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Record W2103278035 · doi:10.1177/0950017014563105

Workplace bullying: exploring an emerging framework

2015· article· en· W2103278035 on OpenAlexaff
Adriana Berlingieri

Bibliographic record

VenueWork Employment and Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOppressionWorkplace bullyingPhenomenonSociologyPower (physics)Workplace violenceFocus (optics)Social psychologyPoison controlPublic relationsPsychologyHuman factors and ergonomicsEpistemologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

To date, emphasis within the literature on workplace bullying has been on gathering empirical data with a focus on individual acts, actors (targets and perpetrators) and consequences. This analytical focus has resulted in an understanding of workplace bullying as fundamentally an individualized phenomenon. This article begins with a brief discussion of the theorization that currently predominates in the workplace violence and bullying literature and the outcomes of this theorizing. An emerging framework, conceptualizing violence broadly, is then outlined for understanding violence and bullying. Through this framework, it is argued that the discourse and research on workplace violence – in all its forms – must explore explicit connections between these social phenomena and the interrelatedness of all forms of oppression. Workplace violence must be examined within a framework where power cannot be separated from social dimensions within and outside the workplace.

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)0.006
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.004
Science and technology studies0.0080.032
Scholarly communication0.0140.015
Open science0.0040.009
Research integrity0.0050.006
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 head0.146
GPT teacher head0.354
Teacher spread0.209 · 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 designQualitative
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

Citations45
Published2015
Admission routes1
Has abstractyes

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