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Record W4387341504 · doi:10.11647/obp.0312.01

Introduction / སན་གང་ག་གཏམ། / 导论

2023· book-chapter· en· W4387341504 on OpenAlexaff
Bendi Tso, Marnyi Gyatso, Naljor Tsering, Mark Turin

Bibliographic record

VenueWorld oral literature series · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOralityTextualityBuddhismIndigenousContext (archaeology)GeographyChinaPerformative utteranceHistoryArabicAnthropologyFace (sociological concept)EthnologyAncient historyArchaeologyArtSociologyAestheticsLiteraturePhilosophySocial scienceLinguistics

Abstract

fetched live from OpenAlex

Shépa is an encyclopaedic collection of antiphonal songs that have been practiced by the Choné people, a Tibetan subgroup residing in Gansu Province of northwest China, for centuries. This collection details Tibetan cosmology, geography, history, social customs, and cultural-religious objects, among other themes. It also contains cultural elements from neighbouring civilisations that were adopted by Tibetans. The content and performative styles of Shépa overlap with other forms of Tibetan oral tradition from northern Amdo to the southern Himalayas. Shépa also has a long-standing and entangled relationship with Tibetan literature, blurring the boundaries between orality and textuality and resisting strict demarcation. Currently, the performance and transmission of Shépa face new challenges and opportunities in the context of intangible cultural heritage preservation. For the Choné people as well as for broader Tibetan society, Shépa constitutes a repository of Indigenous, Bon, and Buddhist knowledge.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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