Subjacency Violations in Second Language Acquisition: Some Evidence from Chinese Mandarin Speakers of L2 English
Bibliographic record
Abstract
The literature review shows that many previous studies have used Subjacency to test the availability of UniversalGrammar (UG) in second language acquisition. Schachter (1989) claimed that L2 learners do not have access to UGprinciples, while Hawkins and Chan (1997) suggested that L2 learners had partial availability of UG, for they foundthere was a strong difference between the elementary L2 learners and the advanced L2 learners in judging theungrammaticality of Subjacency violations; that is, the elementary L2 learners owned the highest accuracy. Underthe hypothesis of partially availability of UG in second language acquisition, L2 learners are only able to acquire theproperties instantiated in their L1s. Although they may accept violations of universal constraints, it is only at facevalue; rather the L2 learners develop different syntactic representations from the native speakers. This study has beenundertaken as a follow-up study of Hawkins and Chan (1997), and tested on L1 Mandarin speakers of L2 English injudging the grammaticality of their Subjacency violations. The results of the Grammaticality Judgement Test showthat the accuracy of Chinese speakers in judgement increased with English proficiency and that they rejectedresumptives inside islands as a repair. Contrary to the previous findings, this study provides evidence that UG isavailable in adult second language 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.070 | 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".