The metrics of regressive saccades during reading in 13 written languages
Bibliographic record
Abstract
A well-documented phenomenon in research on eye movement control during reading is the systematic relationship between the landing positions of forward saccades and target word characteristics. However, the behaviour of regressive saccades, which move the eyes in the opposite direction, remains less explored. This study delves into the landing positions of regressive saccades, emphasizing the distinction between intra-word and inter-word regressions, across diverse languages. Using data from the MECO L1 project, which includes eye-tracking data from 589 participants across 13 languages, we scrutinize the precise landing positions of regressions vis-à-vis forward saccades. Our analysis shows a robust effect of launch distance on landing positions for progressive saccades, with undershoots increasing as launch distance grows and overshoots with shorter launch distances. In contrast, regressive inter-word saccades show only minimal variation in landing positions, typically landing near the centre of the target word regardless of launch distance or word length. Intra-word regressions, however, display a pattern similar to progressive saccades, where the landing position is influenced by launch distance, tending to overshoot the optimal viewing position as the launch site moves away from the word's end. This pattern is consistent across all languages. These findings support the notion of cross-linguistic universality in oculomotor control mechanisms during reading, particularly the precision of regressive saccades. They align with the spatial coding hypothesis, suggesting that precise spatial memory of word positions guides regressive saccades.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".