What do voters do when they prefer a leader from another party?
Bibliographic record
Abstract
There is little research on voters who display incongruent preferences, that is, those who prefer a leader from another party than their preferred one. We address two questions. How many voters prefer a leader from another party? Do these incongruent voters vote for their preferred party or leader? We use the Comparative Study of Electoral Systems (CSES) data sets covering 83 legislative elections over a time period of 20 years (1996–2016). We find that 17% of the electorate typically prefer a leader from another party. In that group, the vast majority (80%) end up supporting their preferred party while 20% of voters support their preferred leader. We find that partisans and those located at the extremes of the political spectrum tend to have more congruent preferences. Moreover, the proportion of incongruent voters who cast their vote for their preferred leader is higher in less established and less polarized countries as well as among non-partisans. We discuss the implications of our findings for our understanding of the role of parties and leaders in contemporary democracies.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".