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Record W3169277397 · doi:10.1177/21676968211014659

“Finding my Blackness, Finding my Rhythm”: Music and Identity Development in African, Caribbean, and Black Emerging Adults

2021· article· en· W3169277397 on OpenAlexafffundabout
Rachelle C. Myrie, Andrea Breen, Lynda M. Ashbourne

Bibliographic record

VenueEmerging Adulthood · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRhythmIdentity (music)PsychologyRace (biology)Developmental psychologyGender studiesSociologyAestheticsArt

Abstract

fetched live from OpenAlex

This study examines how music functions in relation to identity development for African-, Caribbean- and Black-identified emerging adults who have immigrated to Canada. Eleven ACB-identified emerging adults, recruited from music schools, community, and student organizations took part in semi-structured interviews adapted from McAdams' Life Story Interview protocol to focus on music practices and memories. Thematic Analyses results suggest that transitioning to life in Canada necessitated learning new meanings of being and "becoming" Black. Participants described the influence of music on negotiating identity in a Canadian context. They described using music to resist racist and hegemonic narratives of Canadian Black identity, to connect to and celebrate their embodied Black identities, and establish self-continuity and coherence across histories and generations to connect with spiritual memories, land, and ancestors. We conclude by suggesting implications of this work for practice and developing research methodologies that resist whiteness.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.210
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.238
Teacher spread0.212 · 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

Citations10
Published2021
Admission routes3
Has abstractyes

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