Translating the Buddha: Edwin Arnold’s Light of Asia and Its Indian Publics
Bibliographic record
Abstract
In this article, I examine the popular Victorian poem The Light of Asia (1879) and its reception and adaptation in late nineteenth and early twentieth century colonial India. Authored by the popular writer, Sir Edwin Arnold, The Light of Asia is typically regarded as one of the foundational texts of modern Buddhism in the western world. Yet significantly less has been said about its influence in Asia and especially in India, where it has as an equally rich and varied history. While most scholarship has focused on its connections to the Sinhalese Buddhist leader Anagarika Dharmapala and his popular campaigns to ‘liberate’ the MahaBodhi Temple in Bodh Gaya, the singular focus on Dharmapala has obscured the poem’s much more expansive and enduring impact on a wide array of colonial Indian publics, regardless of caste, region, religion, ethnicity or language. The article explores the early history of its numerous adaptations, dramatizations, and translations in various regional languages. In providing an analysis of the poem’s Indian publics, the article shows how regional, political, and cultural idioms formed in multilingual contexts enable different readings and how literary and performative cultures interacted with colonial conceptions of religion, nation, and caste.
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 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 | 0.007 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".