Recontextualization and production roles
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".