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O ensino de Língua Portuguesa através de um projeto de letramento: o jornal escolar

2019· article· pt· W2950620350 on OpenAlexaff
Ana Paula Silva Lino, Andréia Cunha Malheiros Santana

Bibliographic record

VenueSignum Estudos da Linguagem · 2019
Typearticle
Languagept
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

O presente trabalho tem como objetivo apresentar uma proposta para o ensino de língua portuguesa baseada na perspectiva do letramento. Trata-se de uma pesquisa-ação cujo objetivo específico foi a criação de um jornal escolar como estratégia para promover o ensino de língua portuguesa, a partir deste objetivo foram trabalhados os gêneros discursivos necessários à elaboração do jornal. Para tanto, este trabalho tem como base os documentos oficiais que regem a educação brasileira; os Estudos do Letramento, segundo Street (2014), Kleiman (1995, 2000, 2005, 2006a, 2010), Soares (2001). Também há a assunção da concepção sócio-histórica da linguagem baseada em Bakhtin (2003), considerando que as práticas sociais devem orientar o ensino da língua materna no contexto escolar. Como resultado, foi possível constatar que pensar no ensino a partir das práticas sociais colabora para o processo de ensino-aprendizagem, uma vez que a produção dos gêneros do jornal (BONINI, 2014), relacionada a questões dos alunos e da comunidade, conferiu maior sentido no momento da produção.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0170.008
Scholarly communication0.0110.004
Open science0.0010.009
Research integrity0.0020.002
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 head0.036
GPT teacher head0.318
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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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