Bibliographic record
Abstract
Critical Essays was conceived when the editors prepared for the international workshop on Wang Wenxing at the University of Calgary in 2009.Many years have passed since then, and the editors are pleased to see it reach fruition at last.On the eve of publication, the editors feel grateful to many people for their support and selfless assistance.First of all, we would like to express deep appreciation to Wang Wenxing and Chu-yun Chen for their long-term support of this project, in addition to their contributions in writing and assistance with the cover design.During these years, Wang and Chen have been busy traveling all over the world, attending conferences, doing interviews, and being present at award ceremonies; nevertheless, they were always ready to answer the editors' questions and offer all sorts of needed support.Without them, the completion of this project truly would have been impossible.Second, the editors wish to thank the contributors-our dear colleagues and friends-who shared the same interests with us all these years, working hard on revisions and waiting patiently and trustingly for any progress in our preparation of the final version.Their moral support is much appreciated.Among them, the editors especially thank Te-hsing Shan for granting us permission to republish "The Streamof-consciousness Technique in Wang Wenxing's Fiction" and "Wang Wenxing on Wang Wenxing." We also want to thank Anita Lin, Emily Wen, and Roma Ilnyckyj for their assistance in compiling the bibliographies.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.070 | 0.037 |
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".