Art and the Shift in Garden Culture in the Jiangnan Area in China (16th - 17th Century)
Bibliographic record
Abstract
The remarkable growth in interest in aesthetic gardens in the late Ming period has been recognized in Chinese garden culture studies. The materialist historical approach contributes to revealing the importance of gardens’ economic functions in the shift of garden culture, but is inadequate in explaining the successive burgeoning of small plain gardens in the 17th century. This article integrates the aesthetic and materialist perspectives and situates the cultural transition in the concrete social and cultural context in the late Ming period. Beginning with describing a taste change and an expansion in the number of gardens, this article focuses on the small plain garden phenomenon by exploring the unique role that the arts (e.g., poetry and painting) played. A series of artistic criteria were established in the late Ming period. The application of these aesthetic rules to gardens enabled more people to own gardens. This is process that economic requirements for owning gardens were lowered, giving way to the aesthetic appreciation and exploration of literati individuals’ artistic talents. Gardens thus became more widely accessible and provided enhanced pleasure to the middle and lower class families. The conclusion is that the ‘major shift’ in garden culture was closely associated with the change of garden owners’ aesthetic tastes, in addition to the economic conditions in the Jiangnan area. In the increased popularity of gardens, the arts played a significant role.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".