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Economic Voting and Multilevel Governance: A Comparative Individual‐Level Analysis

2006· article· en· W1987209076 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 Journal of Political Science · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsQueen's University
Fundersnot available
KeywordsCLARITYVotingCorporate governanceArgument (complex analysis)Multilevel modelPublic economicsPropositionGovernment (linguistics)Political sciencePunishment (psychology)EconomicsPositive economicsBusinessPsychologySocial psychologyLawComputer sciencePolitics

Abstract

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An important component of incumbent support is the reward/punishment calculus of economic voting. Previous work has shown that “clarity of responsibility” within the central state government conditions national economic effects on incumbent vote choice: where clarity is high (low), economic effects are greater (less). This article advances the “clarity of responsibility” argument by considering the effect of multilevel governance on economic voting. In institutional contexts of multilevel governance, the process of correctly assigning responsibility for economic outcomes can be difficult. This article tests the proposition that multilevel governance mutes effects of national economic conditions by undermining responsibility linkages to the national government. Individual‐level data from the Comparative Study of Electoral Systems Module 1 are used to test this proposition. Results demonstrate that economic voting is weakest in countries where multilevel governance is most prominent. Findings are discussed in light of the contribution to the economic voting literature and the potential implications of multilevel governance.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
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 head0.065
GPT teacher head0.387
Teacher spread0.322 · 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