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Record W2611950864 · doi:10.1111/rego.12161

A worldwide consensus on nudging? Not quite, but almost

2017· article· en· W2611950864 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRegulation & Governance · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Abstract Nudges are choice‐preserving interventions that steer people's behavior in specific directions while still allowing them to go their own way. Some nudges have been controversial, because they are seen as objectionably paternalistic. This study reports on nationally representative surveys in eight diverse countries, investigating what people actually think about nudges and nudging. The study covers Australia, Brazil, Canada, China, Japan, Russia, South Africa, and South Korea. Generally, we find strong majority support for nudges in all countries, with the important exception of Japan, and with spectacularly high approval rates in China and South Korea. We connect the findings here to earlier studies involving Denmark, France, Germany, Hungary, Italy, the United Kingdom, and the United States. Our primary conclusion is that while citizens generally approve of health and safety nudges, the nations of the world appear to fall into three distinct categories: (i) a group of nations, mostly liberal democracies, where strong majorities approve of nudges whenever they (a) are seen to fit with the interests and values of most citizens and (b) do not have illicit purposes; (ii) a group of nations where overwhelming majorities approve of nearly all nudges; and (iii) a group of nations that usually show majority approval, but markedly reduced approval rates. We offer some speculations about the relationship between approval rates and trust.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.736
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.332
Teacher spread0.293 · 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