political fact ions they support. This paper examines those assumptions using an original dataset of fine-grained returns and census data, including a latent variable to capture the independent effect of Islamic conservatism. We find that conservative Muslim areas overwhelmingly supported Prabowo in 2014, but turned out in relatively low numbers. By contrast, rural poor areas turned out heavily for Widodo. This suggests that the conservative vote was under-mobilized and has a greater electoral potential than previously demonstrated. Given the recent mobilization by conservative segments in society, observers should be prepared for significant shifts in the Indonesian electorate in 2019 and beyond.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".