MétaCan
Menu
Back to cohort
Record W7113042101

Revisiting Women and the Electric Guitar:: Why the Research Needs to be Updated and Expanded

2025· article· en· W7113042101 on OpenAlexfundno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
FundersUniversity of California, San DiegoNelson Mandela UniversityUniversity of GlasgowUniversity of CambridgeEmory UniversityStrongUK Research and InnovationUniversity of South FloridaMcGill UniversityJohns Hopkins UniversityUniversity of OxfordHarvard University
KeywordsGuitarScholarshipMasculinityHuman sexualityOrder (exchange)
DOInot available

Abstract

fetched live from OpenAlex

This article investigates the state of the research on women and the electric guitar and argues that there is a strong need for further research in this area. Existing scholarship primarily focuses on factors that inhibit women from playing the electric guitar, is mostly centered on offline/pre-Internet women and guitar relations and tends to link the electric guitar with masculinity and male sexuality and characterize it as a male-dominated practice. This means that the reasons why women do play the electric guitar are not given much attention, the Internet’s impact on women’s guitar practice is largely omitted, and other ways of approaching the relationship between gender and the electric guitar are given minimal consideration. I argue that all of these aspects are vital for better understanding women and the electric guitar, and for advancing the cause of gender equality in music and are therefore in urgent need of further research.

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)0.035
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.037
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.007
Science and technology studies0.0070.034
Scholarly communication0.0170.044
Open science0.0040.009
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0110.002

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 head0.038
GPT teacher head0.282
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDialnet (Universidad de la Rioja)Same topicDiverse Music Education InsightsFrench-language works237,207