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Record W2947104316 · doi:10.1080/00323187.2019.1601021

Assessing the influence of ideologies on vote choice in an ethnoterritorial context: the case of Taiwan

2018· article· en· W2947104316 on OpenAlexaff
Jean‐François Dupré, Mike Medeiros

Bibliographic record

VenuePolitical Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIdeologyContext (archaeology)Social psychologyPsychologySociologyPolitical sciencePoliticsGeographyLaw

Abstract

fetched live from OpenAlex

The literature on vote choice in Taiwan has regularly identified ethnoterritorial ideology – preference for independence or unification with China – as the main ideological cleavage in Taiwanese party politics. This paper contributes to the literature by investigating the effects of two more ideological dimensions on vote choice: social and economic. Based on data from the Taiwan Election and Democratization Study (TEDS) for the 2016 presidential and legislative elections, our findings demonstrate that social and (to a lesser degree) economic ideologies do have significant influence on vote choice, though ethnoterritorial ideology remains the primary ideological determinant. Findings were similar for the presidential and legislative elections. On this basis, we make a case for increased attention to social and economic ideologies in future research on vote choice in Taiwan, and we encourage scholars to study Taiwan in comparative perspective with other societies that are divided along ethnoterritorial lines.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.096
GPT teacher head0.470
Teacher spread0.374 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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