Natural and Unnatural: An Application of Taoist Thought to Bioethics
Bibliographic record
Abstract
In a society where filial piety is regarded as a social norm, should a son consent to withdrawing treatments to his terminally ill father or should he request that his father’s life be maintained as long as possible? Leaving a father unattended is regarded as unfilial in a Confucian society, let alone untreated while being ill. Although Taoism also teaches filial piety, it asserts artificially as unnatural. In other words in Taoist view, uselessly prolonging a life through life-sustaining devices or futilely treating an incurable terminal patient is against the will of Heaven. This paper is not an argument in favor of euthanasia but a discussion of what is natural and un-natural in terms of life and death phenomenon from Taoist perspective. Artificial life relying on external means is not harmonious with nature. Thus keeping a person in PVS stage alive should be ethically flaw. In this sense, don’t all attempts to cure illness un-natural? This author will say that if treatments can restore health, then it is not un-natural. But if medical procedures fail to revert the deterorating health of a terminally ill patient and treatments prove to be futile, foregoing treatments can be regarded as flowing with Heaven and thus is ethically justifiable.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.072 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".