Accruing career capital: How party leaders with more political experience survive longer
Bibliographic record
Abstract
As some of the most experienced political actors, party leaders usually have extensive careers spanning multiple decades, competencies, and institutions. The literature on party leaders, however, has not yet incorporated the wealth of information that these careers have. Therefore, this article introduces career capital as a new continuous measure of political experience and hypothesizes that more career capital leads to longer tenure. In contrast to findings from previous studies, I show that career capital does contribute to party leaders’ survival in office in several analyses of party leader duration in Canada, Germany, the Netherlands and Switzerland in the postwar period (1945–2023). In addition, because career capital is accumulated in three separate institutions, I examine the differences between these descriptively and show in the analysis that especially previous experience in legislative office is conducive for party leaders to remain longer in office. Lastly, the results indicate that the relationship between career capital and party leader duration is non-linear and subject to the effect of attrition, signifying that political experience acquired shortly before entering party leader office is more important for political survival.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 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".