Arhant Mahinda as Redactor of the Buddhapujava and the Panca-, Atthangika- and Dasa-silas in Sinhala Buddhism
Bibliographic record
Abstract
Buddha Puja ‘Homage to the Buddha’ is a religious practice found in every Buddhist temple and many a Buddhist household around the world. Over the last two millennia or more, it has taken many a shape and turn. This treatment, however, relates to the Buddha Puja in the particular cultural context of Sinhala Buddhism, writing it as a single word, Buddhapujava (with a -va denoting the Sinhalizing suffix) to distinguish it from the ritual in other cultural contexts. It is as practiced in Sri Lanka, ironically, not in Sinhala but in Pali , Buddhism being introduced in the 3rd c. BCE by Arhant Mahinda during the reign of Devanampiya Tissa in the Anuradhapura period. It is not the Buddhapujava itself, however, that is the topic of this paper, but its authorship. Finding no evidence of its authorship, or origin, in India, it comes to be located in Sri Lanka. Seeking evidence for its Redactor from within the ritual itself, we are led to none other than Arhant Mahinda who introduces the Buddhadhamma to the island. It is also established how, in the very process of creating the Buddhapujava, the panca-, atthangika- and dasa-silas also come to be systematized into a coherent pattern. Two alternative dates for the possible launch of the ceremony are suggested, making it the oldest living Buddhapuja ritual in the world. In a concluding theoretical detour, a distinction is made between an Etic Buddha Puja and an Emic Buddha Puja.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".