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Record W2187082881 · doi:10.1017/s0003055416000241

The Primary Effect: Preference Votes and Political Promotions

2016· article· en· W2187082881 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Political Science Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsPreferencePrimary electionPoliticsExploitPolitical scienceRegression discontinuity designAnalogyCompetence (human resources)MicroeconomicsGeneral electionEconomicsSocial psychologyPsychologyLawComputer scienceComputer securityStatistics

Abstract

fetched live from OpenAlex

In this analysis of how electoral rules and outcomes shape the internal organization of political parties, we make an analogy to primary elections to argue that parties use preference-vote tallies to identify popular politicians and promote them to positions of power. We document this behavior among parties in Sweden's semi-open-list system and in Brazil's open-list system. To identify a causal impact of preference votes, we exploit a regression discontinuity design around the threshold of winning the most preference votes on a party list. In our main case, Sweden, these narrow “primary winners” are at least 50% more likely to become local party leaders than their runners-up. Across individual politicians, the primary effect is present only for politicians who hold the first few positions on the list and when the preference-vote winner and runner-up have similar competence levels. Across party groups, the primary effect is the strongest in unthreatened governing parties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.010
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.384
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it