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Record W1978154916 · doi:10.1108/tpm-07-2012-0023

Explaining bullying: using theory to answer practical questions

2013· article· en· W1978154916 on OpenAlexaff
Céleste M. Brotheridge

Bibliographic record

VenueTeam Performance Management · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPerspective (graphical)Workplace bullyingPsychologyContext (archaeology)Social psychologyProcess (computing)PersonalityApplied psychologyComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to build a practical understanding of the workplace bullying process through the perspective of multiple theories. Design/methodology/approach The paper presents a number of questions regarding bullying in the workplace that a practitioner, described in the paper, may have. Then, each question is answered through the vantage point of a particular theoretical perspective. In particular, theories are referenced that have not typically been used to explain workplace bullying, but that have proven useful for understanding behavior in other contexts. Findings The answers to a number of practical questions are informed by multiple theoretical perspectives on workplace bullying. These questions include why people engage in and persist in bullying others, why certain individuals are targeted by bullies, how targets deal with bullying, and why bullying may be tolerated in organizations. Bullying is complex and multi‐determined. It is, in part, an individual level problem concerning the dyadic relationship between two individuals. In this manner, it can be seen that there are various personality attributes, both strengths and weaknesses, and personal background characteristics at play in the bully‐target relationship. However, it is grounded in a social context, at the team level and more broadly, that permits it to happen and indeed fosters its development. This context includes other individuals in the workplace who support it in some fashion, the work team and the organization itself. Practical implications Although there are no simple answers, managers and human resource professionals can draw upon the insights that are presented as a means of planning multiple points of intervention in the bullying process. Originality/value The paper builds a bridge between theory and practice as a means of connecting researchers and managers. The sampling of theoretical perspectives that are employed answer relevant questions in a coherent manner and, in doing so, provide a unique way of understanding bullying.

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)0.033
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.042
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.004
Science and technology studies0.0050.027
Scholarly communication0.0100.021
Open science0.0060.009
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.040
GPT teacher head0.344
Teacher spread0.305 · 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 designTheoretical or conceptual
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

Citations14
Published2013
Admission routes1
Has abstractyes

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