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Record W2059709495 · doi:10.1348/026151006x119756

The role of shared practice in joint attention

2007· article· en· W2059709495 on OpenAlexafffund
Timothy P. Racine, Jeremy I. M. Carpendale

Bibliographic record

VenueBritish Journal of Developmental Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsSimon Fraser UniversityUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of CanadaMichael Smith Health Research BC
KeywordsJoint attentionPsychologyCompetence (human resources)Relevance (law)Theory of mindEpistemologySocial cognitionCognitive psychologySocial psychologyCognitive scienceCognitionDevelopmental psychology

Abstract

fetched live from OpenAlex

The infant's participation in sequences of joint activity that require visual attention is usually seen as an outcome of and evidence for the existence of particular infant psychological competencies. In a review of the relevant literature, we suggest that what is presupposed in most theories of joint attention is the role that shared social practices play in understanding the mind. It is, in fact, with recourse to such practices that researchers theorize about the infant's understanding of mind in the first instance. We argue: (1) the mind is not an entity that is separable from human activity; (2) knowledge of shared practices is what the developing agent requires to come to an understanding of their own mind and that of others; and (3) rather than searching for the best indicator of a true competence lying behind and necessary for joint attention, we should consider the various forms of interaction involving shared attention as constitutive of varying degrees of understanding. We consider the relevance of these arguments for contemporary social developmental theory.

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)0.006
metaresearch head score (Gemma)0.026
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 score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.014
Scholarly communication0.0040.006
Open science0.0020.008
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.315
Teacher spread0.300 · 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

Citations114
Published2007
Admission routes2
Has abstractyes

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