Long-lag morphological priming and inflectional paradigm size effectsin Estonian and Finnish text reading
Bibliographic record
Abstract
Abstract Morphological priming and paradigm size effects have been established in single word reading studies, however, morphological priming effects in longer texts have not been observed, and, to the best of our knowledge, paradigmatic effects in text reading have not yet been examined. The current study utilized the Multilingual Eye-Tracking Corpus MECO ( Siegelman et al., 2022 ) to explore paradigmatic and morphological priming effects during text reading in Estonian and Finnish, two morphologically rich Finno-Ugric languages. The results showed clear inflectional paradigm size effects for Estonian during text reading in several eye movement measures, but not for Finnish. This may be linked to the support from the inflectional paradigm being semantically more beneficial to the reader in Estonian than in Finnish. The current study also showed clear long-lag inflectional priming effects in text reading, unlike what was observed in prior studies in Dutch, English, and Spanish. This study is thus the first to show that inflectional priming can extend beyond word or sentence level and suggest that inflectional variants of a particular word in Estonian and Finnish get and remain activated even when text context is present.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".