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Record W2017051213 · doi:10.1509/jmr.12.0335

The Motivating Role of Dissociative Out-Groups in Encouraging Positive Consumer Behaviors

2014· article· en· W2017051213 on OpenAlexaff
Katherine White, Bonnie Simpson, Jennifer Argo

Bibliographic record

VenueJournal of Marketing Research · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of AlbertaWestern UniversityUniversity of British Columbia
Fundersnot available
KeywordsDissociativePsychologySocial psychologyGroup (periodic table)Consumption (sociology)Consumer behaviourNegative informationClinical psychologyAesthetics

Abstract

fetched live from OpenAlex

Previous research has found that people tend to avoid products or behaviors that are linked to dissociative reference groups. The present research demonstrates conditions under which consumers exhibit similar behaviors to dissociative out-group members in the domain of positive consumption behaviors. In particular, when a consumer learns that a dissociative out-group performs comparatively well on a positive behavior, the consumer is more likely to respond with positive intentions and actions when the setting is public (vs. private). The authors suggest that this occurs because learning of the successful performance of a dissociative out-group under public conditions threatens the consumer's group image and activates the desire to present the group image in a positive light. The authors show that although group affirmation mitigates these effects, self-affirmation does not. They also examine the moderating role of the positivity of the behavior and the mediating role of group image motives. Taken together, the results highlight conditions under which communicating information about the behaviors of dissociative out-groups can be used to spur consumers to engage in positive actions.

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)0.048
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.418
Teacher spread0.382 · 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; both teacher heads agree on what is shown here.

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

Citations100
Published2014
Admission routes1
Has abstractyes

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