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Record W4241813068 · doi:10.1300/j006v23n03_05

Children's Handwriting Evaluation Tools and Their Psychometric Properties

2003· article· en· W4241813068 on OpenAlexaff
Katya Feder, Annette Majnemer

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsHandwritingStrengths and weaknessesTest (biology)PsychologyReliability (semiconductor)Scale (ratio)Inter-rater reliabilityRating scaleComputer scienceArtificial intelligenceDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Handwriting is an important area of evaluation for pediatric therapists. In selecting a handwriting instrument, therapists must not only consider a child's area of handwriting difficulty, but also the psychometric properties of the instrument chosen. This paper reviews five commonly used children's handwriting evaluation tools: (a) Diagnosis and Remediation of Handwriting Problems; (b) Minnesota Handwriting Test; (c) Children's Handwriting Evaluation Scale-Manuscript; (d) Evaluation Tool of Children's Handwriting-Manuscript; and (e) Test of Legible Handwriting. Each assessment is described including how it is administered, the scoring system, the reliability and validity of each instrument, and purchase information. The strengths and weaknesses of each tool are discussed along with factors affecting handwriting evaluation.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.217
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.113
GPT teacher head0.376
Teacher spread0.263 · 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

Citations11
Published2003
Admission routes1
Has abstractyes

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