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Record W3212830653

The Effects of Word Length on Handwriting Perception

2021· article· en· W3212830653 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

VenueStudent Research Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsMacEwan University
Fundersnot available
KeywordsHandwritingTypefacePerceptionPsychologyReading (process)Word processingSet (abstract data type)Cognitive psychologyComputer scienceSpeech recognitionArtificial intelligenceLinguisticsNeuroscience
DOInot available

Abstract

fetched live from OpenAlex

Humans are social creatures, and a large part of our communication skills are developed through reading and writing. Unlike typeface, handwriting is unique to each individual writer and can characterize a person. Our brain engages differently when reading and writing handwriting versus typeface. Similar to faces, handwriting is a complex visual stimulus containing multiple dimensions. This study looks at the effects of word length in handwriting perception using traditional psychophysical techniques. Recently, we have developed a set of standardized handwriting stimuli that we can use to investigate whether or not the perceived gender of handwriting depends on the number of letters within a word. Stimuli will be composed of 1, 2, 4, 8, or 16 letters and participants will rate the perceived gender of the handwriting. There are two alternative outcomes we expect to find with this study. Handwriting perception may reflect global visual processing (efficient processing) or local visual processing (inefficient processing). Department: Psychology  Faculty Mentor: Dr. Nicole Anderson

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.084
GPT teacher head0.472
Teacher spread0.387 · 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