Do Minds Switch Bodies? Dualist interpretations across ages and societies_postprint
Bibliographic record
Abstract
Researchers explain cultural phenomena ranging from cognitive biases to widespread religious beliefs by assuming intuitive dualism: humans imagine minds and bodies as distinct and separable. We examine dualist intuition development across two societies that differ in normative focus on thinking about minds. We use a new method that measures people’s tendency to interpret ambiguous stimuli using mind-body dualist thinking. We recruit 180 Canadian children (2-10 yrs.) along with 42 Indigenous iTuakei Fijian children (5-13 yrs.) and 38 Indigenous iTaukei Fijian adults (27-79 yrs.) from a remote island community. Participants tracked a named character within ambiguous animations that could be interpreted as a mind-body switch. Animations vary ‘agency cues’ participants might rely on for dualistic interpretations. Results indicate early emerging dualistic inclinations across populations and reliance on ‘agency cues’ of body proximity and appearance of eyes. ‘Agency cues’ increase dualist interpretations from 10% to 70%, though eyes mattered more for Westernized participants. Overall, statistical models positing dualist interpretations ‘emerge early and everywhere’ fit our data better than models positing dualism ‘develops gradually with exposure to Western cultural traditions.’ Fijian participants, who normatively avoid focus on minds, offered even more dualistic interpretations when they had less Western cultural exposure (via formal education).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".