A song to "The beautiful Goddess": Text, ritual, and devotion in the «Apirami Antati»
Bibliographic record
Abstract
My project locates the 18th century Tamil poem Apirāmi Antāti at the interstices of popular Tamil devotion (bhakti), a form of South Indian Tantra known as Śrīvidyā, and the upper-caste (Brahmin) social, cultural, and ritual worlds that engender the text. Bringing together inter-textual, and ethnographic analysis, I argue that the simultaneous appearance of Tantric themes, alongside themes of Brahmanic domesticity in the text point towards Śrīvidyā, a practice that integrates esoteric Tantric practice with uppercaste Brahmanic social behaviour. My linkage of the Apirāmi Antāti with Śrīvidyā is substantiated by a critical historcization of the Apirāmi Antāti that locates the text in the emergent Tamil Brahmin Tantric milieu at the Tanjavur court in the early eighteenth century. Finally, there is something about this milieu, the shrine of the goddess, and her consort at Tirukkadaiyur that has had an enduring value for the largest group of Tamil Brahmins known as Smārtas. Using ethnographic data the later part of this thesis examines the contemporary appeal of this poem to upper-caste devotees of the goddess. I discuss a rite-of-passage (samskāra), known as śatābhisekam, which is performed at Tirukkadaiyur, and allows the poem and its goddess to become identified with Smārta Brahmin cultural values.
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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 | 0.001 | 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 | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 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".