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Record W3186112551 · doi:10.52598/jpll/3/1/2

Willingness to Communicate and Second Language Speech Fluency: An Idiodynamic Investigation of Attractor States

2021· article· en· W3186112551 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

VenueJournal for the Psychology of Language Learning · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAttractorFluencyDynamics (music)PsychologyVerbal fluency testVocabularyCognitionCognitive psychologyComputer scienceLinguisticsMathematicsMathematics educationPedagogyNeuropsychology

Abstract

fetched live from OpenAlex

Willingness to communicate (WTC) has recently been researched as a dynamic variable, with some investigations viewing it as a complex dynamic system (CDS). One important property associated with CDS is the notion of attractor states, which are characterized by stable patterns of behavior. The present study employed an idiodynamic method to monitor per-second WTC changes with 20 participants during three-minute speaking tasks. Using idiodynamic graphs illustrating the WTC dynamics, patterns of stability were identified as the unit of analysis for WTC attractors. Temporal measures of the utterances that coincided with the WTC attractors were also examined. Results demonstrated that attractors were likely to emerge in both WTC and L2 fluency, and largely depended on two categories of content-related and linguistic-cognitive factors. Data analysis also indicates that WTC and L2 fluency exhibited parallel dynamics in most of the cases. The study’s findings yield pedagogical implications that are discussed at the end.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.579

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 studies0.0000.000
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 head0.052
GPT teacher head0.364
Teacher spread0.312 · 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