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Record W2033376211 · doi:10.1080/19411243.2012.744651

Which to Choose: Manuscript or Cursive Handwriting? A Review of the Literature

2012· review· en· W2033376211 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Occupational Therapy Schools & Early Intervention · 2012
Typereview
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsWomen's College HospitalUniversity of TorontoHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsCursiveHandwritingLinguisticsPsychologyComputer scienceNatural language processingArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Handwriting is a necessary skill for children to learn during school. Most children in North America learn two formats, manuscript and then cursive. Approximately one-fourth of school children have difficulty producing writing. With success and self-esteem of children negatively impacted by writing challenges, is it necessary for all children to learn both formats? This paper reviewed relevant literature on writing to summarize the history and to discover whether evidence exists to support teaching both forms. The components of complexity of the manuscript and cursive writing are highlighted, the implications are discussed, and future research is suggested.

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.

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)0.005
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.463
Teacher spread0.311 · 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