Reliability of the Crossed-Hands Deficit in Tactile Temporal Order Judgements
Bibliographic record
Abstract
Crossing the hands over the midline impairs performance on a tactile temporal order judgement (TOJ) task, resulting in the crossed-hands deficit. This deficit results from a conflict between two reference frames - one internal (somatotopic) and the other external (spatial) - for coding stimulus location. The substantial individual differences observed in the crossed-hands deficit highlight the differential reliance on these reference frames. For example, women have been reported to place a greater emphasis on the external reference frame than men, resulting in a larger crossed-hands deficit for women. It has also been speculated that individuals with an eating disorder place a greater weight on the external reference frame. Further exploration of individual differences in reference frame weighing using a tactile TOJ task requires that the reliability of the task be established. In Experiment 1, we investigated the reliability of the tactile TOJ task across two sessions separated by one week and found high reliability in the magnitude of the crossed-hands deficit. In Experiment 2, we report the split-half reliability across multiple experiments (both published and unpublished). Overall, tactile TOJ reliability was high. Experiments with small to moderate crossed-hands deficits showed good reliability; those with larger deficits showed even higher reliability. Researchers should try to maximize the size of the effect when interested in individual differences in the use of the internal and external reference frames.
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 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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".