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Record W3115613835 · doi:10.3167/arrs.2020.110104

Affective Futures and Relative Eschatology in American Tibetan Buddhism

2020· article· en· W3115613835 on OpenAlexafffund
Amy Catherine Binning

Bibliographic record

VenueReligion and Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsMcGill University
FundersSmuts Memorial Fund, University of CambridgeJesus College, University of CambridgeCambridge TrustUniversity of CambridgeMcGill University
KeywordsBuddhismNarrativeFutures contractRhetoricSalientCommon groundEschatologyAestheticsHistorySociologyLiteratureArtPhilosophyArchaeologyTheology

Abstract

fetched live from OpenAlex

Tibetan Buddhist prophecies of decline are largely unattended when it comes to practitioners’ lived experiences. This article considers such narratives through a focus on a community of American Buddhists in California. The relationship between Buddhist narratives of degenerating future and the American landscape is played out through the creation and distribution of sacred objects, which are potent containers for—and portents of—prophetic futures. Ruptures in time and landscape become, through the frame of prophecy, imaginative spaces where the American topography is drawn into Tibetan history and prophetic future. Narratives of decline, this article argues, also find common ground with salient American rhetoric of preparedness and are therefore far from fringe beliefs, but a more widely available way of thinking through quotidian life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.020
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.008
GPT teacher head0.265
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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