MétaCan
Menu
Back to cohort
Record W2794965836 · doi:10.1177/2165079917750934

Extending the Duluth Model to Workplace Bullying: A Modification and Adaptation of the Workplace Power-Control Wheel

2018· article· en· W2794965836 on OpenAlexaff
Hannah Scott

Bibliographic record

VenueWorkplace Health & Safety · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsIntimidationCoercion (linguistics)PsychologyDomestic violenceSocial psychologyPower (physics)Isolation (microbiology)Poison controlAdaptation (eye)AggressionHuman factors and ergonomicsMedicineMedical emergency

Abstract

fetched live from OpenAlex

Workplace bullying (WB) is an increasingly prevalent topic in the nursing literature. Recently, a new concept has been introduced into WB research to explain the motivations of WB instigators using elements of the Power-Control Wheel (PCW). Initially, this wheel was designed to assist intimate partner violence (IPV) targets/victims identify patterns of abuse and intervene with male batterers/instigators. Research examining IPV and victims/survivors of WB demonstrate that targets often share common abusive experiences, including intimidation, coercion and threats, isolation, and economic and emotional abuse. This article demonstrates clear support for the Duluth Model and its application to WB target experiences. Applications of this model to identify WB and assist individuals to identify and describe experiences of abusive work environments are discussed.

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)0.004
metaresearch head score (Gemma)0.007
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: Methods · Consensus signal: Methods
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0020.013
Scholarly communication0.0050.005
Open science0.0030.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.041
GPT teacher head0.331
Teacher spread0.290 · 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
GenreMethods

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueWorkplace Health & SafetySame topicWorkplace Violence and BullyingFrench-language works237,207