Uses and Functions of Formulaic Sequences in Second-Language Speech: An Exploration of the Foundations of Fluency
Bibliographic record
Abstract
Formulaic sequences are fixed combinations of words that have a range of functions and uses in speech production and communication, and seem to be cognitively stored and retrieved by speakers as if they were single words. They can facilitate fluency in speech by making pauses shorter and less frequent, and allowing longer runs of speech between pauses. The present study was undertaken to identify the uses and functions of formulaic sequences in the development of speech fluency in narrative retelling in English as a second language (ESL). Spontaneous spoken narrative retells by ESL learners were analyzed for ways in which use of formulaic sequences may have facilitated fluency growth over a six-month period, be they pragmatic, functional, or strategic. Five categories of formula use emerged: repetition of a formula; use of multiple formulas to extend a run; reliance on one formula; use of self-talk and filler formulas; and use of formulas as rhetorical devices. These categories are illustrated by excerpts from transcripts of learner speech. Les expressions stéréotypées sont des combinaisons fixes de mots qui ont divers usages et rôles dans la production du langage et la communication. Elles semblent être cognitivement enregistrées et récupérées par les usagers comme s'il s'agissait d'un seul mot. Ces expressions peuvent améliorer la fluidité verbale d'un discours en diminuant la longueur et la fréquence des pauses, et en permettant de plus longues séquences de discours ininterrompues entre les pauses. La présente étude a été effectuée dans le but de déterminer l'usage et le rôle des expressions stéréotypées dans le développement de la fluidité verbale pour les exposés redits en anglais, langue seconde (ALS). On a analysé les exposés oraux redits spontanément par des étudiants en ALS afin de trouver comment les expressions stéréotypées ont favorisé le développement de la fluidité au cours d'une période de six mois, peu importe que les expressions soient pragmatiques, fonctionnelles ou stratégiques. Cinq catégories d'expressions se sont dégagées : la répétition d'une expression ; l'enchaînement de multiples expressions ; le recours à une [End Page 13] seule expression ; l'emploi de la verbalisation intérieure et d'expressions de remplissage ; et l'emploi d'expressions comme figure de style. Pour chacune de ces catégories, on donne des exemples tirés de la transcription des discours des étudiants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".