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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 OpenAlexaff
Heidi Schwellnus, Debra Cameron, Heather Carnahan

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.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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

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 designSystematic review
Domainnot available
GenreReview

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

Citations23
Published2012
Admission routes1
Has abstractyes

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