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The emergence of a novel representation from action: evidence from preschoolers

2009· article· en· W2032607461 on OpenAlexaff
Rebecca Boncoddo, James A. Dixon, Elizabeth Kelley

Bibliographic record

VenueDevelopmental Science · 2009
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsQueen's University
FundersNational Science Foundation
KeywordsEmbodied cognitionRepresentation (politics)Alternation (linguistics)PsychologyCognitionSet (abstract data type)Action (physics)Cognitive psychologyMental representationDevelopmental psychologyCognitive scienceComputer scienceArtificial intelligenceLinguistics

Abstract

fetched live from OpenAlex

Recent work in embodied cognition has proposed that representations and actions are inextricably linked. The current study examines a developmental account of this relationship. Specifically, we propose that children's actions are foundational for novel representations. Thirty-two preschoolers, aged 3.4 to 5.7 years, were asked to solve a set of simple gear-system problems. Participants' motions and verbalizations were coded to establish the strategies they used. The preschoolers initially solved the problems by simulating the turning and pushing of the gears. Subsequently, most participants discovered a new representation of the problems: the turning direction of the gears alternates. Results show that the number of actions that embodied alternation information, during their simulation of the system, predicted the later emergence of the higher-order representation (i.e. that the gears alternate turning direction). Thus, it appears that the preschoolers discovered a new representation based on their own actions. These results are consistent with the developmental embodiment hypothesis: actions are central to the emergence of new representations.

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)0.002
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.100
GPT teacher head0.378
Teacher spread0.278 · 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

Citations63
Published2009
Admission routes1
Has abstractyes

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