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Record W4200564747 · doi:10.5539/jfr.v11n1p1

Risk Communication under Conflicting Information: The Role of Confidence in Subjective Risk Assessment

2021· article· en· W4200564747 on OpenAlexvenueno aff
Takashi Ishida, Atsushi Maruyama, Shinichi Kurihara

Bibliographic record

VenueJournal of Food Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsRisk assessmentConsumer confidence indexConfidence intervalRisk perceptionActuarial scienceConsumption (sociology)Low ConfidenceValue (mathematics)BusinessPsychologyEnvironmental healthMarketingMedicineEconomicsStatisticsSocial psychologyPerception

Abstract

fetched live from OpenAlex

In this study, we develop a model of food consumption with a focus on the subjectively assessed risk of consumers and their degree of confidence in their risk assessment and use it to examine consumer behavior in the chaotic situation created by the Fukushima nuclear accident in 2011. The data were collected in March 2012 using a mail survey for 1300 Japanese women, the primary food purchasers. The respondents were asked to evaluate the cancer risk of eating agricultural products, which were assumed to be grown in the affected area, despite meeting national regulatory standards for radioactive materials, as a measure of their risk assessment and willingness to purchase Fukushima beef. The results show that the effect of confidence in a consumer’s risk assessment on their behavior depends on the stated risk level: when stated risk is below an estimated critical value, termed the switching point, the risk perceived by a consumer without confidence exceeds that of one with confidence. On the other hand, perceived risk is inversely related to confidence when the stated risk exceeds the switching point.

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.

How this classification was reachedexpand

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)0.010
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.075
GPT teacher head0.463
Teacher spread0.388 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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