MétaCan
Menu
Back to cohort

Análise ética dos impactos da pandemia de COVID-19 na saúde de crianças e adolescentes

2022· article· pt· W4285297878 on OpenAlexaff
Raíssa Passos dos Santos, Eliane Tatsch Neves, Ivone Evangelista Cabral, Sydney Campbell, Franco A. Carnevale

Bibliographic record

VenueEscola Anna Nery · 2022
Typearticle
Languagept
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsInstitute for Work & HealthUniversity of TorontoInstitute of Health Services and Policy ResearchMcGill University
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)PhilosophyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

RESUMO A pandemia de COVID-19 trouxe impactos significativos para a vida de crianças e adolescentes em todo o mundo. Considerando esse contexto, o objetivo deste artigo foi examinar como as crianças e os adolescentes no Brasil foram impactados pela pandemia à luz de uma análise ética. Para tanto, uma análise interpretativa de estudos brasileiros sobre a saúde da criança e do adolescente durante a pandemia foi realizada. A tarefa de reconhecer essa dimensão ética é importante para entender como as respostas a situações de crise, tais como a presente situação da pandemia de COVID-19, podem ser moldadas e identificar quais as prioridades de ação de acordo com todas as partes interessadas, situando a criança entre essas partes de interesse. A análise demonstrou que tanto os efeitos diretos quanto os indiretos implicam em processos de tomada de decisão que precisam utilizar e sustentar o direito de participação da criança para que a ação tomada esteja o máximo possível focada nos melhores interesses da criança. Contudo, a realidade brasileira tem demonstrado uma exclusão estrutural das vozes infantis. Recomenda-se que mais estudos sejam conduzidos a fim de aprofundar o conhecimento sobre os melhores interesses das crianças e sua participação nas ações tomadas durante a pandemia.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.076
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.584
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0080.001
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0010.025
Insufficient payload (model declined to judge)0.0190.001

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 head0.132
GPT teacher head0.491
Teacher spread0.360 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEscola Anna NerySame topicEthics in medical practiceFrench-language works237,207