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Record W6892448657 · doi:10.5281/zenodo.10073500

ENSINO INTERCULTURAL DE ESTEREÓTIPOS EM ATIVIDADES DE LÍNGUA ESTRANGEIRA: UMA REFLEXÃO CRÍTICA E DIALÓGICA PARA UMA POSIÇÃO RESPONSIVA EM SALA DE AULA

2023· article· pt· W6892448657 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languagept
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Order (exchange)Happening

Abstract

fetched live from OpenAlex

Resumo: Este artigo foi produzido com o intuito de apresentar conceitos bakhtinianos ao professor de língua estrangeira a fim de que, a partir de atividades interculturais que tenham como tema estereótipos, ele possa conduzir a uma reflexão crítica e dialógica, o que estimula o aluno a adotar uma posição responsiva. Trata-se de uma pesquisa qualitativa que se propõe a analisar uma atividade chamada les stéréotypes, produzida e disponibilizada pelo site público do governo de Québec TV5 Monde, à luz da teoria dialógica do teórico e filósofo russo Mikhail Bakhtin (2011). De acordo com Hinton (2000), a pesquisa em torno dos estereótipos é entendida por diferentes perspectivas, sublinhando o caráter inevitável dos processos cognitivos humanos que desenvolvem os diferentes tipos de estereótipos, os quais se revelam úteis ou inconvenientes dependendo das situações quotidianas onde são levantados. Buscamos, portanto, usar os conceitos bakhtinianos de dialogia, plurilinguismo e atitude responsiva para analisar e esclarecer as possibilidades de tratamento do tema estereótipos em sala de aula de língua estrangeira. Esses conceitos nos levaram a concluir que a atividade analisada só poderia ser utilizada no contexto brasileiro de uma sala de aula de Língua Estrangeira caso fosse adaptada às noções que esta sociedade tem acerca dos países referidos.

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)0.002
metaresearch head score (Gemma)0.004
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0060.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0230.014

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 head0.113
GPT teacher head0.330
Teacher spread0.217 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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