Jumping on the bandwagon and off the Titanic: An experimental study of turnout in two-tier voting
Why this work is in the frame
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Bibliographic record
Abstract
We experimentally study voter turnout in two-tier elections when the electorate consists of multiple groups, such as states. Votes are aggregated within the groups by the winner-take-all rule or the proportional rule, and the group-level decisions are combined to determine the winner. We observe that, compared with the theoretical prediction, turnout is significantly lower in the minority camp (the Titanic effect ) and significantly higher in the majority camp (the behavioral bandwagon effect ), and these effects are stronger under the proportional rule than under the winner-take-all rule. As a result, the distribution of voter welfare becomes more unequal than theoretically predicted, and this welfare effect is stronger under the proportional rule than under the winner-take-all rule.
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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 | 0.003 | 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