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Record W4287510324 · doi:10.56238/sevedi76016-006

Impacto da tecnologia nos adolescentes durante a pandemia

2022· book-chapter· pt· W4287510324 on OpenAlexaff
Adilson Vagner de Oliveira, Leonardo Plaster Silva, Felipe Guedes Moreira Vieira

Bibliographic record

VenueSeven Editora eBooks · 2022
Typebook-chapter
Languagept
FieldSocial Sciences
TopicEducation during COVID-19 pandemic
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)PsychologyArtMedicine

Abstract

fetched live from OpenAlex

Este trabalho analisa o comportamento digital e educacional de estudantes adolescentes, durante o período de isolamento social, provocado pela pandemia da Covid-19 em 2020. Trata-se de uma pesquisa de natureza quantitativa, a partir de uma amostra de 272 participantes de Mato Grosso. Os resultados apontam que a) os adolescentes percebem os excessos na utilização de ferramentas digitais para as práticas de interação interpessoal, potencializadas pela pandemia; b) apesar do tempo disponível, durante o isolamento social, preferiram atividades de entretenimento mais passivas, como séries, filmes e jogos virtuais, com intensa desmotivação para realizar projetos artísticos e atividades intelectuais, mais exigentes, como leitura e estudos escolares. Portanto, mesmo diante de inúmeras ferramentas digitais e tecnológicas disponíveis para a aprendizagem e o entretenimento, os processos criativos e artísticos exigem elementos motivacionais exteriores que promovam a ação intelectual.

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)0.004
metaresearch head score (Gemma)0.020
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: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.048
GPT teacher head0.330
Teacher spread0.282 · 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
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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