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AÇÕES EXTENSIONISTAS EM MEIO A PANDEMIA

2021· article· pt· W4205417912 on OpenAlexaff
Ítalo Matheus Batista Medeiros, Gabriela Pereira de Araújo Dantas, Vitória Jade Alves de Carvalho, André Luiz de Melo Sousa, Amíria Bezerra Brasil

Bibliographic record

VenueRevista Extensão & Sociedade · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicEducation during COVID-19 pandemic
Canadian institutionsGreenfield Research (Canada)
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)PhilosophyArtMedicine

Abstract

fetched live from OpenAlex

Apesar da ampla veiculação de notícias e recomendações acerca da pandemia do novo Coronavírus - e da doença COVID-19 - o EMAU Maré e o grupo ATHIS da UFRN identificaram que a linguagem e a representação dessas eram muito técnicas, e viram a necessidade de produzir um material de mais fácil compreensão direcionado para as comunidades populares. O conteúdo audiovisual também partiu da urgência de repensar a extensão universitária em um contexto de distanciamento social, visualizando a internet e as redes sociais como um instrumento para que os grupos extensionistas pudessem fomentar a discussão da saúde nos assentamentos populares. Assim, neste artigo será discutida a necessidade de criar material que corresponda à realidade dessas pessoas e serão apresentados a metodologia, o conteúdo e o público-alvo da cartilha e dos vídeos produzidos pelo grupo. Palavras-chave: extensão; Covid-19; assentamentos populares; linguagem acessível; cartilha informativa.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0040.005
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.003

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 head0.062
GPT teacher head0.375
Teacher spread0.314 · 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 designObservational
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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