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Record W2790072190 · doi:10.1080/02732173.2017.1409146

Does Institutional Trust Increase Willingness to Pay More Taxes to Support the Welfare State?

2018· article· en· W2790072190 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

VenueSociological Spectrum · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsWillingness to payPublic economicsWelfareRetrenchmentUnit (ring theory)Welfare stateBusinessEconomicsState (computer science)MicroeconomicsPsychologyPublic administrationPolitical scienceLawMarket economy

Abstract

fetched live from OpenAlex

We evaluate the effect of institutional trust on the willingness to pay more taxes to support the welfare state. We found a positive effect of institutional trust on the willingness to pay more taxes to support the welfare state irrespective of the empirical approach used. Our instrumental variable analysis shows that causality run from institutional trust to welfare state support. A one-unit increase in institutional trust leads to a 15 percentage point increase in the willingness to pay more taxes to help the needy. Similarly, a one-unit increase in institutional trust leads to a 16 percentage point increase in the willingness to pay more taxes to support public health care and education. Consequently, institutional trust should be viewed as one of the most important mechanisms that protect the welfare state from dismantling and retrenchment. We also found a stronger effect of support for more universal programs such as public health care and education than for helping the needy.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.309
Teacher spread0.288 · 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