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Record W4315781980 · doi:10.1108/joepp-07-2022-0215

How contemptuous leaders might harm their organization by putting high-performing followers in their place

2023· article· en· W4315781980 on OpenAlexaff
Dirk De Clercq, Muhammad Umer Azeem, Inam Ul Haq

Bibliographic record

VenueJournal of Organizational Effectiveness People and Performance · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBrock University
Fundersnot available
KeywordsContemptOrganizational citizenship behaviorHarmSocial psychologyPublic relationsPsychologyOriginalityValue (mathematics)Abusive supervisionAbuse of powerOrganizational commitmentPolitical scienceLaw

Abstract

fetched live from OpenAlex

Purpose This study investigates how leaders react when they perceive a threat to their hierarchical position, such as by engaging in abusive supervision in ways that diminish followers’ organizational citizenship behavior. It also tests for a dual harmful role of leaders’ dispositional contempt in this process. Design/methodology/approach Three-wave survey data were collected among 231 leader–follower dyads across different industry sectors. Findings Leaders’ beliefs that their authority is being threatened by high-performing followers can lead followers to halt their voluntary work behaviors, because leaders engage in verbal abuse. The harmful role of leaders’ dispositional contempt in this process is twofold: It enhances abusive supervision directly, and it operates as an indirect catalyst of the mediating role of abusive supervision. Practical implications Organizations would be better placed to decrease the risk that disruptions of the hierarchical order, as perceived by leaders, escalate into diminished work-related voluntarism among employee bases by promoting leadership approaches that consider employees deserving of respect instead of disdain. Originality/value This study details how and when leaders who fear they may lose authority, evoked by the strong performance of their followers, actually discourage followers from doing anything more than their formal job duties.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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 designObservational
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

Citations4
Published2023
Admission routes1
Has abstractyes

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