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EDITORIAL

2022· editorial· en· W4365800640 on OpenAlexaboutno aff
Estelle R. Jorgensen

Bibliographic record

VenuePhilosophy of Music Education Review · 2022
Typeeditorial
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyPoliticsMedia studiesSociologyResistance (ecology)Music educationSocial sciencePolitical scienceLawPedagogy

Abstract

fetched live from OpenAlex

Editorial Estelle R. Jorgensen In June 2019, panelists Panagiotis Kanellopoulos, Joseph Abramo, Randall Allsup, and Cathy Benedict drew attention to “Music Education in Times of Darkness” in their presentation to the International Symposium XII for the Philosophy of Music Education held at Western University, London, Canada. They could not have known the full extent of the disasters that would befall the world in the years following, including a Covid 19 pandemic, the continued spread of authoritarian and anti-democratic regimes, wars, famines, corruption, pervasive misinformation and disinformation, natural calamities, a Russian invasion of Ukraine on the European continent, racial and civic unrest, and an attempted political coup in the United States that heretofore viewed itself as a beacon of equality, democracy, and freedom. Collectively, they examined the importance of resistance against the rising tide of neoliberalism and autocracy and challenged musician educators to find a way through these “dark times” towards more humane approaches to music education. Their intersecting articles now appear in the symposium that leads off this issue. This symposium constitutes a self-contained discussion introduced by the authors. It comprises a quartet of articles dealing with matters of obligation to resist cooption by the political right, the question of whether creativity suffices to ensure criticality, resistance to neoliberal subjectivities among friendship groups in popular music, and subversive versus subsumptive creativity as a form of resistance. Kim Boeskov reflects on the problematic of the ambiguity of musical practice for the social analysis of music educational practice. In thinking of music education’s ambiguous relationship to matters of social justice, Boeskov forwards three principles of musical ambiguity that are of potential value in reflecting on social analyses of music education. These are music’s “bidirectionality,” “multiplicity of social meanings,” and “in-betweenness.” In unpacking these ideas, Boeskov [End Page 109] complicates social interpretations of musical and music educational practices and resists what might otherwise constitute oversimplified social readings of events. Ketil Thorgesen and Thomas von Wachenfeldt reflect on the musical learning and socialization of young Black Metal musicians through German and Nordic interpretations of the notion of Bildung. They show the similarities between the ideals and means of Bildung and the informal learning and socialization of these musicians. Thorgesen and Wachenfeldt suggest that juxtaposing Black Metal music and notions of Bildung provide conceptual tools for critiquing “hegemonic discourses” in music education. Rounding out this issue are two book reviews: Nasim Niknafs’ review of Lauren Richerme’s Complicating, Considering, and Connecting Music Education (Indiana University Press, 2020) and Martin Berger’s review of Juliet Hess’s Music Education for Social Change—Constructing an Activist Music Education (Routledge, 2019). [End Page 110] Estelle R. Jorgensen Yarmouth Port, MA Copyright © 2022 The Trustees of Indiana University

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)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.768
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0080.004
Open science0.0020.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.2320.167

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 head0.059
GPT teacher head0.290
Teacher spread0.231 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2022
Admission routes1
Has abstractyes

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