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Record W4379656318 · doi:10.4000/emscat.6109

The heritagisation of rituals: commodification and transmission. A case study of Nianli Festival in Zhanjiang, China

2023· article· en· W4379656318 on OpenAlexaff
Shanshan Zheng

Bibliographic record

VenueÉtudes mongoles sibériennes centrasiatiques et tibétaines · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsCanadian Heritage
FundersÉcole française d'Extrême-Orient
KeywordsCommodificationChinaGeographyArchaeologyEconomyEconomics

Abstract

fetched live from OpenAlex

This article inquires into the effects of heritagisation on popular religious practices in Guangdong Province, People’s Republic of China. With the establishment of the intangible cultural heritage (ICH) inventory system in China, numerous popular religious practices, such as procession of local deities, ancestor worship, temple festivals, exorcisms, divination, and spirit mediumship, are free of the stigma of “feudal superstition” and are now recognised as ICH. Based on the fieldwork conducted in the prefecture city of Zhanjiang (Guangdong Province, China) on the local festival tradition of Nianli, I examine how local communities respond to the Party-state’s efforts to safeguard ICH through two processes: the commodification and the transmission of ritual practice. How does the heritage-making process affect the commodification of ritual practice? And what impact has the participation of a plurality of new actors in ICH transmission had on the methods of transmission of local ritual 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 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)0.003
metaresearch head score (Gemma)0.003
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 score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.012
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.001
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 head0.033
GPT teacher head0.352
Teacher spread0.319 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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