Artisans’ Knowledge on Bronze Making in Ancient China: Cross Examination of the Casting Moulds of the Shang Dynasty
Bibliographic record
Abstract
This dissertation examines the production of bronze casting vessels by studying the bronze casting moulds produced and used by bronze artisans. Since its discovery, Chinese bronze vessel production has captivated archaeologists' interest and ongoing research. Most of the focus was on the vessels and how the elites used these vessels to represent power and prestige, but that was only half of the story of the past involving bronze vessel production. More recent research has focused on the casting moulds used to produce the bronze vessels and looking at them as their artifacts. We were missing a crucial part of the past involving the artisans' choices in making the vessels, knowledge, and organization by combining the data collected through hand specimen, petrographic, and scanning electron microscope (SEM) analysis of the three bronze vessel casting moulds housed at the Royal Ontario Museum (ROM).The result from this dissertation indicated a highly specialized group of artisans who worked in three of the main foundry sites and supplied their casting moulds to the other foundries of Anyang. From the similarities and differences between the sequence of production, the Anyang mould artisans shared raw material resources and firing techniques within their specialization, while two distinct groups formed the casting moulds. Although there were two different production methods, the production method stayed consistent within the two groups with little to no experimentation within the production sequence. The lack of experimentation further supports the production being a highly specialized profession with the knowledge held by the bronze casting mould artisans. The consistency in production also suggests that the artisans passed down their knowledge with verbal and hands on instructions to ensure the exact method of production continued during the Anyang occupation.
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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 | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".