Bibliographic record
Abstract
The inadequacy of research studies in evaluating English for Special Purposes (ESP) textbooks in terms of pragmatic awareness should not be disregarded. The current study is an attempt to extend politeness and speech act theory to the analysis of ESP in hope of bridging the gap between the form of language and its function. Traditionally, studies on ESP focused basically on the syntactic and the lexical choices made by the learners in order to cope with specialized content and vocabulary. This paper aims to show how pragmatics is inherently incorporated in ESP contexts. The claim draws on an ESP textbook, English for Personal Assistants, to show how pragmatics is an integral constituent of this approach to EFL/ESL learning. The study attempts to promote theory-informed pragmatic awareness for ESP learners and teachers alike. To this end, the paper presents the theoretical framework upon which the argument is based. Then, an investigation is carried out with respect to how speech act theory and politeness theory can be drawn upon in order to establish a correlation between pragmatics and ESP.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".