MétaCan
Menu
Back to cohort
Record W2520815698 · doi:10.1111/mbe.12125

Reading‐Specific Flexibility Moderates the Relation Between Reading Strategy Use and Reading Comprehension During the Elementary Years

2016· article· en· W2520815698 on OpenAlexfundno aff
Emily K. Gnaedinger, Alycia M. Hund, Matthew Hesson-McInnis

Bibliographic record

VenueMind Brain and Education · 2016
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
FundersMcMaster University
KeywordsFluencyReading (process)VocabularyReading comprehensionFlexibility (engineering)PsychologyCognitive flexibilityCognitive psychologyCard sortingComprehensionTask (project management)CognitionRelation (database)Computer scienceLinguisticsMathematics educationMathematics

Abstract

fetched live from OpenAlex

ABSTRACT The goal was to test whether cognitive flexibility moderates the relation between reading strategy use and reading comprehension during the elementary years. Seventy‐five second‐ through fifth‐grade students completed a think aloud task and a metacognitive questionnaire to measure reading strategies, two card‐sorting tasks to measure general and reading‐specific cognitive flexibility, and one standardized measure of reading comprehension, as well as measures of oral reading fluency and vocabulary. As expected, oral reading fluency and vocabulary predicted reading comprehension, as did reading‐specific flexibility. Importantly, reading‐specific flexibility had a significant moderating effect, over and above the other effects. Specifically, weak reading‐specific flexibility skills were associated with a negative relation between reading strategy use during think aloud and reading comprehension, suggesting that children with weak flexibility skills are less adept at using reading strategies effectively.

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)0.005
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.049
GPT teacher head0.320
Teacher spread0.271 · 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

Citations32
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueMind Brain and EducationSame topicReading and Literacy DevelopmentFrench-language works237,207