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Record W2791661600 · doi:10.13037/gr.vol34n100.4399

ASSÉDIO MORAL NO TRABALHO: ESTADO DA ARTE E LACUNAS DE ESTUDOS

2018· article· pt· W2791661600 on OpenAlexaff
Juliana Moro Bueno Mendonça, Marcelo Augusto Finazzi Santos, Kesley Morais de Paula

Bibliographic record

VenueGestão & Regionalidade · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPhilosophySociologyArt

Abstract

fetched live from OpenAlex

Em virtude dos malefícios oriundos do assédio moral no trabalho e suas consequências deletérias na integridade física e psíquica dos trabalhadores, a temática merece atenção no âmbito dos estudos sociais e organizacionais. Realizou-se, assim, estudo bibliométrico de artigos em periódicos brasileiros relevantes nas áreas de Administração e Psicologia Social e do Trabalho datados de 2001 a outubro de 2016, além daqueles apresentados no congresso EnAnpad. Este estudo propicia um panorama da construção teórico-empírica sobre a temática de relevância social, indicando direções para futuras pesquisas. É preciso ampliar debates e estudos para o enfrentamento da violência moral a partir de olhares multidisciplinares, atuando de forma colaborativa. Desse modo, constatou-se a necessidade de fortalecimento do campo, para melhor compreensão do fenômeno, visto que o palco de sua ocorrência são justamente as organizações. Palavras-chave: Assédio moral; ambiente de trabalho; estado da arte; bibliometria; agenda de pesquisa.

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)0.060
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.018
Science and technology studies0.0120.048
Scholarly communication0.0380.026
Open science0.0030.017
Research integrity0.0040.005
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 head0.063
GPT teacher head0.332
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2018
Admission routes1
Has abstractyes

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