Seeing the Peony in Early Qing-Dynasty Art: An Embodiment of Individual Identity
Bibliographic record
Abstract
Within the context of the Manchurians’ conquest of the Ming dynasty and their subsequent establishment of a new imperial rule, the intricate symbolic systems embodied in floral imagery, particularly the peony flowers, instilled a profound sense of insecurity in the nascent Qing court. Despite the government’s strict scrutiny of the visual and literary works of literati, as well as the imperial authority’s monopolization of peony portrayals, Yun Shouping and Gao Fenghan’s paintings of peonies exude an air of innocence and purity. However, beneath their seemingly tranquil facade lay internal struggles with themselves in the context of the era, along with a subtle defiance towards the new governing regime. This study examines how the two artists transcended the constraints of traditional depictions and aesthetic conventions surrounding peonies dictated by the highest social class, by analyzing the visual aspects of their peony paintings in conjunction with their biographical accounts, thus individualizing the floral motif with distinctive artistic languages. It exemplifies the reclamation of Yun and Gao’s dominion over each visual realm, wherein they assert their autonomous authority in shaping the conveyed information and emotions through the blossoms, while also finding security and solace in redefining and recontextualizing the subject matter whose symbolic significance has endured for millennia.
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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 | 0.001 |
| 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 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".