A Comparison of Chinese and Western Interpretations of Cause, Will, and Free Will
Bibliographic record
Abstract
A cross-cultural comparison of how constructs overlapping with cause, will (human cause), and free will (human cause of a controversial kind) have evolved from concrete origins reflected by Chinese pictographs and the Indo-European etymologies of Greek written words. Cause-related constructs compared are Zhang Dainian’s 元 (yuán), 因 (yīn), 故 (gù), and 所以 (suóyǐ) and the Greek terms aitia (αιτια; “cause”), archē (αρχε; “origin”) and genesis (γενεσις, “genesis”). 因 (yīn) is said, for example, to show a man enclosed (by determinants, possibly prison walls), while aitia (“cause”) is said to be related to aisa (“fate”) and ultimately to the Indo-European root *aito- (“share,” “allotment,” what fate has—concretely, it is contended here—allotted to a person). Reflections on cause lead to interpretations of the more specific cause called will, encountered as 志 (zhì) and 意志 (yìzhì) in Mandarin. Whether the ancient Greeks relied on a construct like will has been debated, but volition in some sense underlies the hekusion (εκούσιον), the voluntary. Volition immediately raises the much debated issue of whether the will is “free.” i.e., whether there is a subset of willed acts without antecedents, spontaneous, emerging ex nihilo. Examination of the etymologies of the characters used to translate the term free will into Chinese—自由的意志 (zìyóu de yìzhì, “freedom of the will”)—and of the Indo-European etymologies of Greek terms like hekusion and prohairesis (προαιρεσις, “deliberated choice”), suggest that neither the Chinese nor the ancient Greeks postulated the existence of free will.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".