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Record W4405496931 · doi:10.1093/ser/mwae078

When partisanship and technocratic credibility collide: mass attitudes and central bank endorsements of fiscal policy in Canada and the USA

2024· article· en· W4405496931 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSocio-Economic Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversité de MontréalMemorial University of NewfoundlandQueen's University
Fundersnot available
KeywordsTechnocracyCredibilityPolitical scienceCentral bankEconomicsFiscal policyMacroeconomicsMonetary policyPolitics

Abstract

fetched live from OpenAlex

Abstract Developments over the past decade have made it increasingly difficult for central banks to achieve their macroeconomic objectives without the help of fiscal policy, resulting in some surprisingly public efforts from central banks to influence the size and direction of government budget balances. But do voters find central bank appeals persuasive and what are the reputational consequences of engaging the public on this sensitive issue, particularly in the event of partisan counterattacks? We examine these issues with two parallel survey experiments conducted in Canada and the USA. The results suggest central bank endorsements modestly increased support for expansionary fiscal policies. They also suggest the right’s attack on the central bank may have backfired—ultimately improving rather than undermining the bank’s reputation among non-conservatives. This research has implications for theoretical work in political psychology and public economics and for on-going empirical debates about voters’ attitudes toward austerity.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.178
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.335
Teacher spread0.302 · 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