Bibliographic record
Abstract
Written discourse completion tasks (WDCTs) have frequently been employed in pragmatics research as a key research instrument in eliciting the production of speech acts by second language learners while studies incorporating verbal report have provided evidence of the processes involved in second language speech act production. This study responds to the call to include native speakers in verbal protocol research and focuses on the paired concurrent verbal report of six English native speakers, elicited in conjunction with their responses to 18 WDCTs eliciting English requests. The study aimed to identify the focus of participants’ attention while on task and employed content analysis to identify themes emerging from the participants’ verbal protocols. Findings from the analysis suggest that participants’ attention may be directed to perceived deficiencies in the elicitation instrument, reflecting criticisms in the research literature relating to the design and authenticity of WDCTs. Secondly, the study found that participants may respond to these deficiencies by recreating the task within an authentic speech event. In providing a respondent perspective on the research methodology, the study highlights implications for the design and employment of WDCTs in eliciting speech acts in second language acquisition research.
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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 | 0.034 | 0.194 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".