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Record W4255904462 · doi:10.1108/ict-12-2013-0086

Corporate psychopathy: deviant workplace behaviour and toxic leaders – part one

2015· article· en· W4255904462 on OpenAlexaff
Henry S. Cheang, Steven H. Appelbaum

Bibliographic record

VenueIndustrial and Commercial Training · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsPsychopathyPsychologyEmpirical researchAntisocial personality disorderPersonalityApplied psychologySocial psychologyPoison controlInjury prevention

Abstract

fetched live from OpenAlex

Purpose – Increasingly, it is recognized that (larger) organizations have many employees who present with corporate psychopathy (i.e. a milder version of antisocial personality disorder (APD)). Importantly, such a disorder contributes to the presence of deviant workplace behaviour. Organizations must therefore adapt its practices to both identify and manage employees who either present with, or have tendencies towards, corporate psychopathy. As a means of developing a guiding framework for organizational adaptation, the purpose of this two-part paper is to offer two reviews of relevant research. The first revolves around the body of knowledge regarding corporate psychopathy and the primary, established behavioural method of identifying its presence; the second is a brief review on physiological measures that can complement current gold standards. Design/methodology/approach – A range of published empirical and practitioner research articles were reviewed to elaborate on APD and corporate psychopathy; showcase the efficacy of the currently most accepted method of detecting psychopathic behaviour – the Psychopathy Checklist (PCL) and; highlight physiological methods of detecting psychopathic tendencies which may complement usage of the PCL – electroencephalography, measurement of galvanic skin responses, and electromyography. Findings – Deviant workplace behaviours cause losses of billions of dollars across all business organizations, and much of this behaviour stems from corporate psychopaths in positions of leadership; the PCL, while useful, can nonetheless yield sharp differences in the identification of psychopathy across different administrators of the test; measures of physiological states show good reliability in discriminating psychopathic persons from non-psychopathic persons. Based on these findings, the authors propose guidelines for how to identify and mitigate the effects of corporate psychopathy for organizations. Research limitations/implications – The proposed guidelines must be tested in an empirical paper to measure their effectiveness. Practical implications – The paper suggests an overall framework that may help leaders and organizational development practitioners identify the major factors which may be considered to safeguard against the potentially detrimental conduct of corporate psychopaths in their organizations. Social implications – This paper highlights the need to identify and ward against the presence of corporate psychopaths. There needs to be guidelines for organizations on how to identify and mitigate the effects of corporate psychopathy for organizations. Originality/value – The suggestion of integrating physiological methods of detection with the PCL, as well as urging proactive education of all employees as the symptoms and effects of corporate psychopathy, is the novel contribution of the paper.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.505
GPT teacher head0.359
Teacher spread0.147 · 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

Citations21
Published2015
Admission routes1
Has abstractyes

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