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Record W4206941314 · doi:10.1017/s0143814x21000234

Party cues or policy information? The differential influence of financial and economic literacy on economic policy preferences

2022· article· en· W4206941314 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

VenueJournal of Public Policy · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of Toronto
FundersUniversity of Washington
KeywordsFinancial literacyWelfarePoliticsPublic economicsEconomic welfareEconomicsBusinessFinancePolitical scienceMarket economy

Abstract

fetched live from OpenAlex

Abstract Political economy theories tell us that policy preferences are driven by economic self-interest and that party cues can be a rational decision-making strategy. But does citizens’ ability to assess their self-interest influence the sources of information they rely on and their policy choices? I hypothesise that financial and economic literacy influences the type of information individuals are responsive to, and ultimately, their economic policy preferences. Using a survey experiment on price controls in Italy, I manipulate whether citizens receive party cues or policy information. I show that financially and economically literate individuals are more likely to understand information concerning the costs and benefits of the policy under analysis, and to be responsive to it. This is not the case for financially and economically illiterate individuals, who are more receptive to party cues, even when such cues are misleading and lead them to support welfare-reducing policies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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