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Assessing Story Comprehension in Preschool Children

2008· article· en· W1964329452 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

VenueTopics in Language Disorders · 2008
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsDempsey (Canada)
Fundersnot available
KeywordsComprehensionPsychologyReading comprehensionDevelopmental psychologyLiteracyCognitive psychologyLinguisticsPedagogyReading (process)

Abstract

fetched live from OpenAlex

Many of the foundational abilities that are necessary for learning to read emerge in preschool children's oral language in advance of formal literacy instruction. This is not only true of phonemic awareness skills but also true of oral language comprehension, particularly of stories. Thus, clinical evaluation of preschoolers' story comprehension abilities is an important part of a preliteracy assessment. Ensuring that the outcomes of these evaluations accurately reflect children's abilities and lead to optimal clinical decisions requires familiarity with the available tools, their task demands, and psychometric properties. To provide clinicians with information necessary for making evidence-based choices in their assessment of story comprehension, we review the development of story comprehension in young children with and without language impairment. We then describe the procedures, both traditional and novel, that have been used to measure early story comprehension, assessing strengths and limitations.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.322
Teacher spread0.304 · 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