Distribution of Articles in Malaysian Secondary School English Language Textbooks
Bibliographic record
Abstract
This paper reports the results of a corpus-based study on English grammar articles presented in the Malaysian Form 1 to Form 5 English Language textbooks. The study aimed to find out the distribution patterns of the articles and the distributions of their colligation patterns in the secondary school English Language textbooks. The findings showed that all the three articles (a, an, the) are presented in all the five English Language textbooks and that their frequency of occurrences has an increasing trend from Form 1 to Form 5. However, the distributions of the colligation patterns of the articles showed inconsistency from one form to another. Some colligation patterns were over-emphasized while others were neglected in the English language textbooks. This study indicates that a textbook corpus can be useful in analyzing the presentation of grammatical structures (articles, in the case of this research). The findings can provide guidance to teachers to improve their pedagogical practices in the teaching of articles and to cater to the weaknesses of the presentation of articles in the textbooks.
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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 | 0.001 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".