Representation matters: Developing a Canadian BIPOC composers dataset for music collection evaluation and development

• Main Author: Doi, Carolyn
• Format: Conference Object
• Language: English
• Published: 2022
• Subjects: music collections; inclusive collections; Canada; Metis
• Online Access: https://hdl.handle.net/10388/14246

Peer Reviewed The music profession and industry, especially in traditions of western art music, is marked noticeably by a lack of compositions by Black, Indigenous and People of Colour (BIPOC). This lack of representation is just one of the many effects of generations of colonization, systematic exclusion, bias, and racism. There are numerous consequences to curating music library collections that continue to exclude BIPOC composers and artists, most notably giving the impression that such individuals do not exist or that their works are not worthy of inclusion. This potentially leads to a ripple effect whereby it becomes harder to program music by BIPOC composers, teach it, and write about it. This presentation describes the process and development of a dataset of BIPOC Composers with a connection to Canada, a project undertaken at the University of Saskatchewan (Treaty Six Territory and Homeland of the Metis, Saskatoon SK, Canada) through the work of the University of British Columbia School of Information Professional Experience Program. This project aimed to identify composers who identify as BIPOC and Canadian, or who identify as BIPOC and are based in what is now known as Canada. The project’s end goal was evaluating BIPOC representation in the University of Saskatchewan Libraries music collections, and ultimately filling collection gaps where needed. The dataset primarily serves as a tool for internal collection assessment but will be published and preserved in an open format for others who may be doing similar work. We will discuss the challenges associated with identifying BIPOC composers, especially in a Canadian context, and explore some of the ethical considerations when attempting to classify professionals using markers such as ethnicity or nationality.