Extending the maze task to Hungarian: New insights in relative clause processing.
Bibliographic record
Abstract
Relative clauses are one of the most studied constructions in sentence processing research. But even as the number of investigations has grown, there still remain open questions regarding the precise sources of observed processing effects. This article contributes to this domain by adapting the maze task paradigm to Hungarian, a free word order language where memory-based and expectation-based accounts of syntactic processing make distinct predictions for the processing of relative clauses. At the point of the relative pronoun, we observe an effect that is most consistent with expectation-based accounts. At the relative clause verb, we find mixed evidence: In L-maze, we see a memory-based locality effect, while in A-maze, an expectation-driven antilocality effect emerges. These findings add to an existing body of research showing that memory- and expectation-based effects can both occur within the same linguistic structure. We additionally conclude that while the maze task is a valuable tool for increasing language diversity in sentence processing studies, the partially divergent findings between its variants warrant further research. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.001 |
| 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".