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Record W2607646044 · doi:10.1017/s0047404517000173

Action in interaction is conduct under a description

2017· article· en· W2607646044 on OpenAlexaff
Jack Sidnell

Bibliographic record

VenueLanguage in Society · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAction (physics)ConversationConversation analysisCategorizationKey (lock)AccountabilityComputer scienceOrder (exchange)EpistemologyPsychologyCommunicationPolitical scienceArtificial intelligenceBusinessComputer securityLaw

Abstract

fetched live from OpenAlex

Abstract Requests, offers, invitations, complaints, and greetings are some of the many action types routinely invoked in the description and analysis of interaction. But what is the ontological status of, for instance, a request? In what follows I propose that action is conduct under a description. Thus, for the most part, interaction is organized independently of any action description or categorization of conduct into discrete action types. Instead, participants in interaction draw on the details of the situation in which they find themselves in order to produce conduct that others will recognize and to which they are able to respond in fitted ways. ‘Action’ still plays a key role in the organization of interaction, however, because accountability attaches not to raw conduct but only to conduct under some particular, action-formulating description. (Action, interaction, description, conversation analysis, Anscombe)*

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.037
Scholarly communication0.0080.013
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.233
GPT teacher head0.404
Teacher spread0.171 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations93
Published2017
Admission routes1
Has abstractyes

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