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Record W2034836290 · doi:10.1177/0022219411413544

RAN and Double-Deficit Theory

2011· article· en· W2034836290 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

VenueJournal of Learning Disabilities · 2011
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsPsychologyPseudowordReading (process)Developmental psychologyPhonological awarenessRapid automatized namingReading comprehensionPhonologyLongitudinal studyLanguage disorderCognitionLinguisticsLiteracy

Abstract

fetched live from OpenAlex

Lervag and Hulme's neuro-developmental theory and Wolf and Bowers's double-deficit hypothesis were examined in this longitudinal study. A total of 130 children were tested in preschool and followed through fifth grade, when 84 remained in the study. During preschool and kindergarten the participants were given tests of end-sound discrimination (phonological awareness; PA) and the rapid naming of objects (rapid automatic naming; RAN) and were placed into the four groupings of the double-deficit hypothesis. The growth curves for the four groups with the subtests of word reading, pseudoword reading, and comprehension supported the double-deficit hypothesis. The RAN objects scores of preschool and kindergarten predicted reading at every age level and offered support for Lervag and Hulme's neuro-developmental theory. It was concluded that both RAN and PA predicted reading in the English language throughout the elementary school years and that the early assessments of these variables were more diagnostic than measures at later ages.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.999

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)0.0020.000

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 head0.043
GPT teacher head0.300
Teacher spread0.258 · 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