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Record W2032340166 · doi:10.1075/japc.17.1.06coo

Beyond Language

2007· article· en· W2032340166 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Asian Pacific Communication · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsYork University
Fundersnot available
KeywordsArgument (complex analysis)Construct (python library)Resistance (ecology)CurriculumSociologyPsychologyPower (physics)Discourse analysisCompliance (psychology)Raising (metalworking)LinguisticsPedagogyMathematics educationSocial psychologyComputer science

Abstract

fetched live from OpenAlex

Drawing on data from three New Zealand worksites, an analysis of transcripts suggests a pattern of regulation, compliance and resistance, in which small talk aids the exercise of power. To consider the implications of workplace dialogues for L2 workers, the study looks at recorded conversations in the light of Gee’s (1999) concept of “building tasks” in discourse analysis, revealing the importance of “language and beyond” — language that carries constant reference to social realities, inside and outside worksites, that construct interactions among workers. The paper derives conclusions for language instruction, language learners and the personnel of workplaces, arguing that language instruction (e.g., teachers and curriculum developers) can benefit from an awareness of the above issues and include attention to social realities in language courses. Despite debate in the literature, the argument supports the analysis of authentic texts, “battered texts”, and the findings of linguistic analysis in L2 teaching, and proposes consciousness-raising in workplaces.

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.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.281
Teacher spread0.266 · 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