Production and Perception of Stylistic Variation along the Continuum of Formality in English as a First and Second Language
Bibliographic record
Abstract
This research explores production and perception of stylistic variation along the continuum of formality in written English. It looks to contribute to research focused on sociopragmatic and pragmalinguistic competence by (1) offering insights into English-dominant individuals’ and English learners’ understanding of formality, knowledge of stylistic variants, and approach to the expression and perception of formality; (2) demonstrating how English-dominant individuals and English learners create styles with specific degrees of formality and how they perceive degrees of formality; and, (3) reporting English-dominant individuals’ and English learners’ confidence about their ability to express and perceive formality. To these ends, data for this research were collected in two subsequent phases (i.e., a production and a perception phase), with each drawing on its own set of participants. Each set included three groups of individuals: those who live in Canada and speak English as a dominant language, those who are learning English while embedded in the Canadian context, and those who are learning English as a foreign language in Slovakia. In both phases, questionnaire data were collected to discover participants’ understanding of formality and knowledge of stylistic variants. The participants in the production phase composed six e-mail messages in English with a specific degree of formality in mind. The participants in the perception phase rated the formality of 18 of the e-mail messages that had been generated by the participants in the production phase. The findings show that, in contrast to the English-dominant individuals, both groups of English learners were less able to provide specific examples of (in)formal stylistic variants; the preferred use of stylistic variants differed across the three participant groups; and the perceived degrees of formality for half of the e-mail messages differed across the three participant groups. The findings also showed that the English learners felt less confident than did the English-dominant individuals about their ability to express and perceive formality in English. This research concludes that English learners would benefit from instruction that increases their knowledge of salient (in)formal stylistic variants and that raises their awareness of the social, cultural, and personal factors that influence their use in English.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".