Canonization and commodification: illustrations to the Tales of Ise in the modern era
Bibliographic record
Abstract
By the early nineteenth century, illustrations and visual appropriations of the tenth-century court romance lse monogatari [Tales oflse] existed in a bewildering variety.There was the standardizing iconography of the Sagabon (Fig. 1) [all figures are at the end of the article], first published in 1608, and reproduced, with minor changes, continually throughout the Edo period. 1 There was the elite iconography of what would eventually be called Rimpa, 2 recycling imagery from the fourteenth-century Ihon, or "variant," illustrated version.There were parodies born out of the standardization of the Saga-bon 3 and Narihira's close association with shunga.4 By the eighteenth century, Tales of Ise was appearing on the stage, which in turn led to it functioning as a major trope of mitate-e, or visual parodies.5 Finally, by the same period there were editions of the lse designed to serve as primers, 1 The two best and most easily accessible collections of lse-e reproductions are Chino Kaori, (Emaki) lse monogatari e, Nihon no bijutsu 6.301 (Tokyo: Ibundo, 1991 ); and the exhibition catalogue lse monogatari no sekai, Gotoh Bijutsukan, 1994.On Saga-bon see also Katagiri Yoichi, ed., lse monogatari (KeichO jusan-nenkan Saga-hon dai-isshu) (Osaka: Izumi Shoin, 1981), and Fritz Rumpf, Das lse Monogatari von 1608 and sein Einfluss auf die Buchillustration des XVI/.Jahrhunderts in Japan (
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".