Measuring the Frequency Occurrence of Handwriting and Handprinting Characteristics<sup>,</sup>
Bibliographic record
Abstract
The premise of this study was to take a valid population sampling of handwriting and handprinting and assess how many times each of the predetermined characteristic is found in the samples. Approximately 1500 handwriting specimens were collected from across the United States and pared to obtain a representative sample of the U.S. adult population according to selected demographics based on age, sex, ethnicity, handedness, education level, and location of lower-grade school education. This study has been able to support a quantitative assessment of extrinsic and intrinsic effects in handwriting and handprinting for the six subgroups. Additional results include analyses of the interdependence of characteristics. This study found that 98.55% of handprinted characteristics and 97.39% of cursive characteristics had an independence correlation of under 0.2. The conclusions support use of the product rule in general, but with noted caveats. Finally, this study provides frequency occurrence proportions for 776 handwriting and handprinting characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".