MétaCan
Menu
Back to cohort
Record W1986177741 · doi:10.1177/1073191105277006

The Woodcock Reading Mastery Test

2005· article· en· W1986177741 on OpenAlexaff
Hye K. Pae, Justin C. Wise, Paul T. Cirino, Rose A. Sevcik, Maureen W. Lovett, Maryanne Wolf, Robin D. Morris

Bibliographic record

VenueAssessment · 2005
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsWoodcockPsychologyRaw scoreTest (biology)Reading (process)NormativeDevelopmental psychologyTest validityAchievement testEthnic groupConvergent validityIntelligence quotientPsychometricsStandardized testMathematics educationCognitionInternal consistency

Abstract

fetched live from OpenAlex

This study examined the magnitude of differences in standard scores, convergent validity, and concurrent validity when an individual's performance was gauged using the revised and the normative update (Woodcock, 1998) editions of the Woodcock Reading Mastery Test in which the actual test items remained identical but norms have been updated. From three metropolitan areas, 899 first to third grade students referred by their teachers for a reading intervention program participated. Results showed the inverse Flynn effect, indicating systematic inflation averaging 5 to 9 standard score points, regardless of gender, IQ, city site, or ethnicity, when calculated using the updated norms. Inflation was greater at lower raw score levels. Implications for using the updated norms for identifying children with reading disabilities and changing norms during an ongoing study 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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.031
GPT teacher head0.344
Teacher spread0.312 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations101
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAssessmentSame topicCognitive and developmental aspects of mathematical skillsFrench-language works237,207