Phonological and semantic processing of words: Laterality changes according to gender in right- and left-handers
Bibliographic record
Abstract
The ability of cerebral hemispheres to process language is influenced by multiple factors. The well-known right visual field advantage in word recognition in divided visual field tasks is affected by both intra- and inter-individual variables. For example, hemispheric linguistic abilities may vary within a given individual according to the language component being processed, whereas variations between individuals may be modulated by the individual's handedness and gender. The objective of this divided visual field study was to compare gender differences in right- and left-handers in relation to their hemispheric abilities in performing phonological and semantic tasks. The results indicate that for both types of processing, gender had a different impact on right- and left-handed groups. Unexpectedly, a gender difference in laterality pattern was found in left-handers but not in right-handers for both phonological and semantic abilities. Intriguingly, left-handed men displayed a more symmetrical laterality pattern in phonological and semantic abilities than left-handed women.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".