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Record W1741321712

Studying Tense in Classroom Discourse on the Base of Hallidayian Systemic Functional Grammar (SFG)

2011· article· en· W1741321712 on OpenAlexvenueno aff
Kamal Shayegh, Nasser Hassanzadeh, Frideh Hoseini

Bibliographic record

VenueJournal of academic and applied studies · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSystemic functional grammarLinguisticsGrammarDependent clauseSimple pastPsychologyCausativeSubject (documents)Competence (human resources)Traditional grammarComputer scienceVerbSentenceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

In functional approach to interpersonal metafunction, Halliday defines clause as a unit of exchange, with two main constituents called Mood and Residue. Mood is composed of Subject and Finite. Subject is invested with modal responsibility whereas finite realizes primary tense and modality. Residue includes predicator, complement and adjunct. Secondary tense is expressed throughout predicator while Complement and adjunct just add additional but unnecessary information to clause meaning. Derived from theoretical framework outlined above, present research tries its best to determine a kind of agreement between primary and secondary tenses in gender talk of ELT classrooms and its relation to bilingual language learners’ proficiency in their foreign language learning. About twelve hours of oral conversation between students and teachers from eight randomly selected classrooms are recorded and transcribed, resulting to 3288 clauses. Our findings show that both genders use simple present tense as primary one in their talks with high frequency to refer to events happening in present. It is found out that simple present tense is used much more for holding an unmarked grammatical structure; whereas using other temporal structures desire much more grammatical competence and subsequently are used with low frequency. This may result into students’ non-proficiency in grammar skill, making them use different and also wrong tenses in different given temporal situations in high levels of foreign language learning.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.121
GPT teacher head0.293
Teacher spread0.173 · 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.

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
Published2011
Admission routes1
Has abstractyes

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