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Record W2892950359 · doi:10.1177/1029864918802331

Music and cultural prejudice reduction: A review

2018· review· en· W2892950359 on OpenAlexaff
Dave Miranda, Patrick Gaudreau

Bibliographic record

VenueMusicae Scientiae · 2018
Typereview
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPrejudice (legal term)PsychologySocial psychologyActive listeningHarmony (color)EmpathyRepertoireCommunication

Abstract

fetched live from OpenAlex

Music is often believed to be a universal cultural language that may bring different people together, in harmony. In this article, we review studies that examined interrelations between music and prejudice reduction during youth development. More specifically, our aim is to reflect on potential circumstances under which music listening and music making reduce cultural prejudice in childhood, adolescence, and emerging adulthood. We argue that this research theme is important but understudied. Nonetheless, the rare published empirical studies that we found ( N = 13) cover a broad repertoire of research methods and outcomes that point to pertinent research directions for cultural attitude change, intergroup processes, positive intergroup contact, and empathy. Overall, although more research is needed, these preliminary findings suggest that music may have some potential to reduce cultural prejudice during youth development.

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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.156
GPT teacher head0.447
Teacher spread0.292 · 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
GenreReview

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

Citations13
Published2018
Admission routes1
Has abstractyes

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