Disintegrating Particles, Non-Local Causation and Category Mistakes: What do Conservation Laws have to do with Dualism?
Bibliographic record
Abstract
The single most influential and widely accepted objection against any form of dualism, the belief that human beings are both body and soul, is the objection that dualism violates conservation laws in physics. The conservation laws objection against dualism posits that body and soul interaction is at best mysterious, and at worst impossible. While this objection has been both influential from the time of its initial formulation until present, this paper occupies itself with arguing that this objection is a fleeting one, and has successful answers from both scientific and philosophical perspectives. It is to this end that I provide three groups of responses to the conservation laws objection. First, I outline responses which take the ‘laws of nature’ as the proper entry point into the discussion. Secondly, I provide an analysis of those who argue that contemporary quantum physical data requires that the objection itself involves scientifically unjustified premises. Finally, I layout a philosophically oriented answer which argues that the objection is linguistically problematic since its demands on the dualist are categorically fallacious. From these groups of answers, I conclude that while the conservation laws objection has been arguably the most widely accepted objection against dualism, the objection is without philosophical justification.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.033 |
| Scholarly communication | 0.006 | 0.021 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| 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".