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Record W1545963841 · doi:10.22004/ag.econ.7717

Perceived Risk is Important for Consumers' Acceptance of Genetically Modified Foods, but Trust in Industry not Really: A Means-End Analysis of German Consumers

2006· article· en· W1545963841 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

VenueAgEcon Search (University of Minnesota, USA) · 2006
Typearticle
Languageen
FieldPsychology
TopicCognitive and psychological constructs research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGermanRisk perceptionBusinessMarketingEmpirical researchAdvertisingPsychologyPerceptionMathematics

Abstract

fetched live from OpenAlex

Applies the means-end approach to investigate how German consumers relate GM food attributes to values via perceived consequences in their purchase decisions. Analyses in particular the importance of risk-related dimensions and issues of (dis)trust for different levels of purchase intentions. Identifies two segments: rejecters (n=24) and accepters (n=36). Finds considerable similarities in means-end chains between segments, in particular that risk plays a much bigger role than trust for purchase intentions. Furthermore, for both segments the link between trust and risk is found to be weak which implies to reconsider results from previous empirical studies pointing out the strong interaction of trust and perceived risk.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.058
GPT teacher head0.341
Teacher spread0.283 · 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