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Record W2800878997 · doi:10.1037/apl0000311

Honor among thieves: The interaction of team and member deviance on trust in the team.

2018· article· en· W2800878997 on OpenAlex
Kira Schabram, Sandra L. Robinson, Kevin S. Cruz

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 Applied Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDeviance (statistics)PsychologySocial psychologyPsycINFOPositive devianceHonorLawInternet privacy

Abstract

fetched live from OpenAlex

In this article, we examine member trust in deviant teams. We contend that a member's trust in his or her deviant team depends on the member's own deviant actions; although all members will judge the actions of their deviant teams as rational evidence that they should not be trusted, deviant members, but not honest members, can hold on to trust in their teams because of a sense of connection to the team. We tested our predictions in a field study of 562 members across 111 teams and 24 organizations as well as in an experiment of 178 participants in deviant and non-deviant teams. Both studies show that honest members experience a greater decline in trust as team deviance goes up. Moreover, our experiment finds that deviant members have as much trust in their deviant teams as honest members do in honest teams, but only in teams with coordinated rather than independent acts of deviance, in which deviant members engage in a variety of ongoing dynamics foundational to a sense of connection and affective-based trust. (PsycINFO Database Record

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.296

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 integrity0.0000.001
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 head0.025
GPT teacher head0.349
Teacher spread0.324 · 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