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Record W2728596954

DESAFIOS EM RELAÇÃO AO USO DA LÍNGUA INGLESA: CONSIDERAÇÕES A PARTIR DE EXPERIÊNCIAS DE UM GRUPO DE UNIVERSITÁRIOS BRASILEIROS EM CONTEXTO DE INTERCÂMBIO

2016· article· pt· W2728596954 on OpenAlexaboutno aff
Talita Aparecida de Oliveira, Eliane Hércules Augusto-Navarro

Bibliographic record

Venuerevista Linguasagem · 2016
Typearticle
Languagept
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophySociology
DOInot available

Abstract

fetched live from OpenAlex

Programas de internacionalizacao das ciencias por meio de intercâmbio de alunos em contexto academico tem se intensificado em nosso pais e tornaram-se realidade durante a graduacao de alunos brasileiros. Considerando esse panorama, este trabalho tem como objetivo discutir necessidades linguisticas e pragmaticas apontadas por alunos de uma universidade publica do Estado de Sao Paulo, participantes de programas de intercâmbio (por meio do programa Ciencia sem Fronteiras), especialmente nos Estados Unidos, Canada e Inglaterra, para que se possa pensar em pressupostos ao se planejar cursos e materiais didaticos que considerem necessidades e desafios linguisticos previsiveis para universitarios brasileiros candidatos a intercâmbio em paises de lingua inglesa. Para alcancar tal objetivo, temos como base teorias relacionadas a analise de necessidade (DUDLEY-EVANS E ST JOHN, 2010), questoes pragmaticas (ANDRADE, 2013) e culturais (HINKEL, 2012). Alguns dos pressupostos identificados nesta pesquisa sao: a importância de sensibilizar os futuros intercambistas sobre maneiras apropriadas de se dirigir a professores e supervisores; a organizacao de generos academicos, como apresentacao oral de pequenos trabalhos em sala de aula; lidar com diferentes sotaques, tanto de falantes nativos do ingles como de estrangeiros de diferentes paises, entre outros discutidos no texto.

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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.064
GPT teacher head0.329
Teacher spread0.265 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuerevista LinguasagemSame topicDiscourse Analysis in Language StudiesFrench-language works237,207