Sinner to saviour: the ‘new translation’ of <i>Renwang Jing</i> 仁王經 and mid-Tang throne’s redemption
Bibliographic record
Abstract
The mid-Tang imperial court’s authority was undermined not only by An Lushan Rebellion but also by the defiant regional commands established to counter the rebels. Disasters and ill omens—signs of a potential loss of Heaven’s Mandate in traditional views—provided these internal and external rivals with a political tool to rally support. The recension of the Renwang jing conducted in such a context offered an alternative explanation for the origins of both sovereignty and calamities, aligning with the interests of the ruling authority. Disasters and ill omens, still seen as portending a nation’s downfall, were then reframed as the result of collective misdeeds shared by all inhabitants, with salvation attainable only through a united national effort guided by the ruler. The grand public preaching on the scripture then could help recast the ruler, previously a culprit in indigenous discourse, an essential saviour worthy of support and reverence. A central aim of the text’s revision was to propagate this more politically advantageous doctrine, reflecting the political stance of Buddhist monastics amid the mid-Tang crisis and contributing to the revival of Imperial Buddhism in the aftermath of the rebellion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".