Bibliographic record
Abstract
This paper examines the concluding scene (chapter 113) of the Harivamsa’s Krsna biography, in which Krsna tries to steal some cows, but then chooses not to. I argue that the episode should be understood first in connection with the Mahabharata’s amsavatarana frame of partial incarnations. Secondly, I bring to bear on Harivamsa 113 the multiple meanings of the cow in epic mythology, according to which the animal stands in for both the earth and the brahmin as paradigmatic objects of ksatriya protection. In so doing, I hope to provide a reading of Harivamsa 113 which illustrates its participation in a recurring epic theme of ksatriya transgression against the brahmin and subsequent retreat to a properly deferential position. I then historicize these bovine-encoded anxieties attending brahmin–ksatriya relations in their post-Mauryan context. Recognizing such themes at work in Harivamsa 113 can help us to see that, however much popular traditions may favour the playful and transgressive Krsna, his posture in the latter part of the Harivamsa is characterized by a complex conservatism informed by both historic and epic-mythological concerns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".