Grammar Structures and Deaf and Hard of Hearing Students: A Review of Past Performance and a Report of New Findings
Bibliographic record
Abstract
Results of a study are presented that suggest the grammatical structures of English some deaf and hard of hearing students struggle to acquire. A review of the literature from the past 40 years is presented, exploring particular lexical and morphosyntactic areas in which deaf and hard of hearing children have traditionally exhibited difficulty. Twenty-six participants from an urban day school for the deaf used the LanguageLinks software, produced by Laureate Learning Systems, for 10 minutes daily for 9 weeks. The descriptive analysis of the results expands on findings reported by Cannon, Easterbrooks, Gagne, and Beal-Alvarez (2011). The results indicated that many participants struggled with regular noun singular/plural; accusative first- and second-person singular; noun/verb agreement copular "be"; accusative third-person number/ gender; locative pronominals; auxiliary "be"/regular past "-ed;" and prenominal determiners plural.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".