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Native Reading Direction and Corresponding Preferences for Left- or Right-Lit Images

2013· article· en· W2038524380 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerceptual and Motor Skills · 2013
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLeft and rightRight-to-leftReading (process)ClockwisePsychologySignificant differenceCognitive psychologyLinguisticsComputer scienceMedicineArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.268
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it