Bibliographic record
Abstract
This article offers a new perspective on the study of the discourse on superstition (mixin) in modern China. Drawing upon recent work on the import of the concept “superstition” to the colonial world during the 19th century, the article intervenes in the current study of the circulation of discursive constructs in area studies. This intervention is done in two ways: first, I identify how in the modern era missionaries and Western empires collaborated in linking anti-superstition thought to discourses on women’s liberation. Couched in promises of civilizational progress to cultures who free their women from backward superstitions, this historical connection between empire, gender and modern knowledge urges us to reorient our understanding of superstition merely as the ultimate other of “religion” or “science.” Second, in order to explore the nuances of the connection between gender and superstition, I turn to an archive that is currently understudied in the research on superstition in China. I propose that we mine modern Chinese literature by using literary methods. I demonstrate this proposal by reading China’s first feminist manifesto, The Women’s Bell by Jin Tianhe and the short story Medicine by Lu Xun.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".