Language Idiosyncrasies in Second Language Learners’ Use of Communication Strategies
Bibliographic record
Abstract
The term, “language idiosyncrasies” can generally be defined as what an individual typically says that becomespart of his or her personality. In doing so, this language behaviour can either positively or negatively impactcommunication. Based on this premise, the current study sets out to examine the occurrences of languageidiosyncrasies in second language (L2) communication, particularly at the point when communication strategies(CSs) were employed to overcome communication problems. By employing non-participant observations of realuniversity admission interviews, this study departs from the other studies related to CSs which involvednon-authentic, simulated environments. The observed interview sessions were conducted in the English languageinvolving 29 Malay candidates from 20 interview sessions. These sessions were video-recorded before the rawdata were transcribed. The results revealed some occurrences of language idiosyncrasies in candidates’utterances hence, supporting Paribakht’s (1985) research finding that speakers exhibited idiosyncratic patterns inthe realization of communication strategies. The results also concurred with the findings of past studies on theinfluence of speakers’ L2 proficiency level on their use of CSs. As all participants were Malays communicatingin an English speaking context, issues on cultural values added to the richness of the data and will also bediscussed. While the findings may not be generalizable to all populations, it is hoped that this study will informcurriculum developers of language idiosyncrasies of Malay students, who form the bulk of the studentpopulation in Malaysia, so that awareness may be raised and appropriate interventions may be introduced.
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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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".