EFL Iraqi Learners' Pragmatic Failure in English Animal Idiomatic Expressions
Bibliographic record
Abstract
This research concerns the pragmatic failure of the Iraqi EFL learners in interpreting the meanings of some sorts of idiomatic expression; namely, animal idiomatic expressions. Regardless of their grammatical formation, idiomatic expressions use tends to be largely dependent upon context. Pragmatic failure is a term which was first coined by Jenny Thomas in (1983) which is defined as the inability to understand what is said by what is intended. Pragmatic failure is of two types: pragma-linguistic and socio-pragmatic failure. As known, the meaning of animal idiomatic expressions vary from culture to culture, because of the difference of norms and principles the culture imposes on the residents of certain place. Pragmatically, the use of idiomatic expressions in English carry a diversity of meanings which learners of other languages will surely fall short in determining the exact intentions of speakers using these expressions as well as having a relation to the culture that the speech community has. The culture pragmatically place a major role too. However, this is due to the fact that idiomatic expressions have indirect speech acts and implicatures bond by the culture of the language that ought to be figured out by the learners. The study hypothesizes that most of EFL Iraqi learners will fail to interpret these expressions and also after putting these idiomatic expressions into their contexts.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".