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Record W2910096604 · doi:10.31639/rbpfp.v8i14.133

Políticas de formação de formadores para educação de jovens e adultos (EJA) no plano nacional de educação PNE 2014-2024

2016· article· pt· W2910096604 on OpenAlexaff
Ada Augusta Celestino Bezerra, Márcia Alves de Carvalho Machado

Bibliographic record

VenueFormação Docente – Revista Brasileira de Pesquisa sobre Formação de Professores · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

A formação de formadores representa antigo desafio e relaciona-se à eficácia das políticas educacionais implementadas pelo Estado brasileiro. O PNE constitui-se em importante instrumento para enfrentar os desafios impostos à área educacional, entre eles os da formação de formadores da EJA. O objetivo deste trabalho é analisar conquistas e perdas do processo coletivo que precedeu o PNE 2014-2024, suas contradições, desafios e possibilidades nas instâncias locais e estaduais, no que se refere à formação de formadores para a EJA. O foco recai na responsabilização das universidades e demais instituições de educação superior para com a formação do professor da EJA, nem sempre contemplada nos projetos pedagógicos das licenciaturas. A história demonstra a necessidade de priorização da educação básica, especialmente da EJA, frente às novas demandas do sistema educacional articulado que se quer construir com a participação ativa dos formadores de formadores num processo contextualizado e pertinente.

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)0.006
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.395
Threshold uncertainty score0.786

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.051
GPT teacher head0.388
Teacher spread0.337 · 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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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