JOURNAL ARTICLE
The (Un)popular Brass: Evidence from Czechia, Switzerland and Zimbabwe.
Published In: Journal of World Popular Music, 2025, v. 12, n. 1. P. 91 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Chapuis, Yves; Daniel, Ondřej; Machek, Jakub; Magwati, Phineas 3 of 3
Abstract
This article investigates the (un)popularity of brass bands in Zimbabwe, Switzerland, and Czechia through a comparative transnational lens, highlighting how distinct historical, cultural, and institutional contexts shape their current status. In Zimbabwe, brass music remains largely confined to military and church institutions, hindered by colonial legacies, limited incorporation of local musical styles, high instrument costs, and gender disparities, preventing its integration into the broader popular music scene. Swiss brass bands, while widespread and historically linked to civic identity, face significant membership decline due to perceptions of being outdated and militaristic; however, innovative groups like the Unique Horns demonstrate potential revitalization through modern repertoires and rebranding. In Czechia, brass bands, once popular and associated with national identity, have become marginalized due to their association with rural, socialist-era traditions and resistance from younger, urban audiences, with limited crossover into contemporary popular music despite some experimental projects. Across all three countries, challenges include balancing the participatory, community-oriented ethos of brass bands with evolving musical tastes, addressing gender inclusivity, and adapting to changing cultural dynamics to ensure sustainability and relevance.
Additional Information
- Source:Journal of World Popular Music. 2025/01, Vol. 12, Issue 1, p91
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2025
- ISSN:2052-4900
- DOI:10.1558/jwpm.33424
- Accession Number:186522945
- Copyright Statement:Copyright of Journal of World Popular Music is the property of Equinox Publishing Group 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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