Modality in ESL Textbooks: Insights from a Contrastive Corpus-Based Analysis
Bibliographic record
Abstract
This study investigates modality in textbooks designed for learners of English by exploring the frequency and distribution of modal verbs in two corpora – one of authentic native-speaker language and a pedagogical one used by francophone learners of English in Quebec – with a view to identifying areas where added support for learning may be beneficial. The analysis is divided into two parts: the first investigates distributional frequencies of nine central modals across the two corpora; the second explores and compares the semantics of four selected modal auxiliaries (must, can, may, and should) in the two corpora. If it is assumed that textbooks should be an accurate reflection of authentic native speakers’ language use, then support for the acquisition of modality in the textbooks proved to be less than ideal. Although there is a reasonably good coverage of modals in the textbooks in terms of frequency, the semantic analysis reveals discrepancies between the native corpus and the textbooks. Learners are exposed to a limited range of meanings that do not fully reflect authentic use. Findings are also discussed from an alternate perspective whereby strong representations of potentially difficult to acquire uses of modals in the textbooks can be seen as beneficial for acquisition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 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 teacher head, 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".