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Record W1982289368 · doi:10.1159/000277170

The Importance of Motor Activity in Sensorimotor Development: A Perspective from Children with Physical Handicaps

2010· article· en· W1982289368 on OpenAlexaff
James M. Bebko, Lillian Burke, Jean Craven, Natalie Sarlo

Bibliographic record

VenueHuman Development · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsYork University
Fundersnot available
KeywordsPerspective (graphical)PsychologyMotor skillDevelopmental psychologyMotor activityPhysical developmentCognitive psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

The assumption that motor activity and physical manipulation play a central role in early development is evaluated in light of a number of studies reporting that at least some severely physically handicapped children seem to attain age-appropriate or slightly delayed levels of cognitive development. In addition, we examine the importance of motor activity in strong and weak formulations of Piagetian theory, as well as in neo-Piagetian and perceptual analytic [Mandler, 1988] theories. General methodological difficulties affecting interpretation of many studies with the physically handicapped are highlighted. The sufficiency of alternative pathways to development, using available modalities for sensory input and action, is discussed, as well as the possibility of using other people and objects instrumentally to act on the environment in the testing of hypotheses. We conclude that motor activity may be the modal means by which cognitive development normally proceeds, but that it is not a necessary contributor. This view is seen as most consistent with the perceptual analytic and neo-Piagetian models, although neither is specific enough on the issue.

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)0.002
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.007
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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

Citations21
Published2010
Admission routes1
Has abstractyes

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