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Record W2021656857 · doi:10.1068/p7698

Visual Word Expertise: A Study of Inversion and the Word-Length Effect, with Perceptual Transforms

2014· article· en· W2021656857 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

VenuePerception · 2014
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWord lengthInversion (geology)Computer scienceWord (group theory)PerceptionReading (process)Speech recognitionOrientation (vector space)Artificial intelligenceNatural language processingPsychologyLinguisticsMathematicsGeometryNeurosciencePhilosophy

Abstract

fetched live from OpenAlex

The word-length effect may indicate whether reading is proceeding in an efficient whole-word fashion or by serial letter processing. If it is an index of an orientation-dependent expert reading mechanism, then it should show an inversion effect, with a large difference between upright and upside-down text that is specific for normally configured text. We measured response time of healthy subjects reading 3- to 9-letter words presented in normal configuration, in mirror reflection or spelt backward, in either upright or inverted orientation. The word-length effect showed an inversion effect specific for normal text, as it was not seen for either backward or mirrored text, a result that differed from that for simple mean response times. Also, the word-length effect was smaller for backward than for mirrored text, suggesting that reading of transformed text uses primarily local letters rather than global word forms. We conclude that the word-length effect is a suitable index of expert reading, and reveals that reading under perceptually difficult conditions relies on a sublexical letter-based strategy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.009
GPT teacher head0.286
Teacher spread0.276 · 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