An Phased Analysis on the Research of Textile and Costume History in Journal of Silk
Bibliographic record
Abstract
The historical theory column "History and Culture" of Journal of Silk is unique in the textile and costume journal industry. Many famous scholars in history and nowadays have written papers on this column. The phased research on the column will help us clarify the academic history and important figures of textile and costume history. Based on the relevant statistics of Journal of Silk, the research concludes that: ① The name change of historical theory column in Journal of Silk reflects the determination of Journal of Silk whose historical theory column starts from the history of silk and finally extends to the entire history of textile culture and textile technology. ② The research on clothing history in Journal of Silk can be divided into four periods. 1977-1986 is the budding period, 1987-2003 is the hovering period, 2004-2014 is the stable period, and 2015 is the accelerated development period. ③ The factors of this stage are closely related to the amount of papers published. The changes in the amount of papers published in the previous period are closely related to politics. With the deepening of economic reforms, it is closely related to the reform and development of the textile industry and the development of universities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.027 | 0.029 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".