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"The Good, the Bad or Just Plain Bored? Boredom Predicting Citizenship and Counterproductive Behavior"

2016· article· en· W2765536135 on OpenAlexaff
Patricia L. Baratta, Jeffrey S. Spence

Bibliographic record

VenueAcademy of Management Proceedings · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBoredomCounterproductive work behaviorOrganizational citizenship behaviorPsychologySocial psychologyFeelingHarmConstruct (python library)Prosocial behaviorPersonalityOrganizational commitment

Abstract

fetched live from OpenAlex

Boredom is often treated as a “dark” construct with the potential to harm organizations. Recently, however, researchers have proposed a “light” side of boredom wherein it could benefit organizations. In the present paper, we juxtapose the “dark” and “light” sides of boredom by investigating the extent to which feeling bored at work causes individuals to perform counterproductive work behavior (CWB) and organizational citizenship behavior (OCB). To test these hypotheses, we surveyed 136 full-time employees using experience sampling methodology. Our results indicated that whereas bored individuals engage in CWB, they are unlikely to perform OCB. In addition, we found evidence suggesting that need for achievement and proactive personality moderate the relations between feeling bored and CWB and OCB, respectively. Our results support the idea that individual differences may shape bored employees’ behavior, such as by enabling them to perform prosocial acts in addition to harmful ones.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.430

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.285
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2016
Admission routes1
Has abstractyes

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