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Record W3206894731 · doi:10.23977/aetp.2021.56023

Reflections on the Development of Chinese National Vocal Music

2021· article· en· W3206894731 on OpenAlexvenueno aff
Xiaolan Xie

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSingingPower (physics)GlobalizationChinese cultureVocal musicAestheticsSociologyPolitical scienceMusicChinaMusic educationVisual artsArtManagementLaw

Abstract

fetched live from OpenAlex

If the singing art wants to go to the world, it must first strengthen the national personality. The stronger the national personality, the stronger the cosmopolitanism. Today's world is in an era of globalization and cultural diversity, which provides an opportunity for the inheritance and development of Chinese national vocal music art and the world. We must seize this historical opportunity and make full use of all available opportunities and channels to make Chinese people love their own vocal music culture; let people of all countries in the world understand Chinese national vocal music culture, and then like and love our national vocal music culture. In the process of inheriting Chinese traditional vocal music culture, we should develop and innovate our national vocal music culture; while building an economic power, we must also create the image of a cultural power. Therefore, it is of strategic significance to strengthen the national development of Chinese vocal music art, as well as the worldwide dissemination.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.047
GPT teacher head0.465
Teacher spread0.418 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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