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Record W2511522655 · doi:10.1080/09518390310001632171

Transcription work: learning through coparticipation in research practices

2003· article· en· W2511522655 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

VenueInternational Journal of Qualitative Studies in Education · 2003
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsBrock University
FundersUniversity of Cambridge
KeywordsTranscription (linguistics)Focus groupQualitative researchPedagogyPsychologyContext (archaeology)Participant observationSemi-structured interviewMedical educationSociologyMedicineSocial science

Abstract

fetched live from OpenAlex

The focus for this paper evolved out of doctoral research conducted by the author with incarcerated women attending a prison school. During that project, she hired an assistant to transcribe audiotapes of interviews, participant observations, and field notes. In this paper, one context‐specific case is used to examine the complexities of transcription work involving a person other than the researcher. Lave and Wenger's (1991) “legitimate peripheral participation” serves as an analytical framework to explore the learning experienced by both researcher and transcriber as a result of their co‐participation in the project. Transcripts of four interviews conducted with the transcriber provide the basis for the investigation. The findings disrupt simplistic notions of the transcription process and show how peripheral participation can lead to educational experiences for those involved.

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)0.006
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.666
GPT teacher head0.645
Teacher spread0.021 · 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