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Record W2003106209 · doi:10.1207/s15327663jcp1701_9

Deliberative and Automatic Bases of Suspicion: Empirical Evidence of the Sinister Attribution Error

2007· article· en· W2003106209 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Consumer Psychology · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversity of British ColumbiaYork University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British Columbia
KeywordsFlatteryAttributionCategorizationPsychologyCounterfactual thinkingContext (archaeology)PerceptionInterpersonal communicationSocial psychologyNegative informationEmpirical researchEmpirical evidenceProsocial behaviorInformation processingCognitive psychologyComputer scienceArtificial intelligenceEpistemology

Abstract

fetched live from OpenAlex

This research explores perceptions of interpersonal influence in the form of flattery that occurs in a consumer retail setting. Across 4 experiments, results demonstrate empirical evidence of a sinister attribution error (Kramer, 1994), as consumer reactions to flattery were more negative than warranted by the situation. Results across 3 experiments demonstrated that there are 2 types of information processing occurring when consumers make trust judgments in response to flattery. Depending on when flattery occurs, consumers engage in either automatic or deliberative processing of information provided by the sales context. The final experiment further suggests that the automatic processing occurred through categorization based on social cues.

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 score0.160
Threshold uncertainty score0.271

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 studies0.0000.000
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 head0.161
GPT teacher head0.401
Teacher spread0.240 · 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