A SAÚDE MENTAL DO PÓS-GRADUANDO BRASILEIRO NA PANDEMIA DE COVID-19: UMA ANÁLISE DE FATORES ASSOCIADOS À DEPRESSÃO, ANSIEDADE E O ESTRESSE
Bibliographic record
Abstract
A SAÚDE MENTAL DO PÓS-GRADUANDO BRASILEIRO NA PANDEMIA DE COVID-19: UMA ANÁLISE DE FATORES ASSOCIADOS À DEPRESSÃO, ANSIEDADE E O ESTRESSE Post Artigo - Editora Omnis Scientia | Entrar Início Institucional Blog Catálogo Normas Corpo Editorial Indexadores Parceiros Contato A SAÚDE MENTAL DO PÓS-GRADUANDO BRASILEIRO NA PANDEMIA DE COVID-19: UMA ANÁLISE DE FATORES ASSOCIADOS À DEPRESSÃO, ANSIEDADE E O ESTRESSE A pandemia de Covid-19 tem sido responsável por significativos impactos sociais, econômicos, políticos e em saúde ao redor do mundo (FARO et al., 2020). Na educação, a pandemia alterou o cotidiano de estudantes inseridos nos mais variados contextos de ensino, com destaque para os pósgraduandos que vivenciam diversos desafios no trabalho em que estão inseridos, especialmente no que se refere às questões pessoais e profissionais. As grandes exigências junto a esse público causam consequências em saúde, com maior disposição para o adoecimento mental, incluindo a depressão, ansiedade e risco de suicídio (GARCIA DA COSTA, NEBEL, 2018). Descrição Autores Download Ler Online A SAÚDE MENTAL DO PÓS-GRADUANDO BRASILEIRO NA PANDEMIA DE COVID-19: UMA ANÁLISE DE FATORES ASSOCIADOS À DEPRESSÃO, ANSIEDADE E O ESTRESSE Doi: 10.47094/IICOLUBRAIS2022/41 PALAVRAS CHAVE: Saúde Mental. Pandemia. Educação de Pós-Graduação. KEYWORDS: Mental health. Pandemic. Graduate Education. ABSTRACT:The Covid-19 pandemic has been responsible for significant social, economic, political and health impacts around the world (FARO et al., 2020). In education, the pandemic has changed the daily lives of students inserted in the most varied teaching contexts, with emphasis on graduate students who experience various challenges in the work in which they are inserted, especially with regard to personal and professional issues. The great demands on this public have health consequences, with a greater disposition towards mental illness, including depression, anxiety and suicide risk (GARCIA DA COSTA, NEBEL, 2018). Autores Adriana Inocenti Miasso Assis do Carmo Pereira Junior Gabriela Di Donato Kelly Graziani Giacchero Vedana Laysa Fernanda Silva Pedrollo Nayara Paula Fernandes Martins Molina Download Editora Institucional Blog Catálogos Todos Navegação Início Catálogos Contato © 2021 Editora Omnis Scientia - Todos os direitos reservados. Desenvolvido por Alexsander Arcelino Olá 👋 Podemos te ajudar?
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".