Chinese Folklore for Modern Times: Three Feminist Re-visions of <i>The Legend of the White Snake</i>
Bibliographic record
Abstract
Folktales function as a form of cultural heritage in contemporary society and offer models for interpreting experience in everyday practices, but the beliefs and values conveyed by many folktales are ingrained in a patriarchal discourse. Thus, the models they offer are challenged by the modern prominence given to women’s perspectives. This article applies an intertextual analysis in a broad cultural context by exploring how the White Snake story has been transformed to cater to modern progressive attitudes on gender and sex. By focussing on the modern adaptations of the White Snake legend by three female authors – Hong Kong author Li Bihua’s novel, Green Snake (1986), American–Chinese writer Yan Geling’s novella, White Snake (1999), and Canadian author Larissa Lai’s novel, Salt Fish Girl (2002) – this study examines how contemporary Hong Kong and Chinese diasporic female authors incorporate and adapt old folktales in their separate narratives. By adapting the well-known folktale through female voices, the three novels challenge the inherited literary and cultural tradition, interrogate and question its gendered discourse defined by the heteronormative patriarchal family structure, and suggest ways in which non-normative sexuality and gender roles can be imagined and practised by female members of the society.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".