Enacting Identities: Chōgen, Kujō Kanezane, and the Tōdaiji Great Buddha
Bibliographic record
Abstract
This article examines the collaboration of the Shingon monk Chōgen (1121–1206) and the powerful courtier Kujō Kanezane (1149–1207) in the restoration of Tōdaiji’s Great Buddha statue, which still stands as one of Japan’s leading national symbols. Resituating Judith Butler’s insights on how performance continuously constructs rather than simply expresses identity, I use Chōgen’s and Kanezane’s material, ritual, and narrative restoration activities to argue that this insight holds as true for the objects and places venerated in religious performances as for the performers themselves. The article is most concerned with the shifting deity identities for the Great Buddha enacted by the monk and the courtier in connection with their dedications of relics and other material-ritual offerings. The article also shows that those deity identities were tied to identifications of the statue as an embodiment of imperial and Buddhist law (ōbō-buppō) and to constructions of Tōdaiji and Japan as Buddhist centers in their own right. I argue that these multiple, intertwined identities for icon, object, and place were—like the gender and sexual identities that Butler explores—all contingently constructed through performances that changed over time. Moreover, I suggest, the very need for repetition underscores the fluidity and instability of the identities invoked in the performances. Simultaneously, however, I argue that we must also recognize the constraints for resignification imposed by the particular contexts of materiality and precedent that we examine.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".