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Record W1982116297 · doi:10.1207/s15327078in0801_6

Infants' Ability to Distinguish Between Intentional and Accidental Actions and Its Relation to Internal State Language

2005· article· en· W1982116297 on OpenAlexaff
Kara M. Olineck, Diane Poulin‐Dubois

Bibliographic record

VenueInfancy · 2005
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsConcordia University
Fundersnot available
KeywordsPsychologyAccidentalImitationVocabularyRelation (database)Task (project management)Action (physics)Developmental psychologyCognitive psychologyProduction (economics)Social psychologyLinguisticsComputer science

Abstract

fetched live from OpenAlex

The experiment reported here investigated infants' concept of intention, as well as the relation among intention understanding, general productive vocabulary, and internal state language production during the 2nd year. Results from an imitation task indicated that 18-month-olds are better able to differentiate between intentional and accidental actions than 14-month-olds. Although there was no relation between infants' performance on the intention task and their general productive vocabulary, internal state language production at 30 months was predicted by infants' ability to differentiate between intentional and accidental actions about a year earlier. These findings shed light on the developmental progression of infants' concept of intention, as well as on the continuity between infants' understanding of intentional action and their ability to use internal state words.

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)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.338
Teacher spread0.320 · 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

Citations86
Published2005
Admission routes1
Has abstractyes

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