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Record W2152299683 · doi:10.1017/s0047404506350348

<scp>Gene Lerner</scp> (ed.), <i>Conversation analysis: Studies from the first generation</i>

2006· article· en· W2152299683 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLanguage in Society · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConversationConversation analysisSociologyMedia studiesPsychologyLinguisticsPhilosophyCommunication

Abstract

fetched live from OpenAlex

Gene Lerner (ed.), Conversation analysis: Studies from the first generation . Amsterdam: John Benjamins, 2004. Pp. 300. Hb $138.00, Pb $65.95. Conversation analysis developed in the mid to late 1960s in a collaboration initially between Harvey Sacks and Emanuel Schegloff and, somewhat later, with the addition of Gail Jefferson. By the early 1970s, several students joined the group, by this point based at the University of California campuses at Irvine and Los Angeles, to form what Lerner calls “the first generation.” Conversation analysis has continued to grow, indeed has flourished, in the years since. Today conversation analysts are to be found not only in the United Stated, Canada, and the United Kingdom, but also Japan, Korea, Germany, Finland, the Netherlands, and many other countries. There are conversation analysts in departments of sociology, linguistics, anthropology, communication, and psychology, as well as in many modern language and applied programs. The widespread success of conversation analysis is largely attributable to three characteristics of its research program:

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)0.000
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: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.036
GPT teacher head0.275
Teacher spread0.239 · 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