Turnout Rates in Closed Party Leadership Primaries: Flash and Fade Out?
Why this work is in the frame
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Bibliographic record
Abstract
The organization of primaries in which all party members can participate is increasingly used by political parties to select their leader. We focus here on one of the consequences of these procedures – participation rates. Based on general participation theories (mobilization theory, instrumental motivation theory and learning theory) in combination with insights into the introduction and functioning of leadership primaries, we expect that the first time a party organizes leadership primaries, participation rates will be high, but that they will decline gradually afterwards. We have focused on direct member votes for the selection of party leaders in Belgium, Israel and Canada. Our results show that participation rates are not influenced by how many times such a contest is held in a party (only first-time participation tends to be higher), but mainly by how competitive the contest is.
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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 | 0.000 | 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