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Record W1596360718

The Inheritance Plight of Yangtze River Chant and Its Rescue and Protection Measures

2015· article· en· W1596360718 on OpenAlexvenueno aff
Tingting Yan

Bibliographic record

VenueCross-cultural communication · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsInheritance (genetic algorithm)Yangtze riverCultural inheritanceMechanism (biology)Protection mechanismField (mathematics)Investment (military)GeographyPolitical scienceEnvironmental resource managementHistoryChinaComputer scienceLawEnvironmental scienceBiologyArtificial intelligenceEpistemologyLiteratureArt
DOInot available

Abstract

fetched live from OpenAlex

“Yangtze River chant” is one of the first group of national non-material cultural heritages. The author has conducted extensive field researches on the inheritance status of Yangtze River chant. Achievement has been made from the application for non-material cultural heritage to the post application era, but there is also a plight. Scientific and practical protection policy should be made to ensure Yangtze River chant can be effectively preserved and inherited. As for problems such as the inheritance mode tends to be single, the inheritance investment is not enough, the evaluation mechanisms is still absent, and the working mechanism needs to be specified, the author has advocated protection measures such as to establish diversified inheritance modes, to improve the evaluation mechanism and to develop a clear division system of right and responsibility, etc.. This article is based on systematic methods, interviews and field researches to explore the internal mechanism of effective inheritance and ecological protection.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

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 studies0.0040.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.186
GPT teacher head0.304
Teacher spread0.118 · 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 designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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