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Record W2102155111 · doi:10.1017/s0021911812002227

Blazing Pelts and Burning Passions: Nationalism, Cultural Politics, and Spectacular Decommodification in Tibet

2013· article· en· W2102155111 on OpenAlexfundno aff
Emily T. Yeh

Bibliographic record

VenueThe Journal of Asian Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
FundersSimon Fraser UniversityUniversity of California, Santa Cruz
KeywordsCommodificationCeremonyNationalismPoliticsPassionsBalladGrassrootsSociologyPolitical economyHistoryPolitical scienceGender studiesLawEconomyArt

Abstract

fetched live from OpenAlex

A few months after the fourteenth Dalai Lama stated at the Kalachakra Initiation Ceremony in India in January 2006 that Tibetans should cease wearing clothing lined with endangered animal skins, Tibetans across the Tibetan Plateau destroyed millions of yuan worth of otter, leopard, tiger, and other pelts. Outsiders' interpretations of these events have flattened out the complexity of participants' motivations, which included not only religious and national loyalty, but also concerns about inequality wrought by capitalist development, framed through a lens of modern Chinese history. This paper traces heated debates among Tibetans about the burnings, including their implications for Tibetans' global reputation, the survival of Tibetan culture, and the possibility of a moral economy in an era of deepening commodification. It also explores the embodied, visual, and performative elements of the burnings through participants' videos. The role of local filmmaking efforts in spreading the burnings makes the accompanying videos especially relevant.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.293
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.377
Teacher spread0.327 · 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

Citations27
Published2013
Admission routes1
Has abstractyes

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