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Record W4328031149 · doi:10.1558/rosa.24396

Deferential Krsna

2022· article· en· W4328031149 on OpenAlexaff
Christopher R. Austin

Bibliographic record

VenueReligions of South Asia · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMythologyTheme (computing)Context (archaeology)LiteratureTransgressiveEPICHistoryMarine transgressionAestheticsPhilosophyArt

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.024
GPT teacher head0.208
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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