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Record W2901128491 · doi:10.1038/s41598-018-35748-y

Investigating the Neurological Correlates of Workplace Deviance Using a Rodent Model of Extinction

2018· article· en· W2901128491 on OpenAlexafffund
Jason Tabor, Yannick Griep, Reid Collins, Richelle Mychasiuk

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersAlberta Children's Hospital Research Institute
KeywordsDeviance (statistics)PsychologyStressorNucleus accumbensPerceptionClinical psychologyNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Employee deviance and time theft is an expensive and pervasive workplace problem. Research indicates that a primary reason employees engage in deviant behaviour is the perception of injustice often associated with psychological contract breach (i.e., broken promises). This study used a rodent model to mimic said experience of broken promises and then examined the subsequent neurophysiological changes that lead to the display of deviant behaviours. Specifically, we generated a psychological contract using a 3 choice serial reaction task, then broke the promise, and finally examined deviant behaviours and neurological correlates. After the broken promise, rats had elevated levels of corticosterone and testosterone, engaged in riskier behaviour, and were more aggressive. The most prominent changes in gene expression were associated with serotonin and stress, and were found in the nucleus accumbens. This study highlights the value of pre-clinical models in the investigation of the theoretical tenants of industrial and organizational psychology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.081
GPT teacher head0.305
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2018
Admission routes2
Has abstractyes

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