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Record W2884631709

Formação de Professores de Ciências na perspectiva da Inclusão de Pessoas com Deficiências no Vale do Jaguari

2018· article· pt· W2884631709 on OpenAlexvenueno aff
Denise Gabriel de Melo, Simone Medianeira Franzin

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesSociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Diante das transformacoes da educacao brasileira, licenciandos e professores atuantes necessitam refletir sobre sua identidade, em especial sobre a educacao inclusiva, contribuindo para a construcao de novos rumos do ensino de pessoas com deficiencia. O trabalho teve como objetivo identificar a percentagem de pessoas com deficiencias nos municipios do Vale do Jaguari/RS, e analisar a realidade das Escolas do municipio com maior indice de deficiencia em duas fontes da pesquisa inicial, verificando a formacao dos professores de Ciencias que trabalham com alunos com deficiencia. O trabalho foi realizado no Instituto Federal Farroupillha Campus Sao Vicente do Sul, no ano de 2016, em duas etapas: a primeira composta pela analise estatistica dos dados de pessoas com deficiencia baseados no IBGE (2010) e FADERS (2010) e a segunda na aplicacao de questionarios para professores de Ciencias das escolas do municipio selecionado. Observou-se percentual elevado de pessoas com deficiencias nos municipios do Vale do Jaguari e uma percentagem de matriculados na rede basica de educacao.  Evidencia-se que a inclusao de pessoas com deficiencia necessita mais do que a obrigatoriedade legal, dando prioridade para condicoes de participacao e aprendizagem tanto na sala de aula quanto em outros espacos da vida cidada.

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)0.015
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0030.007
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.154
GPT teacher head0.477
Teacher spread0.323 · 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 designQualitative
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

Citations0
Published2018
Admission routes1
Has abstractyes

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