Native Word Order Processing Is Not Uniform: An ERP Study of Verb-Second Word Order
Bibliographic record
Abstract
Studies of native syntactic processing often target phrase structure violations that do not occur in natural production. In contrast, this study examines how variation in basic word order is processed, looking specifically at structures traditionally labelled as violations but that do occur naturally. We examined Swedish verb-second (V2) and verb-third (V3) word order processing in adult native Swedish speakers, manipulating sentence-initial adverbials (temporal idag ‘today’, spatial hemma ‘at home’ and sentential kanske ‘maybe’) in acceptability judgements, in simultaneously recorded event-related potentials (ERP) to visually presented sentences and in a written sentence completion task. An initial corpus study showed that the adverbials differ in frequency in fronted position (idag > kanske > hemma), and although all occur mainly with V2 word order, kanske occurs more frequently with V3 in natural production than both idag and hemma. The experimental results reflected these patterns such that V2 sentences were overall more frequently produced and were deemed more acceptable than V3 sentences. The ERP results consisted of a biphasic N400/P600 response to V3 word order that indicated effects of word retrieval and sentence reanalysis. We also found consistent effects of adverbials. As predicted, V3 was produced more frequently and judged as more acceptable in Kanske sentences than in sentences with the other two adverbials. The ERP analyses showed stronger effects for idag and hemma with V3, especially regarding the P600. The results suggest that the naturally occurring word order ‘violation’, V3 with kanske, is processed differently than V3 with other adverbials where the V2 norm is stronger. Moreover, these patterns are related to individuals’ own production patterns. Overall, the results suggest a more varied native word order processing than previously reported.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".