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Record W4362735211 · doi:10.1080/1091367x.2023.2199126

Trust the “Process”? When Fundamental Motor Skill Scores are Reliably Unreliable

2023· article· en· W4362735211 on OpenAlexaff
Ryan M. Hulteen, Larissa True, Edward Kroc

Bibliographic record

VenueMeasurement in Physical Education and Exercise Science · 2023
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyGross motor skillMotor skillReliability (semiconductor)Inter-rater reliabilityInternal consistencyPhysical medicine and rehabilitationApplied psychologyPhysical therapyClinical psychologyPsychometricsRating scaleDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

The typical process for assessing inter-rater reliability is facilitated by training raters within a research team. Lacking is an understanding if inter-rater reliability scores between research teams demonstrate adequate reliability. This study examined inter-rater reliability between 16 researchers who assessed fundamental motor skills using the Test of Gross Motor Development-3rd edition. Total score agreement (ICC = 0.363) and locomotor subscale agreement (ICC = 0.383) were “very poor,” while ball skills subscale agreement (ICC = 0.478) was “poor.” Consistencies of total (ICC = 0.757), locomotor (ICC = 0.730), and ball skills (ICC = 0.746) scores were “fair.” Component percentage agreement ranged from 40.5% to 96.2%. These data suggest that there are significant differences in how different research groups evaluate fundamental motor skills based on the subjective nature of scoring. Consistency and agreement among users need to be addressed in motor development research to allow for direct comparisons across studies that use process-oriented measures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.793
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.310
Teacher spread0.282 · 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 teacher head, 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

Citations17
Published2023
Admission routes1
Has abstractyes

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