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Language and Theory of Mind: Meta-Analysis of the Relation Between Language Ability and False-belief Understanding

2007· review· en· W2171847059 on OpenAlexaff
Karen Milligan, Janet Wilde Astington, Lisa Ain Dack

Bibliographic record

VenueChild Development · 2007
Typereview
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyFalse beliefVariation (astronomy)VocabularyRelation (database)Cognitive psychologyTheory of mindMeta-analysisTask (project management)Developmental psychologyLinguisticsCognition

Abstract

fetched live from OpenAlex

Numerous studies show that children's language ability is related to false-belief understanding. However, there is considerable variation in the size of the correlation reported. Using data from 104 studies (N=8,891), this meta-analysis determines the strength of the relation in children under age 7 and examines moderators that may account for the variability across studies--including aspect of language ability assessed, type of false-belief task used, and direction of effect. The results indicate a moderate to large effect size overall that remains significant when age is controlled. Receptive vocabulary measures had weaker relations than measures of general language. Stronger effects were found from earlier language to later false belief than the reverse. Significant differences were not found among types of false-belief task.

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)0.015
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.039
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.015
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.166
GPT teacher head0.379
Teacher spread0.212 · 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.

Study designMeta-analysis
DomainMethods
GenreReview

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

Citations1,233
Published2007
Admission routes1
Has abstractyes

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