Measuring the Frequency Occurrence of Handwriting and Handprinting Characteristics<sup>,</sup>
Why this work is in the frame
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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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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it