Native and non-native parsing of adjective placement – An ERP study of Mandarin and English sentence processing
Bibliographic record
Abstract
• Processing of adjective order similar for native processing in both Mandarin and English. • Mandarin adjective order is challenging even for advanced learners. • Adjective-noun pairs in Mandarin may sometimes be single words. • Individuals vary in how they detect incorrect adjective order, but with limitations. Adjectives in English and Mandarin are typically prenominal, but the corresponding grammatical rules vary in subtle ways. Our event-related potential (ERP) study shows that native speakers of both languages rely on similar processing mechanisms when reading sentences with anomalous noun-adjective order (e.g., the vase * white ) in their first language, reflected by a biphasic N400-P600 profile. Only Mandarin native speakers showed an additional N400 on grammatical adjectives (e.g., the white vase), potentially due to atypical word-by-word presentation of lexicalized compounds. English native speakers with advanced Mandarin proficiency were tested in both languages. They processed ungrammatical noun-adjective pairs in English like English monolinguals (N400-P600), but only exhibited an N400 in Mandarin. The absent P600 effect corresponded to their (surprisingly) low proficiency with noun-adjective violations in Mandarin, questioning simple rule transfer from English grammar.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".