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Record W2078975190 · doi:10.5430/elr.v1n1p35

Fluent Speakers’ Management of Prospective Communication Breakdowns: The Case of Stuttering

2012· article· en· W2078975190 on OpenAlexvenueno aff
Stephanie Hughes, Farzan Irani, Derek E. Daniels

Bibliographic record

VenueEnglish Linguistics Research · 2012
Typearticle
Languageen
FieldPsychology
TopicStuttering Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsStutteringFluencyPsychologyShynessAnxietyFluentVerbal fluency testCognitionCognitive psychologyLinguisticsSocial psychologyDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

Stuttering is a disorder of verbal fluency that is often associated with such negative stereotypes as shyness and anxiety. This study investigates typically fluent speakers’ advice to both people who stutter (PWS) and other fluent speakers as they interact with each other. A written, open-ended, qualitative survey was administered to 135 members of the general public and analyzed thematically. Results indicate that stuttering is a disorder which engenders cognitive and emotional reactions in fluent speakers as well as proscribed communication strategies designed to prevent and manage communicative breakdowns. Fluent speakers appear to engage in high-level metalinguistic and metacognitive strategies as they interact with someone who stutters and believe that PWS should do the same. Research implications for those who work with people who have communication disorders in educational and healthcare settings are discussed.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.089
GPT teacher head0.443
Teacher spread0.354 · 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 designQualitative
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

Citations1
Published2012
Admission routes1
Has abstractyes

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