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Record W7120543229

Historical knowledge after BNCC and the New High School: changes and permanences of a school discipline

2024· dissertation· pt· W7120543229 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2024
Typedissertation
Languagept
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsNoticeAutonomyDisciplineReading (process)CurriculumState (computer science)DocumentationNeoliberalism (international relations)Educational research
DOInot available

Abstract

fetched live from OpenAlex

This research investigates the changes and the continuation in History teaching after the approval of the National Common Curricular Base (BNCC) and the Reform called New High School (NEM). The research starts from the reading key that associates these educational reforms with neoliberalism (LAVAL, 2019). It is also important for this research to analyze the “narrative warfare” around the History curriculum (LAVILLE, 1999), to investigate the conflicts and conceptions of History teaching, brought to the midst of debates about reforms and the concept of disciplinary code (FERNÁNDEZ, 1997) to think about the changes and the permanencies in History teaching. An investigation was carried out into the documentation that instituted the reforms, such as Law No. 13,415/2017 (High School reform), texts from the 1st, 2nd and 3rd versions of the BNCC and the DCRC (Ceará Reference Curricular Document). The research was carried out using quantitative and qualitative methodology, using a questionnaire, with 50 answers; 6 interviews with High School History teachers from the Ceará state schools network. Among the results, it was found that the reforms studied affect teachers in different ways, depending on the school model and the teacher's stability in the education network and at the school. 92% responded that they notice changes in history teaching, caused by the reduction of the workload, which leads to increasingly larger cuts by teachers, the lack of rganization of content by grade, the organization of content by skills and abilities and the absence of a History book. However, the teachers also state that they feel more autonomy to choose the contents after the reforms (18%) and 78% stated thatw although they feel negative impacts, they are able to maintain autonomy in their teaching practices.

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)0.010
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 score0.028
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.012
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0010.002
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 head0.044
GPT teacher head0.313
Teacher spread0.268 · 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
Published2024
Admission routes1
Has abstractyes

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