Moral judgement by the disconnected left and right cerebral hemispheres: a split-brain investigation
Bibliographic record
Abstract
Owing to the hemispheric isolation resulting from a severed corpus callosum, research on split-brain patients can help elucidate the brain regions necessary and sufficient for moral judgement. Notably, typically developing adults heavily weight the intentions underlying others' moral actions, placing greater importance on valenced intentions versus outcomes when assigning praise and blame. Prioritization of intent in moral judgements may depend on neural activity in the right hemisphere's temporoparietal junction, an area implicated in reasoning about mental states. To date, split-brain research has found that the right hemisphere is necessary for intent-based moral judgement. When testing the left hemisphere using linguistically based moral vignettes, split-brain patients evaluate actions based on outcomes, not intentions. Because the right hemisphere has limited language ability relative to the left, and morality paradigms to date have involved significant linguistic demands, it is currently unknown whether the right hemisphere alone generates intent-based judgements. Here we use nonlinguistic morality plays with split-brain patient J.W. to examine the moral judgements of the disconnected right hemisphere, demonstrating a clear focus on intent. This finding indicates that the right hemisphere is not only necessary but also sufficient for intent-based moral judgement, advancing research into the neural systems supporting the moral sense.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".