Bibliographic record
Abstract
Born in Guangdong Province on June 20, 1937, Wai-lim Yip moved to Hong Kong, where he began his life as a poet. He soon moved to Taiwan and graduated from National Taiwan University with a BA in 1959, and then earned an MA in 1961 from National Taiwan Normal University. Then in 1963 he traveled to the United States, where he earned an MFA from the prestigious Iowa Writers' Workshop at the University of Iowa, and later a PhD from Princeton in 1967. He accepted a position at the University of California, San Diego that same year and taught there until his retirement in 2010. Over these many years Yip has published over fifty volumes of critical, scholarly, and poetic work in both English and Chinese; his influence in American poetry circles and abroad is significant and extensive. He has taught or lectured in Taiwan, Hong Kong, Beijing, Shanghai, and many other universities across China, and he has been instrumental in setting up Comparative Literature programs throughout Taiwan and China. With several recent conferences in China devoted to his work, Yip has become arguably one of the most important East-West scholar-poets of the last quarter-century.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".