Individuality in Commonality: A Comparative Study of Su Embroidery and Gu Embroidery Based on Online Retrieval of Museum Collections
Bibliographic record
Abstract
As traditional handicrafts in the south of the Yangtze River, Su embroidery and Gu embroidery are closely related to each other due to their geographical proximity, mutual exchange of embroidery techniques and similar cultural backgrounds. In recent years, there has been considerable research on the historical origins and relationship between the two, but no unified conclusion has been formed. Through the combination of quantitative statistics of online collections in domestic museums and qualitative analysis of literature records, following the idea of “deconstruction - research - recombination”, this paper studies the similarities, differences, and influencing factors of Su embroidery and Gu embroidery, and illustrates the relationship between them. Su embroidery and Gu embroidery are two independent embroidery categories, which showed the characteristics of “Individuality in Commonality” with the evolution of the historical process. Under the call to revitalize traditional handicrafts, it is beneficial for the protection and inheritance of Su and Gu embroidery to trace their historical origins, analyze their respective technical characteristics, and clarify their relationship.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| 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".