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Record W2790651206 · doi:10.1177/2053168017751993

Compulsory voting and voter information seeking

2018· article· en· W2790651206 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResearch & Politics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBallotVotingSophisticationPoliticsPolitical scienceVoting behaviorFeelingQuality (philosophy)Social psychologyPsychologyLawSociology

Abstract

fetched live from OpenAlex

Compulsory voting is known to produce a relatively weak match between voters’ ballot choices and their preferences. We theorize that this link, in part, exists because compelled voters are relatively unlikely to seek out political information during an election campaign, even after differences in political sophistication across compelled and voluntary voters are taken into account. To test our expectations, we use a simulation of an Australian election, through which we track participants’ information searches. Our findings show that those who do not turn out voluntarily under Australia’s compulsory voting law tend to spend less time seeking out political information, and they engage with less information. While differences in political sophistication between those who feel compelled to vote and those who do not account for a portion of this pattern, feeling compelled also has an independent effect on information seeking. This suggests that the negative relationship between compulsory voting and the “quality” of votes is partly due to the fact that those who are compelled to turn out expend less effort when deciding how to cast their ballots.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.113
GPT teacher head0.456
Teacher spread0.343 · 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