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Record W2046765180 · doi:10.1037/a0037796

Anxious, threatened, and also unethical: How anxiety makes individuals feel threatened and commit unethical acts.

2014· article· en· W2046765180 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 Applied Psychology · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsPsychologyCheatingAnxietyCommitSocial psychologyPerceptionDishonestyMechanism (biology)

Abstract

fetched live from OpenAlex

People often experience anxiety in the workplace. Across 6 studies, we show that anxiety, both induced and measured, can lead to self-interested unethical behavior. In Studies 1 and 2, we find that compared with individuals in a neutral state, anxious individuals are more willing (a) to participate in unethical actions in hypothetical scenarios and (b) to engage in more cheating to make money in situations that require truthful self-reports. In Studies 3 and 4, we explore the psychological mechanism underlying unethical behaviors when experiencing anxiety. We suggest and find that anxiety increases threat perception, which, in turn, results in self-interested unethical behaviors. Study 5 shows that, relative to participants in the neutral condition, anxious individuals find their own unethical actions to be less problematic than similar actions of others. In Study 6, data from subordinate-supervisor dyads demonstrate that experienced anxiety at work is positively related with experienced threat and unethical behavior. We discuss the theoretical and practical implications of our findings.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.120
GPT teacher head0.406
Teacher spread0.286 · 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