MétaCan
Menu
Back to cohort
Record W2741823111 · doi:10.1111/jasp.12457

To trust or not to trust: How self‐construal affects consumer responses to interpersonal influence

2017· article· en· W2741823111 on OpenAlexafffund
Wenxia Guo, Kelley Main

Bibliographic record

VenueJournal of Applied Social Psychology · 2017
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of ManitobaAcadia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPersuasionPsychologySelf construalConstrual level theorySocial psychologyInterpersonal communicationInterdependenceSociology

Abstract

fetched live from OpenAlex

Abstract Although people generally prefer persuasive messages that align with their self‐construal, the present research explores a seemingly paradoxical situation wherein mismatched message that does not align with people's self‐construal is positively received. Given sufficient cognitive capacity to trigger persuasion knowledge—the knowledge of persuasion tactics that are encountered in the marketplace, the use of an individually focused persuasion attempt on consumers with an interdependent self‐construal results in greater levels of trust in the sales agent. In contrast, consumers with an independent self‐construal respond similarly to different types of persuasion attempts. Persuasion knowledge is a mechanism for variations in trust. The findings replicate those of prior work, and the robustness of the effects is confirmed via small‐scale meta‐analysis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.446
Teacher spread0.341 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Applied Social PsychologySame topicCultural Differences and ValuesFrench-language works237,207