Representation in Corpus Studies of Music

Commentary on Shea's (2022) "A Demographic Sampling Model and Database for Addressing Racial, Ethnic, and Gender Bias in Popular-music Empirical Research"

Bibliographic Data

ID21749127
AuthorsTrevor De Clercq (0000-0002-0718-9526, Middle Tennessee State University, corresponding author)
Year2024
Volume18
Issue2
Pages175-180
Publication date2024-06-07
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEmpirical Musicology Review (JOURNAL)
Journal identifiersISSN: 1559-5749 • E-ISSN: 1559-5749
PublisherThe Ohio State University Libraries (PUBLISHER • US)
DOI10.18061/emr.v18i2.9726
OpenAlexW4399421153
LanguageEN
References cited7

This commentary responds to the article by Nicholas Shea in Vol. 17(1) of this journal, which offers a method to encode the demographic information of the artists in a corpus of popular music and then describes a resampling procedure to create a new corpus based on specific demographic targets. I argue that attempts to diversify the demographic distribution of popular music corpora should occur not at the sampling stage but instead at a prior stage when the researcher is determining the musical style or era to study. Once this musical style or era has been determined, empirical principles oblige the researcher to create a corpus that faithfully represents the statistical population

Art · Ethnic group · Linguistics · Musical · Political science · Popular music · Population · Resampling · Sociology · Visual arts · Anthropology · Computational and Text Analysis Methods · Computer Science · Demography · Diverse Musicological Studies · Music History and Culture · Psychology · Artificial Intelligence

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