Parochial Universalism, Democracy <i>Jihad</i> and the Orientalist Image of Burma: The New Evangelism
Bibliographic record
Abstract
In an episode in the South Indian version of the Ramayana by Kamban,' Rama, in hiding, shoots one of the monkey kings, Vali, in the back. As he lies dying with Rama's arrows in him, Vali asks Rama, how he, the epitome of the perfect human, the incarnation of Vishnu, the honourable warrior, could do such a cowardly and unjust thing? Rama replies that it is because Vali had taken the wife of his brother Sugreeva after killing him. Vali says he did not try to kill his brother, that Rama had gotten only one side of the story, and that, in his culture of monkeys, taking care of one's brother's wife after his death was quite common and expected. Besides, why is Rama imposing his human values on him and castigating him and his kind for not following them? Rama tells Vali that he is intelligent enough to know that there are higher ideals, and even if they are human and not monkey ideals, he still expects Vali's kind to meet these higher standards. In effect, Rama is saying: don't give me any of your 'monkey values' argument, what I'm advocating are universal values to which all should aspire. Vali finally acknowledges his inferior way of thinking and concedes that Rama isjustified in shooting him in the back after all; it is his pleasure to die at the hands of such an honourable man and for such a noble cause. This single incident of the Ramayana captures many of the themes contained in this essay.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.043 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".