Native Reading Direction and Corresponding Preferences for Left- or Right-Lit Images
Bibliographic record
Abstract
The first language an individual learns has been shown to influence performance on cognitive tasks. Individuals who first learn to read and write in a left-to-right direction (native left-to-right readers) tend to bisect lines left of centre and draw counterclockwise circles, whereas those who learn to read and write from right-to-left (native right-to-left readers) will bisect lines closer to the objective centre and draw circles in a clockwise direction. The aim of the current study was to assess group differences in image preferences and eye movements when participants are simultaneously presented with an original and mirror image with an obvious illumination difference. Twenty native left-to-right readers (4 men, 16 women) and 25 native right-to-left readers (13 men, 12 women) participated. Left-to-right readers made more fixations on the left side of images and exhibited a significantly different left-lit image bias than right-to-left readers' choices. These results draw attention to the influence that reading direction has on scanning distributions and lighting preferences, and question previous results finding no difference between groups.
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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 | 0.001 | 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) | 0.003 | 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".