Reading the novel through odours : an investigation into Chinese olfactory aesthetics using The Story of the Stone as a case study
Bibliographic record
Abstract
By taking the mid-eighteenth Chinese novel Story of the Stone as a case study, this thesis aims to demonstrate that the concept of a literary “olfactory aesthetics” is a single object with two aspects: (1) authors employ odours as a xiefa 寫法 (narrative method) to add metaphorical, symbolic, and allegorical implications in fictional works; (2) readers (including late-imperial Chinese literary critics, as well as modern readers like me) employ odours as a dufa 讀法 (reading method) in interpreting olfactory narrations in early literary writings. Following an overview of several odour-related dufa in late-imperial commentarial history, chapter one introduces its odour-oriented dufa, including odour symbolism, olfactory division, odour distribution, odour cartography, and odour coordinates. Chapter two explores three ideological systems in this novel through examining the symbolic significance of odours and the mechanism of point of view in developing a framework of olfactory division. Chapter three uses odour distribution and odour coordinates to read the author’s mapping of Grand Prospect Garden. I argue that odours can serve as an approach to writing and reading fictional works, since (1) defining odours relies less on the defined characters’ “biological” odours, but more as the symbolic extension of their invisible essence such as characteristics, temperaments, and virtues. (2) The division between fragrant and foul-smelling odours often matches the definer’s evaluation of “the self” and “the other.” The characters in this novel divide along olfactory lines to evaluate others, closely matching the three separate yet linked ideological spheres long seen by scholars as central to the novel’s meanings. That is, the immortals’ play with real and unreal, the orthodox Confucian concern with moral obligations, and the cult of qing among the garden-world characters. (3) Odour overlap (and contrast) all match the close (and far) relationship between the occupants in this novel, as revealed in a four-character Chinese idiom, qiwei xiangtou 氣味相投 (people with similar personality and aspirations share the same odours and tastes). (4) Odours usually appear as symbolic signals of extraordinary experience, generate strong sensory atmospheres, and affectively map different spaces as overlapping zones in the literary imagination.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".