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Record W2734021023 · doi:10.16997/book4.j

Girls Rock! Best Practices and Challenges in Collaborative Production at Rock Camp for Girls

2017· book-chapter· en· W2734021023 on OpenAlexafffundabout
Miranda Campbell

Bibliographic record

VenueUniversity of Westminster Press eBooks · 2017
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsToronto Metropolitan University
FundersFaculty of Communication and Design, Ryerson UniversityMiddlesex University
KeywordsProduction (economics)GeologyMining engineeringEconomics

Abstract

fetched live from OpenAlex

Rock Camp for Girls Montreal (RCFG) is a summer camp where girls aged 10-17 learn an instrument, form, band, and write and perform an original song. Based in a feminist mandate of empowerment, this camp seeks to foster greater inclusion of girls and young women in musical production. Mobilizing the concept of the community of practice (CoP), this chapter forwards a case study of RCFG through participation observation, examining this organization’s pedagogies and practices, and evaluating how conceptualizations of the CoP (Lave and Wenger 1991; Wenger 1998, 2010) afford a lens to understand how RCFG seeks to widen access to male-dominated music scenes through collaboration. Highlighting challenges and successes at RCFG in fostering greater participation in cultural production, this chapter contrasts RCFG’s mode of collaborative production with individual-focused and male-dominated norms in the music industry. Making use of Wenger’s (1998) CoP characteristics of mutual engagement, joint enterprise, and shared repertoire, this chapter defines RCFG as an alternative CoP in that its characteristics differ from normative practices in CoPs that may result in exclusion. While the RCFG model offers some potential in combatting barriers in entry to cultural production, this chapter concludes that collaborative modes of production alone cannot intervene in systemic barriers to entry to creative work or lack of equity in the creative industries writ large. REFERENCES<br>Lave, J., &amp; Wenger, E. (1991). <i>Situated Learning: Legitimate Peripheral Participation</i>, Cambridge: Cambridge University Press.<br>Wenger, E. (1998). <i>Communities of Practice: Learning, Meaning and Identity</i>, Cambridge: Cambridge University Press.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.214
GPT teacher head0.263
Teacher spread0.049 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes3
Has abstractyes

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