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Record W2567193265 · doi:10.32469/10355/48706

A new measure of economic voting : priority heuristic theory and combining sociotropic and egocentric evaluations

2015· dissertation· en· W2567193265 on OpenAlexaboutno aff
Jungsub Shin

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsnot available
Fundersnot available
KeywordsVotingIdeologyPositive economicsConstruct (python library)Dimension (graph theory)Scale (ratio)EconomicsPublic economicsPoliticsMicroeconomicsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

It is well-known that a voter's retrospective economic evaluations influence vote choice. A classic debate within the literature on retrospective economic voting concerns whether voters are sociotropic or egocentric when evaluating an incumbent's economic performance. Each side assumes a voter independently considers two perceptual dimensions of economic health, the national economy and one's household financial situation. However, the extant studies overlook the fact that two economic perceptions are correlated. Consequently, our current understanding often fails to account for how sociotropic and egocentric economic evaluations interactively affect vote choice. Moreover, theoretically, voters tend to simplify decision-making when confronted with several alternatives. This notion suggests that voters jointly use sociotropic and egocentric evaluations in a scale rather than use them separately to assess incumbents. Like assuming that voters use a unidimensional scale of ideology though there are several different items that reflect an individual's or a political party's ideology, it is plausible that voters use a unidimensional scale of economic evaluation. On the basis of this notion, this dissertation proposes an improved interval measure of economic evaluation to capture a voter's economic assessment in a single dimension and to provide a comparable economic voting measurement across elections. To construct the new unidimensional measure, this dissertation proposes a lexicographic or priority ordering of economic evaluations on the basis of priority heuristic theory, which provides a convincing prediction of how voters jointly use two different criteria of economic evaluation. PH theory argues that decision makers place alternatives along a single dimension by primarily using the first-priority criterion and then using the next priority to supplement the first. In the case of retrospective economic voting, voters may judge the incumbent mainly according to the economic evaluation they value more and use the other to supplement the decision. According to this theoretical expectation, this dissertation proposes a new unidimensional scale of a voter's economic evaluation. By treating this ordinal variable as nominal in a logistic regression model to predict the probability of an incumbent vote, this dissertation tests its theoretical expectation that voters use the two economic evaluations in a combined way on the basis of priority heuristics. This theoretical expectation is tested with survey data from the elections of five countries (the United States, Britain, Canada, South Korea, and Taiwan). The empirical findings of this research show that voters order economic perceptions and prioritize in sequence, thus merging sociotropic and egocentric retrospective evaluations. A logistic regression model demonstrates that the order of probabilities in voting for the incumbent corresponds with the ordinal measure. Throughout recent elections in five countries, voters used sociotropic and egocentric economic assessments jointly for making vote decisions. Voters depend primarily on sociotropic evaluations as a component of vote choice. However, they incorporate an egocentric perspective as a complementary criterion. This is a universal voting behavior of economic voters examined in this dissertation. This confirms the theoretical expectation on the basis of priority heuristics. This dissertation proposes an economic voting heuristic, an innovative unidimensional measurement combining sociotropic and egocentric assessments that is theoretically stronger than, and empirically as strong as, traditional retrospective voting models.

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)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.115
GPT teacher head0.448
Teacher spread0.332 · 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 designTheoretical or conceptual
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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