Sensitivity to Inflectional Morphology in a Non-native Language: Evidence From ERPs
Bibliographic record
Abstract
The extent to which non-native speakers are sensitive to morphological structure during language processing remains a matter of debate. The present study used a masked-priming lexical decision task with simultaneous electroencephalographic (EEG) recording to investigate whether native and non-native speakers of French yield behavioral and brain-level responses to inflected verbs. The results from reaction time and EEG analyses indicate that both native and non-native French speakers were indeed sensitive to morphological structure, and this sensitivity cannot be explained simply by the presence of orthographic or semantic overlap between prime and target. Moreover, sensitivity to morphological structure in non-native speakers was not influenced by proficiency (as reflected by the N400); lower-level learners show similar sensitivity at the word level as very advanced learners. These results demonstrate that native-like processing of inflectional morphology is possible in adult learners, even at lower levels of proficiency, which runs counter to proposals suggesting that native-like processing of inflection is beyond the capacity of non-native speakers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".