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Record W4407149281 · doi:10.25071/2564-2855.41

Recontextualization and production roles

2025· article· en· W4407149281 on OpenAlexaffvenue

Bibliographic record

VenueWorking papers in Applied Linguistics and Linguistics at York · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsYork University
Fundersnot available
KeywordsProduction (economics)Economics

Abstract

fetched live from OpenAlex

In a courtroom setting, a witness who is not a native speaker of the official language receives the services of a court interpreter, and the trial is transcribed by court reporters. In other words, once an utterance is produced by the witness, it undergoes two kinds of recontextualization involved in this process: it is 1) interpreted by the interpreter, and 2) recorded by the transcriptionist. This study investigates court transcripts of trials involving non-native witnesses and analyzes the shift of production roles when their utterance is interpreted and transcribed utilizing Goffman’s (1979) participation framework. The study found that the court transcripts represented the witnesses with inconsistency and vagueness, which blurs the animator and the author of the utterance at each phase, while holding the witness as the principal. In legal settings, this could lead to the witness being held accountable for the inconsistency rooted in the recontextualizations.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.260
Teacher spread0.233 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2025
Admission routes2
Has abstractyes

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