To do or not to do: willingness to communicate in the ESL context
Bibliographic record
Abstract
English is used by more than one and a half billion people as a first, second or foreign language for communication purposes (Strevens, 1992). In this context, the purpose of teaching English has shifted from mastery of the grammatical rules to the ability to use the target language for successful communication. Consequently, the communication aspect of teaching and learning English has become the key issue in the domain of second language acquisition (Yashima, 2002: 54). Therefore, the issue of whether the learners will communicate in English when they have the chance to do so and to what extent they are willing to communicate gain importance. These questions have led to the emergence of an important construct in the field of L2 instruction, i.e. willingness to communicate (hereafter, WTC), which is defined as a learner's ‘readiness to enter into discourse at a particular time with a specific person or persons, using a L2’ (MacIntyre et al., 1998: 547). MacIntyre and his associates even proposed that WTC in L2 should be conceptualized as ‘the primary goal’ of language instruction (MacIntyre et al., 1998: 545). This paper explores the important concept of WTC by looking into Pakistani students' WTC in Canada.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".