SÍNDROME DE BURNOUT: O IMPACTO NA GESTÃO DE PESSOAS E FORMAS DE PREVENÇÃO
Bibliographic record
Abstract
Este artigo científico aborda o tema Síndrome de Burnout: o impacto na gestão de pessoas e formas de prevenção, e tem como objetivo conhecer a Síndrome de Burnout e as formas de prevenção através da gestão de pessoas. A metodologia deste estudo está ancorada em dois eixos científicos: pesquisa de campo e pesquisa bibliográfica. Foi realizada uma pesquisa de campo com 89 alunos de uma IES privada no extremo sul da Bahia através da aplicação de um questionário fechado. Os principais resultados obtidos na amostra pesquisada foram a presença de vários aspectos percorrendo as três principais dimensões abordadas pelo estudo de Benevides-Pereira (2002). O presente tema da pesquisa deve ser observado com o devido rigor através da gestão de pessoas, pois trata-se de um perigo silencioso e devastador na vida daqueles que são vulneráveis a ela e representa um fator de atenção para as empresas no mundo moderno.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".