Bibliographic record
Abstract
Abstract This article continues the discussion on the nature of the early language of Buddhism and the language that the Buddha spoke, arguing that the received Pāli transmission evolved out of an earlier Middle Indic idiom, which is identified as akoine. Evidence for thiskoinecan be found by examining correspondence sets within Pāli and its various varieties and by examining parallel, cognate correspondence sets between Pāli and other Prakrits which have survived. This article compares 30 correspondence sets transmitted in theDhammapadarecensions: the Gāndhārī Prakrit verses, the partially Sanskritized Pāli and PatnaDhammapadaPrakrit verses, and the fully Sanskritized verses of theUdānavarga. By comparing cognate words, it demonstrates the existence of an underlying inter-language which in many cases can be shown to be the source of the phonological differences in the transmission. The paper includes a discussion on the two major factors of dialect change, evolution with variation over time, and the diffusionary, synchronic influence of dialect variation; it concludes that both are important, with dialect variation – and the phonological constraints of indigenous speakers who adopted MI as a second language – providing the pathways on which the natural evolutionary process was channeled.
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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 | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".