No Evidence of Perceptual Pseudoneglect in Alexithymia
Bibliographic record
Abstract
The research in neuroscience links alexithymia, the difficulty of identifying and describing feelings and emotions, with a left hemisphere preference and/or a right hemisphere deficit. To provide a neuropsychological support to this finding, we explored the relationship between alexithymia and the performance in a line bisection task, a standard method to evaluate spatial attention in relation with the functioning of the right hemisphere. 222 healthy participants completed a version of the TAS-20 scale, which measures alexithymia, and were asked to mark (bisect) the center of a 10 cm horizontal segment. The results document a significant rightward shift of the line center in borderline and manifest alexithymic participants, as compared to non-alexithymic individuals. Moreover, the higher the TAS-20 score the greater the rightward shift in the line bisection task. This result supports the right-hemisphere deficit hypothesis in alexithymia and suggests that visuospatial abnormalities may be an inner component of their profile.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".