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Record W1972837226 · doi:10.1177/002221940203500304

The Incidence and Nature of Letter Orientation Errors in Reading Disability

2002· article· en· W1972837226 on OpenAlexaff
Megan Terepocki, Richard S. Kruk, Dale M. Willows

Bibliographic record

VenueJournal of Learning Disabilities · 2002
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of TorontoUniversity of Manitoba
Fundersnot available
KeywordsReading (process)Orientation (vector space)PsychologyCopyingReading disabilityDyslexiaCognitive psychologyDevelopmental psychologyLinguistics

Abstract

fetched live from OpenAlex

Letter orientation confusions (reversals) in the reading and writing of 10-year-old children with and without reading disability were investigated to determine whether reading disability is associated with letter orientation errors and to identify the nature of the errors. In a variety of tasks measuring letter orientation confusions in reception (reversal detection and recognition) and production (controlled writing, copying), individuals with reading disability made more orientation confusions than average readers. Orientation errors were more frequent for reversible than for nonreversible items in tasks involving long-term memory processes. The results did not appear to be related to group differences in attention or speed of motor responding. Possible sources of orientation confusions, including deficient magnocellular system processing, mislabeling, and overreliance on visual strategies, are discussed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.016
GPT teacher head0.308
Teacher spread0.292 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations84
Published2002
Admission routes1
Has abstractyes

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