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Record W2133098504 · doi:10.1177/0010414015574877

Elections in the Arab World

2015· article· en· W2133098504 on OpenAlexafffund
Carolina de Miguel, Amaney Jamal, Mark Tessler

Bibliographic record

VenueComparative Political Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsVotingTurnoutAuthoritarianismArgument (complex analysis)Political economyPolitical scienceDemocracyMediationEconomicsLawPolitics

Abstract

fetched live from OpenAlex

This article examines the determinants of voting in competitive authoritarian regimes in the Arab world. In contrast to scholars who view elections in the Arab World purely as patronage contests, we argue that citizens also care about policy outputs and use turnout as a way to signal their approval or disapproval with the regime. We draw on the literature on economic voting in democratic regimes to develop an argument about economic voting under authoritarian conditions, and we propose a mediation model to get at the mechanisms of economic voting. We test our argument with original data based on surveys conducted in seven Arab countries between 2006 and 2009. Our results show that although patronage helps to explain turnout, especially among high-income citizens, policy outcomes are also important in the calculus of voting. Most voters turn out to vote to show approval of the regime and its economic performance.

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)0.007
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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.525
GPT teacher head0.531
Teacher spread0.007 · 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

Citations58
Published2015
Admission routes2
Has abstractyes

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