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Record W2744440691

OS CADERNOS DE NORMALISTA NO ESTADO DO PARANÁ NA DÉCADA DE 1970: sinais e vestígios de como ensinar a matemática

2017· article· pt· W2744440691 on OpenAlexaff
Reginaldo Rodrigues da Costa, Wagner Alexandre do Amaral

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsVESTPhysicsHumanitiesPhilosophyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Este texto apresenta dados parciais de uma investigação sobre os conhecimentos sobre o ensino de matemática na formação de professores da escola normal e/ou no magistério de 2º grau no período de 1970 a 1990. A análise de vestígios das orientações de como a matemática deveria ser tratada nas séries iniciais a partir de dois cadernos de uma aluna que frequentou o curso normal na década de 1970. A partir dessas fontes e sua triangulação com programas de ensino e orientações da Secretaria da Educação do Estado do Paraná, foi possível observar que os conteúdos, os objetivos de ensino, os recursos, as atividades de aprendizagem, a ação do professor e do aluno se aproximam das orientações oficias paranaenses na década de 1970. Além disso, ao observar os cadernos foi possível identificar um forte traço da abordagem tecnicista sobre a elaboração da prática pedagógica, seja em relação à aluna no curso normal, como também na condução da prática a ser desenvolvida na escola de aplicação.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.450

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.004
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.384
GPT teacher head0.624
Teacher spread0.241 · 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 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
Published2017
Admission routes1
Has abstractyes

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