Hand Preference Side and Its Relation to Hand Preference Switch History Among Old and Oldest-Old Adults
Bibliographic record
Abstract
The last 10 years of research on adult hand preference patterns have generated a controversy over the meaning of the difference in the incidence rates of left- and right-hand preference in older adult samples (> 60 years old) when compared to samples of younger individuals (< 30 years old). Age differences in hand preference prevalence often are studied with large, cross-sectional age samples; however, with 1 notable exception (Gilbert & Wysocki, 1992), these large samples frequently are dominated numerically by individuals below the age of 45 years. This study reports on hand preference data from a sample of 1,277 individuals between the ages of 65 and 100 years. Overall, the participants in this sample displayed an incidence of 93.1% right preference versus 6.9% left preference. However, the occurrence of age differences in right-hand use when the oldest-old adults (> 73 years old) were compared to the others in this sample were only apparent for writing hand preference. Variation in hand preference prevalence was related to whether an individual reported a history of attempts to switch preference toward the right side. These findings support the view that age-related variations in hand preference prevalence are best explained by a number of factors, the interaction of which is still not well understood (Hugdahl, Satz, Mitrushina, & Miller, 1993; Hugdahl, Zaucha, Satz, Mitrushina, & Miller, 1996).
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".