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Record W2540141507 · doi:10.1123/jmld.2016-0001

Fundamental Movement Skills in Children With and Without Movement Difficulties

2016· article· en· W2540141507 on OpenAlexaff
Chantelle Zimmer, Kerri L. Staples, William J. Harvey

Bibliographic record

VenueJournal of Motor Learning and Development · 2016
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsMcGill UniversityUniversity of ReginaUniversity of Alberta
Fundersnot available
KeywordsMovement assessmentPsychologyMotor skillMovement (music)Gross motor skillMovement controlDevelopmental psychologyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

The performance of various fundamental movement skills is important for children with movement difficulties (MD) to be successful in physical education and play. The current study aimed to provide a detailed understanding of the aspects impaired in the performance of static and dynamic locomotor and object control skills among children with MD, identified with the Movement Assessment Battery for Children , relative to their same-aged peers without MD. Children, 7–10 years, were recruited from three elementary schools. Eighteen children with MD (mean age = 9.14 years, SD = 0.97) and 18 without MD (mean age = 9.12 years, SD = 0.97) participated in the study. Quantitative and qualitative aspects of their movement performance were assessed using the Test of Gross Motor Development ( TGMD-2 ) and PE Metrics . Children with MD demonstrated significantly poorer performance than children without MD for locomotor skills on the PE Metrics and object control skills on both the TGMD-2 and PE Metrics . The findings of this study suggest that children with MD primarily demonstrate immature movement patterns, inefficient movement strategies, and impaired aspects of movement that impact their performance for dynamic object control skills.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.240
Teacher spread0.234 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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