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Record W2397761866 · doi:10.1177/1525740115627420

Language Screening for Infants and Toddlers

2016· article· en· W2397761866 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCommunication Disorders Quarterly · 2016
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsnot available
FundersMcMaster UniversityUniversity of Minnesota
KeywordsIntervention (counseling)Developmental psychologyPsychologyLanguage delayAffect (linguistics)Language developmentPsychiatry

Abstract

fetched live from OpenAlex

Children from low-income environments are at increased risk of developing language delays which can negatively affect later academic and social outcomes. As children age, deficits between children with language delays and their typically developing peers continue to widen. In order to prevent future disabilities, efficient early language screening tools are needed to identify infants and toddlers who are at risk of language delay as the first step towards providing early intervention. The purpose of this review was to identify commercially available language screening tools for use with children under three years of age. The psychometric properties of each tool are described—including a specific focus on technical adequacy of the measures for use with diverse families. There are currently four tools available for use with infants and toddlers. The strengths and limitations of each tool are described, as well as the feasibility of using these tools in diverse populations.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.508

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 head0.018
GPT teacher head0.311
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