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Record W2911961469

Popular Music and Gender Equity: Integrating Popular Music into Gender Studies in Grade 9-12

2019· article· en· W2911961469 on OpenAlexaboutno aff
Jiayi Wang

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsPopular musicGender equityPsychologyGender studiesSociologyPolitical scienceArtVisual arts
DOInot available

Abstract

fetched live from OpenAlex

Equity studies has been indicated in Ontario’s social sciences curriculum, and gender equity is included in the grade 11 course “Gender Studies.” Popular music, a crucial part of popular culture, is one of the favourite pastimes among adolescents. The relationship between popular music and gender equity as well as the educational value of popular music has been discussed extensively in both the music and sociology areas. Connecting to gender equity education in schools, this paper demonstrates how gender topics are displayed in popular music and the implications of using 21st-century popular music to discuss gender equity in grades 9-12. In addition, the paper explores the relationship between popular songs and gender equity by critically analyzing redundant popular songs.\nThe purpose of this paper is to illustrate the relationship between 21st-century popular music and gender equity, and the benefits of integrating popular music into introducing gender equity studies in grades 9-12.

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.005
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0010.002
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 head0.219
GPT teacher head0.301
Teacher spread0.082 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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