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Record W2113060899 · doi:10.1509/jm.12.0166

Who or What to Believe: Trust and the Differential Persuasiveness of Human and Anthropomorphized Messengers

2015· article· en· W2113060899 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

VenueJournal of Marketing · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsGoodwillPersuasionInterpersonal communicationPsychologySocial psychologyBusiness

Abstract

fetched live from OpenAlex

Participants in three studies read advertisements in which messages were delivered either by people or by anthropomorphized agents—specifically, “talking” products. The results indicate that people low in interpersonal trust are more persuaded by anthropomorphized messengers than by human spokespeople because low trusters are more attentive to the nature of the messenger and believe that humans, more than partial humans (i.e., anthropomorphized agents), lack goodwill. People high in interpersonal trust are less attentive about who is trying to persuade them and so respond similarly to human and anthropomorphized messengers. However, when prompted to be attentive, they are more persuaded by human spokespeople than by anthropomorphized messengers due to their belief that humans, more than partial humans, act with goodwill. Under conditions in which attentiveness is low for all consumers, high and low trusters alike are unaffected by the nature of persuasion agents. The authors discuss the implications of the findings for advertisers considering the use of anthropomorphized “spokespeople.”

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)0.010
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.035
GPT teacher head0.337
Teacher spread0.302 · 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