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Record W7125680781 · doi:10.7202/1122760ar

Canadian Music Studies and/under the Second Trump Presidency

2025· article· en· W7125680781 on OpenAlexvenueaboutno aff
Robin Elliott

Bibliographic record

VenueMUSICultures · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPresidencySovereigntyPoliticsMusicalContext (archaeology)Music educationMusicologyCultural studies

Abstract

fetched live from OpenAlex

This talk explores the evolving landscape of Canadian music studies in the context of intensifying cross-border cultural and political pressures. Drawing upon historical reflections and contemporary developments, the presentation examines how Canadian music scholarship navigates questions of national identity, academic autonomy, and cultural preservation. It considers the influence of dominant U.S.-based institutions and academic societies on Canadian music studies and reflects on the challenges posed by shifting geopolitical dynamics, including threats to Canadian sovereignty and academic freedom. The talk highlights the resilience and diversity of Canadian musical traditions and underscores the importance of sustaining a distinct Canadian musical identity. Through case studies, historical parallels, and current responses from artists and scholars, the talk invites a broader conversation about the role music studies might play in affirming cultural sovereignty and fostering inclusive, forward-looking scholarship.

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)0.005
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: none
Teacher disagreement score0.922
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0230.010
Scholarly communication0.0150.002
Open science0.0010.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0180.001

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 head0.034
GPT teacher head0.227
Teacher spread0.193 · 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 routes2
Has abstractyes

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