'Action Buddhism' in the Medieval Chinese Empire,
Bibliographic record
Abstract
This essay will focus mostly on the Tang dynastic empire (618–907 CE), a "second wave" empire as defined in the Introduction to this volume, and its relations with Buddhism, although it will be necessary to say something about earlier Chinese dynasties and about other religions. As we shall see, an awareness of history permeates the relationship between the Tang imperium and the Buddhist establishment; both parties were well informed as to what had happened between them before and tried to act accordingly. I will first give an overview of the normative state of relations between the Tang imperial government and the Buddhist church and supply some background on the historical context in which those relations occurred. I will then indicate what I see as the recurrent problems and potential benefits of the relationship (an issue common to empires and religions, as noted in the Introduction), mostly from the perspective of the Tang rulers. Then, I will examine the strategies adopted by the state
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".