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Record W2277978090 · doi:10.1075/pbns.129

Building Coherence and Cohesion

2004· book· en· W2277978090 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

VenuePragmatics & beyond. New series · 2004
Typebook
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCohesion (chemistry)Computer scienceRhetorical questionLinguisticsCoherence (philosophical gambling strategy)Task (project management)Natural language processingEngineering

Abstract

fetched live from OpenAlex

This book examines the resources that speakers employ when building conversations. These resources contribute to overall coherence and cohesion, which speakers create and maintain interactively as they build on each other’s contributions. The study is cross-linguistic, drawing on parallel corpora of task-oriented dialogues between dyads of native speakers of English and Spanish. The framework of the investigation is the analysis of speech genres and their staging; the analysis shows that each stage in the dialogues exhibits different thematic, rhetorical, and cohesive relations. The main contributions of the book are: a corpus-based characterization of a spoken genre (task-oriented dialogue); the compilation of a body of analysis tools for generic analysis; application of English-based analyses to Spanish and comparison between the two languages; and a study of the characteristics of each generic stage in task-oriented dialogue.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.547
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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