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Record W3209072684 · doi:10.1080/08351813.2021.1974745

What Do Newsmark-Type Responses Invite? The Response Space After German <i>echt</i>

2021· article· en· W3209072684 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

VenueResearch on Language and Social Interaction · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsConversationGermanSpace (punctuation)Relevance (law)PsychologySociologyLinguisticsSocial psychologyCommunicationPhilosophyPolitical science

Abstract

fetched live from OpenAlex

This conversation analytic study examines responsive echt (“really”), which is commonly associated with “newsmarks,” in co-present German interaction. Across uses, echt-turns are a practice for topicalizing, however briefly, something in another participant’s just-prior turn. But this topicalization shapes the response space in systematically different ways: Echt-turns can be taken to (a) invite simple reconfirmation, (b) invite topical elaboration, or (c) solicit an account either to reconcile diverging expectations or to manage problems in acceptability. We demonstrate how both the design of echt-turns and participants’ epistemic positioning matter to how echt-turns are treated and shape interactional trajectories. By using the notion of “inviting” a next action, we highlight the importance of conceptualizing response relevance after second-position actions, and specifically after “newsmark-type” responses, as a gradient. Data are taken from everyday and institutional interaction and presented in German with English translations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.129
GPT teacher head0.458
Teacher spread0.330 · 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