Is Major Minor? The Relationship Between Music Major Status and a Measure of Musical Sophistication.

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Title: Is Major Minor? The Relationship Between Music Major Status and a Measure of Musical Sophistication.
Authors: Morrison, Steven J. (AUTHOR), Himes, Aaron D. (AUTHOR), Montemayor, Mark (AUTHOR), Springer, D. Gregory (AUTHOR)
Source: Journal of Research in Music Education. Apr2024, Vol. 72 Issue 1, p71-87. 17p.
Subjects: Logistic regression analysis, Musical ability, Musicals, Music education
Abstract: Although music education researchers often utilize music major status as a single-item proxy variable for musician status—and with this designation presume musical competencies or abilities of research participants—there is a lack of research demonstrating links between status as a music major and those assumed competencies. In this study, we compared undergraduate music majors and non-music majors (N = 237) at the group and individual levels using Goldsmiths Musical Sophistication Index (Gold-MSI), a well-established measure of multiple ways in which people report engaging with music. Comparing group means, we found that music majors scored higher than non-music majors on each Gold-MSI subscale. Moderate distribution overlap suggested that these results should be considered cautiously. A logistic regression analysis further suggested the complexity of using music major status as a single-item measure, given that music major status was only strongly predicted by the musical training subscale. Measures such as Gold-MSI may provide a viable and psychometrically sound way of determining musical sophistication that will allow more granular and refined analyses of studies relating to musical competencies. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Research in Music Education is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Musical+ability%22">Musical ability</searchLink><br /><searchLink fieldCode="DE" term="%22Musicals%22">Musicals</searchLink><br /><searchLink fieldCode="DE" term="%22Music+education%22">Music education</searchLink>
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  Data: Although music education researchers often utilize music major status as a single-item proxy variable for musician status—and with this designation presume musical competencies or abilities of research participants—there is a lack of research demonstrating links between status as a music major and those assumed competencies. In this study, we compared undergraduate music majors and non-music majors (N = 237) at the group and individual levels using Goldsmiths Musical Sophistication Index (Gold-MSI), a well-established measure of multiple ways in which people report engaging with music. Comparing group means, we found that music majors scored higher than non-music majors on each Gold-MSI subscale. Moderate distribution overlap suggested that these results should be considered cautiously. A logistic regression analysis further suggested the complexity of using music major status as a single-item measure, given that music major status was only strongly predicted by the musical training subscale. Measures such as Gold-MSI may provide a viable and psychometrically sound way of determining musical sophistication that will allow more granular and refined analyses of studies relating to musical competencies. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Research in Music Education is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Apr2024
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