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Record W7133043710

Incarnation on the Roof of the World: A History of Practices to Identify Trülku (sprul sku) in Tibetan Buddhism.

2023· dissertation· W7133043710 on OpenAlexfundno aff
Kunga Sherab

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldArts and Humanities
TopicLinguistics and Cultural Studies
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsPoliticsInterpretation (philosophy)IncarnationIdentification (biology)Period (music)InstitutionScale (ratio)History of religions
DOInot available

Abstract

fetched live from OpenAlex

This dissertation is a cultural history of practices used to identify certain children as trülkus (Tib. sprul sku; Mong. khubilgan; Ch. huofo 活佛). Trülku were elevated as religious and political authorities in Tibetan cultural regions beginning in the thirteenth century and continuing today. The practices used to identify trülku adapted and grew as this institution grew in religious, social, political, and economic importance across Inner Asia, from practices that were extremely local in scale in the early period to large scale, public examination and blind texts in the later period. New practices were innovated to satisfy competing sources of trans-regional authority, such as the identification and testing of multiple candidates during the rapid growth of new trülku lineages during the escalation of early Géluk-Kagyu confrontations of the 15th century and the extension of new Qing imperial policies aimed at centralizing imperial authority and foreign relations at the end of the 18th century. During each new period of growth, older and more local practices of identification endured, such as dream interpretation and analyzing the self-statements and unusual behavior of young children. This multi-sited and comparative study of practices to identify the enlightened among human children over eight centuries offers new insight into wider themes in religious and political history in Tibetan Buddhism.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.394
Teacher spread0.288 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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