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Record W2030584292 · doi:10.1080/01650250143000166

Motor activity level and behavioural control in young children

2002· article· en· W2030584292 on OpenAlexaff
Darren W. Campbell, Warren O. Eaton, Nancy A. McKeen

Bibliographic record

VenueInternational Journal of Behavioral Development · 2002
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPsychologyDevelopmental psychologyTask (project management)Motor activityMotor controlMotor skillCognitionMovement controlYoung adultInhibitory controlPhysical activityPhysical medicine and rehabilitationNeuroscienceMedicine

Abstract

fetched live from OpenAlex

How do young children’s typical levels of physical movement relate to their ability to inhibit task-inappropriate behavioural responses? This question was investigated with a cross-sectional sample of 85 children, 4- to 6-years of age. Children’s typical levels of activity were assessed with actometers, mechanical measures of movement frequency. Multiple measures of contra-habitual task performance, reflecting children’s ability to inhibit the typical response associated with a task and to execute a less typical response, were aggregated. Procedurally similar control tasks, not dependent on the inhibition of behavioural responses, were also assessed. Contra-habitual task performance was positively and uniquely related to activity level, and an age by movement interaction showed that this relation was most reliable among the younger children in our sample. Young children’s motor activity is associated with enhanced, not diminished behavioural control.

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)0.004
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.085
GPT teacher head0.339
Teacher spread0.253 · 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

Citations47
Published2002
Admission routes1
Has abstractyes

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Same venueInternational Journal of Behavioral DevelopmentSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207