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Record W2051915755 · doi:10.1037/a0012627

My friend is embarrassing me: Exploring the guilty by association effect.

2008· article· en· W2051915755 on OpenAlexafffund
Jennifer L. Fortune, Ian R. Newby‐Clark

Bibliographic record

VenueJournal of Personality and Social Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsClosenessPsychologySocial psychologyEmbarrassmentPerspective (graphical)FeelingAssociation (psychology)MisconductShamePerception

Abstract

fetched live from OpenAlex

It is contended that people (known here as associates) erroneously believe that their social standing suffers when people with whom they are associated (offenders) act in socially inappropriate ways. Accordingly, the anticipated evaluations of associates and observers were contrasted in 6 studies. Study 1 participants read a second-person scenario from the perspective of an associate or an observer. Associates anticipated that observers would give them less positive ratings when the offender picked his or her nose (versus control), but observers' ratings were unaffected. In Study 2, associates erroneously anticipated that observers' ratings of them would vary systematically as a function of whether or not they were introduced as friends of an offender who had/had not committed academic misconduct. In Study 3, anticipated ratings of associates were negatively affected by the actions of an offender whom they did not know previously. Study 4 showed that perspective-taking is the key to attenuating the effect and reducing feelings of embarrassment. The last 2 studies clarified the role of physical proximity and felt closeness. Consistent with results of a scenario study (Study 5), Study 6 participants' anticipated ratings were negatively affected by a combination of increased physical proximity and felt closeness.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.083
GPT teacher head0.369
Teacher spread0.285 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations34
Published2008
Admission routes2
Has abstractyes

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