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Record W2890836402 · doi:10.3968/10562

Research on the Status and Development Countermeasures of Square Dance Based on Yongchuan District of Chongqing

2018· article· en· W2890836402 on OpenAlexvenueno aff
Xiaoyan Deng, Jia Luo

Bibliographic record

VenueCanadian social science · 2018
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsnot available
Fundersnot available
KeywordsDanceResearch ObjectSWOT analysisSquare (algebra)Object (grammar)SociologyVisual artsComputer scienceMathematicsManagementArtRegional scienceEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

With the rapid economic growth, the people have a higher pursuit of physical health and spiritual culture, so square dances spread all over the streets and are an important part of the cultural life of the people and a key form of expression. Through the study of square dance, it is possible to seek a good development platform for mass sports and to better promote the development of national fitness. This topic takes the current status of square dance in Yongchuan District of Chongqing as the research object, investigates the development of square dance here, and applies SWOT analysis to the research results, establishes a structural model and conducts a factor analysis finally. From the research, rules will be summed up, problems be found and recommendations be come up with to provide some basis for filling the gaps in the study of square dance in Yongchuan District, and also to offer references for the development of square dance in other regions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.106
GPT teacher head0.372
Teacher spread0.266 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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