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Record W4361858991 · doi:10.30681/rln.v2i4.6828

CRENÇAS E ENSINO DE LÍNGUAS – UMA ENTREVISTA COM ANA MARIA FERREIRA BARCELOS

2012· article· pt· W4361858991 on OpenAlexaboutno aff
Leandra Ines Seganfredo SANTOS

Bibliographic record

VenueRevista de Letras Norte mentos · 2012
Typearticle
Languagept
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Apresentação da entrevistada: quem é Ana Maria Ferreira Barcelos?Atualmente, Barcelos é professora Associada na Universidade Federal de Viçosa (UFV). Possui graduação em Letras Português/Inglês pela UFV (1989), mestrado em Lingüística Aplicada pela Universidade Estadual de Campinas (1995), doutorado em Teaching English As a Second Language - The University Of Alabama (2000) e pósdoutorado em Linguística Aplicada pela Universidade de Carleton, Ottawa, Canada (2009). Tem experiência na área de Lingüística Aplicada, com ênfase em crenças sobre

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)0.006
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.014
Scholarly communication0.0100.009
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.060
GPT teacher head0.319
Teacher spread0.259 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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