Chinese and English Horoscopy in the Sixteenth and Seventeenth Centuries: The Astrological Doctrines of the Twelve Houses and the Lot of Fortune in Xingxue dacheng 星學大成 by Wan Minying 萬民英 (1521–1603) and Christian Astrology by William Lilly (1602–1681)
Bibliographic record
Abstract
Abstract This study compares the astrological doctrines of the Twelve Houses and Lot of Fortune as they are explained in Xingxue dacheng 星學大成 of Wan Minying 萬民英 (1521–1603) and Christian Astrology by William Lilly (1602–1681). These two astrologers, who were near contemporaries, lived on opposite sides of Eurasia, yet both were heir to traditions of astrology that together reached back to identical origins in the Near East. The use of largely similar doctrines between both authors testifies to the enduring integrity of astrology throughout centuries of transmission westward and eastward through multiple cultures and languages.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.001 | 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".