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Record W3017080358 · doi:10.1075/slsi.33.01bet

Mobilizing others

2020· book-chapter· en· W3017080358 on OpenAlexaff
Emma Betz, Carmen Taleghani‐Nikazm, Peter Golato

Bibliographic record

VenueStudies in language and social interaction · 2020
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Abstract “Mobilizing others” takes a holistic perspective on the practices that we use to get others to act with, and for, us. This introduction reviews recent conceptual developments, notably ‘recruitment’ ( Section 1 ), and then opens up new territory by arguing for a more explicit focus on ‘activity’ in describing how mobilizing moves are accountably produced and understood. After summarizing existing research on ‘activity’ ( 2 ) we highlight how embodiment and temporality figure crucially in interactants’ use of grammatical, vocal, and embodied resources to reflexively organize larger courses of action ( 3 ). Focusing on ‘situation design’ captures the importance of the overall activity for the design, placement, and understanding of mobilizing turns, and makes visible implicit layers of organization which relevantly shape local conduct.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.719
Threshold uncertainty score1.000

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)0.0010.000

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 head0.147
GPT teacher head0.383
Teacher spread0.236 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreOther

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

Citations3
Published2020
Admission routes1
Has abstractyes

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