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Record W2610543371 · doi:10.1177/0255761417703783

Our culture is who we are! “Rescuing” Grenadian identity through musicking and music education

2017· article· en· W2610543371 on OpenAlexaff
Danielle Sirek

Bibliographic record

VenueInternational Journal of Music Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCaribbean history, culture, and politics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsEthnomusicologyIdentity (music)SociologyContext (archaeology)AestheticsMusicalMusicologyMusic educationGender studiesVisual artsPedagogyHistoryArt

Abstract

fetched live from OpenAlex

In this article I explore the relationships between identities and musicking in Grenada, West Indies, taking into account the understandings of community and nationhood that foreground and inform identity discourse in the Grenadian context. Through the dual lenses of music education and ethnomusicology, I analyze musicking and music education initiatives intended to “rescue” Grenadian identity and Grenadian values as articulated by an older generation of Grenadians and by governmental agencies. I argue that musicking in Grenada is intertwined with identity in complex ways, and that there is a perceived lack of transmission of folk musicking practices whose consequences extend well beyond losing musical traditions. This article illuminates conflicts of identity, the deep sense of loss of “who we are” that has occurred in Grenadian society in recent times, and controversies of music transmission.

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)0.002
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.022
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.066
GPT teacher head0.391
Teacher spread0.324 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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