An Ethical Literary Criticism of Han Suyin’s Autobiography
Bibliographic record
Abstract
Han Suyin (1916/1917–2012) became a household name when Love is A Many-Splendored Thing, the Hollywood rendition of her novel won several awards in 1956. The study of Han Suyin went out of fashion for a while, but it has recently been revitalised, especially in Singapore and Malaysia. Kuek pays attention to The Crippled Tree autobiographical series, delineating her two-track narrative of her family saga against the backdrop of 20th century China. Different from the earlier studies on Han Suyin that employed perspectives from postcolonialism, feminism, and new historicism, this book examines Han Suyin’s autobiography through the lens of ethical literary criticism (ELC), paying attention to the ethical lines and knots embedded in her series. Using ELC, an apolitical literary analysis approach, this book uncovers multiple layers of meaning and reveals Han Suyin’s life trajectory which draws attention to China’s difficult path of modernisation in the past century. The insights gleaned from this book shed light on Han Suyin’s life accomplishments in the face of great adversities and challenges. This is a valuable book that will enlighten literary critics on critical approaches to autobiography and those interested in understanding the development of modern China through the words of a proud Chinese-Eurasian writer living in the era.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".