Bilingual processing of case-marking and locative verbs in Korean: Use of L2-unique information
Bibliographic record
Abstract
Aims and objectives/purpose/research questions:Previous studies show conflicting findings regarding bilingual processing of target information not instantiated in learners’ first language. The current study addresses this issue by investigating whether Chinese speakers can integrate case-marking information, which is unique to Korean, with locative verb information in their processing of the Korean locative constructions.Design/methodology/approach:We conducted an acceptability judgment task to assess Chinese–Korean bilinguals’ explicit knowledge of case-marking constraints on Korean locative constructions, and a self-paced reading task to probe their application of the knowledge to real-time sentence processing.Data and analysis:Twenty-four advanced Chinese–Korean bilinguals’ acceptability judgments and reading times were compared with those of 24 Korean monolingual speakers, using mixed-effects regression modeling.Findings/conclusions:Results from the offline acceptability judgment task revealed the bilinguals’ native-like judgment patterns. Both Korean monolingual and Chinese–Korean bilinguals rejected sentences with wrong case-marking sequences paired with locative verbs. In the self-paced reading task, both monolingual and bilingual speakers showed increased reading times when a mismatch arose between case-marking and locative verb information, indicating their sensitivity to locative agreement violations.Originality:While previous studies have investigated bilinguals’ integration of multiple sources of information, this study adds a new perspective to this issue by testing whether bilinguals can use L2-unique information (i.e., case marking) to integrate it with other types of information (i.e., locative verbs) for sentence processing.Significance/implications:Our findings are consistent with the competition model which predicts that L2-unique information presents little processing difficulty for bilinguals. At the same time, the current results lend credence to the idea that increased proficiency allows bilinguals to integrate multiple information sources during processing.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".