Pragmatic Markers Produced by Multilingual Speakers: Evidence From a CLIL Context
Bibliographic record
Abstract
The purpose of this study is to investigate the production of pragmatic markers (PMs) by multilingual students in a CLIL context. Previous studies have analyzed pragmatic competence in multilingual settings (e.g., Cenoz, 2003; Martín-Laguna & Alcón-Soler, 2015; Portolés, 2015; Safont & Portolés, 2016). However, to the best of our knowledge, no previous study has investigated the use of PMs across languages at the oral level in the multilingual classroom. As suggested by Nashaat-Sobhy (2017, p. 69), there is a need for studies that support or refute whether CLIL helps students communicate more appropriately. In an attempt to fill this gap, the overall aim of this research study is to explore how multilingual students use PMs across languages –namely Spanish, Catalan and English- in terms of frequency and type of PM. Participants were 19 Spanish students in an instructional context where three languages are in contact, namely English, Catalan and Spanish. They completed a language background questionnaire and comparable oral decision-making tasks carried out in pairs, one task in each of the target languages. The analysis explored the frequency and type of PMs (i.e. textual and interpersonal markers). Findings revealed significant differences in the frequency and type of both interpersonal and textual PMs across the three languages, shedding some light on the particular characteristics of the pragmatic competence of multilingual learners in a CLIL setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 teacher head, 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".