THEORIES OF THE SELF, RACE, AND ESSENTIALIZATION IN BUDDHISM: THE UNITED STATES AND THE ASIAN “OTHER,” 1899–1957. By RyanAnningson. Routledge Studies in Asian Religion and Philosophy. London and New York: Routledge, 2021. Pp. xii + 222. Hardback, $170.00; Paperback, $48.95.
Bibliographic record
Abstract
Based on a doctoral dissertation submitted to Wilfrid Laurier University in Canada in 2017, this monograph investigates the implications of Buddhist "Aryanism" (i.e., Buddhism understood as a superior religion related to the Aryan "race") in the United States between the end of the nineteenth century and the late 1950s.As illustrated by Anningson, those years in American history marked the development of a distinctive "yellow peril" ideology, to which Buddhism largely responded through adaptations at the intersection of modernism and bio-racism.This book approaches the "Aryanization" of Buddhism in the United States from a broad perspective, starting with a discussion of the Aryan myth itself, its link to colonialism, racism in North American history, and the impact of these factors on the academic study of Buddhism in those years.Further background analyses are provided in Chapters Four and Five, which introduce examples of the use of Aryanism by various Buddhist players.Among these, one finds Anagārika Dharmapāla's (1864-1933) pseudo-scientific opposition of Europeans (identified with the "Dravidian camp") and Buddhists (identified with the superior "Aryan camp"), as well as the claim that Japanese Buddhism represents the "true Aryans" and the very pinnacle of Buddhism and civilization tout court.Japanese Buddhism features more preeminently in the following chapter, which compares the trajectories of Zen and Shin Buddhism.Here, Anningson identifies notably in American Zen a meaningful promotion of race-craft through a skillful use of the Aryan myth, while he acknowledges in American Shin also a certain tendency to reinterpret traditional doctrines through the lenses of secular thought.Although more careful editing would have perhaps eliminated many of the repetitions and made the text more readable, this volume certainly introduces new materials and provides some significant contributions to the discussion of race, ideology, and religion in the North American context.As such, it is suggested to scholars and students of Buddhism, religion in the United States, and East Asian religions in general to integrate their readings on these topics.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".