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Record W3197051634 · doi:10.23977/aetp.2021.56020

The Generation and Classification of Miao Folk Songs in Western Hunan

2021· article· en· W3197051634 on OpenAlexvenueno aff
Kongxuan Xu

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBeautySadnessEthnic groupAngerHistoryFolk songEthnologyGeographyArtAestheticsSociologyLiteratureAnthropologyPsychology

Abstract

fetched live from OpenAlex

Some people ask, “why do most of the Miao people in Western Hunan still live in mountains and valleys?” At that time, they were forced to work together to fight against the national treasures of the west, but they were forced to struggle against the national treasures of the West because of the oppressive policies of the ethnic minorities. Since ancient times, Miao songs in Western Hunan have also been an indispensable part of Miao people's daily life. Because Miao people have no written expression, their cultural and artistic heritage can only be realized in the form of song and music. Their usual joy, anger, sadness and joy are also reflected in Miao songs vividly. In the big garden of Chinese folk music, Xiangxi Miao song also has its own unique beauty.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.080
GPT teacher head0.337
Teacher spread0.257 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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