Bibliographic record
Abstract
In this paper, I intend to make a case for Buddhist phenomenology. By Buddhist phenomenology, I mean a phenomenological interpretation of Yogācāra’s doctrine of consciousness. Yet, this interpretation will be vulnerable if I do not justify the way in which the anti-essentialistic Buddhist philosophy can countenance the Husserlian essence. I dub this problem of compatibility between Buddhist and phenomenology the ‘problem of essence’. Nevertheless, I argue that this problem will not jeopardize Buddhist phenomenology because: 1) Yogācārins, especially late Yogācārins represented by Xuanzang do not articulate emptiness as a negation but as an affirmation of the existent; 2) Husserl’s phenomenological essence is not a substance that Yogācārins reject but the ideal sense (Sinn) that Yogācārins also stress. After resolving the problem of essence, I formulate Buddhist phenomenology as follows: on the epistemological level, it describes intentional acts of consciousness; on the meta-epistemological level, it entails transcendental idealism.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".