Oral Commentaries and Scholarly Debates in Sanskrit Philosophy
Bibliographic record
Abstract
OVER THE FALL and winter of 2020–2021, students and faculty at the University of Toronto and the Manipal Academy of Higher Education in India came together to study with two renowned scholars of classical Sanskrit knowledge systems: Shree Vidyashreesha Tirtha (formerly Dr. D. Prahladacharya) and Dr. Mani Dravid Shastrigal. As in many traditional learning contexts, these pandits used oral commentary in Sanskrit to guide students through philosophical texts. Unlike in most traditional learn-ing contexts, however, this oral commentary was conducted entirely online via the Zoom conferencing platform. This paper highlights the continuities and disjunctures of this digital commentarial experience within the larger genre of Sanskrit philosophical com-mentaries and explores the relationship between written commentary and orality in this new media landscape. The pandits taught sections of two influential works of philosophy and metaphys-ics: the Nyāyāmṛta (Ambrosia of Logic) by Vyāsatīrtha (fifteenth/sixteenth century) and a polemical rejoinder known as the Advaitasiddhi (The Success of Non-Dualism) writ-ten by Madhusūdana Sarasvatī (sixteenth century). In addition to being highly intertex-tual—incorporating excerpts and citations from a millennium of writings—these texts are highly technical and require expertise in several Sanskrit knowledge systems, mak-ing the oral exegesis of an expert all the more necessary for their study. The first part of this paper, attributed to Elisa Freschi, introduces Sanskrit philosophical commentaries in a broad sense. By showing how philosophical commentaries function through net-works of inter-texts, Freschi explains how commentary was the de facto way of doing philosophy for Sanskrit intellectuals. The next section, attributed to Jonathan Peter-son, contextualizes Vyāsatīrtha and Madhusūdana Sarasvatī within two influential (but mutually antagonistic) traditions of scriptural hermeneutics known as Vedānta . The third section, attributed to Ajay Rao, uses the sessions with Vidyashreesha to examine the relationship between textuality and orality in the context of Vedānta commentary. Commentaries as Networks What makes a text a “commentary”? The question, as Isabelle Ratié shows in this issue, requires a complicated answer. There is no single word for “commentary” in Sanskrit. Rather, there are several, each of which conveys different qualities and degrees of textual engagement. The bhāṣya , for instance, usually entails an extensive elaboration on a con-cise (often cryptic) root text: the Mahābhāṣya of Patañjali is but one of many examples. A vārttika , on the other hand, often indicates a concise, laconic commentary—Kātyāyana's Vārttika on Pṇini's Aṣṭdhyāyī , for instance.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.017 | 0.018 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".