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Record W4386642884 · doi:10.54254/2753-7064/6/20230162

The Influence of the Development of ‘Sang Culture’ on Chinese Youth

2023· article· en· W4386642884 on OpenAlexaff
Xinyi Huang, Yingyi Huang, Yuxin Wang

Bibliographic record

VenueCommunications in Humanities Research · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsBishop's UniversityUniversity of British Columbia
Fundersnot available
KeywordsPopularityPopular cultureChinese cultureYouth culturePessimismPsychologyChinese peopleChinaSociologyGender studiesAestheticsSocial psychologyMedia studiesHistoryArtEpistemology

Abstract

fetched live from OpenAlex

"Sang Culture" is a culture popular among Chinese youth. They use pictures, language and words to express dissatisfaction and pessimism emotion in different media. In this research, the authors want to find the influence of the development of "Sang culture" on Chinese youth, to see what let this culture be popular, to understand Chinese young people's views on this culture. The authors use interviews around different ages and places in Chinese youth to comprehensive understanding of the mourning culture in their eyes. From the interviews, the authors know that the culture of mourning is indeed widespread, mainly due to the pressure of life, studies and other aspects. Based on their judgment and other similar research, the authors believe that the culture of mourning will be replaced by a better culture. The reason why the authors can find its popularity and influence is decreasing. Comparing these interviewees’ age, the authors see younger are more not impact on their life. They also realize Sang Culture is not the best way to expire their pressure.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.464
GPT teacher head0.468
Teacher spread0.004 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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