It’s no secret that online music streaming has been changing the game for Canadian artists, and with even more avenues for artists to self-release, self-manage, and self-promote, you can't ignore the impact services like Spotify and Apple Music have been having on the way listeners get our daily music fix. While we can simply hit shuffle on Spotify's Discover Weekly Playlists, artists can reach wider audiences and theoretically “make it big” from streaming without having to hit the pavement and sell CDs at their local house shows. But if we want to truly understand the way online streaming affects artists beyond what is advertised to us, we have to start asking the right questions and poking around in some data.
Data feminism is the framework this study rests on. Simply put, from Catherine D'Ignazio and Lauren F. Klein’s text titled Data Feminism, it’s a “new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism”. “Intersectionality”, a term coined by Kimberlé Crenshaw in 1989, is used to describe the way different people’s identities overlap. From a Time article, Crenshaw describes intersectional feminism as “a prism, for seeing the way in which various forms of inequality often operate together and exacerbate each other”. In the first chapter of their book, D’Ignazio and Klein explain how data science, while powerful, is power typically held by white, able-bodied, cis, straight men. Data feminists believe that these structures that were created by and benefit those who hold the most power, can and must be challenged by applying intersectional feminist thought to our analyses. So, data feminism is a way for data scientists (or anyone interested in data), to challenge the way they collect, analyze, and visualize their data, to represent those who are most affected and uplift those who know the domain best from experience.
The music industry by nature has been an incredibly difficult domain to make a full-time income from, and very few musicians truly do. However, streaming has been steadily dominating the industry and offering some musicians a chance to rise with it. From the Government of Canada’s 2021 Study of the economic impacts of music streaming on the Canadian music industry, a 2019 figure shows the distribution of Canadian dollars among rights shareholders in the music creation and distribution process. Notably but not surprisingly, record labels still hold over half the distribution. David Arditi in his book Getting Signed details the level of power that labels hold over the dream of getting big in music; actively pushing and maintaining the dogma that to be successful a band has to get a record deal and sign over their rights.
And to some extent that remains true, but independent arts like Fanclubwallet, an indie rock group based right here in Ottawa, have seen great success using online streaming to their advantage during the Covid-19 pandemic. Pre-signing to AWAL (a British music distribution company owned by Sony) without in-person shows, interviews, tours, or merch tables, Fanclubwallet launched their project, which has now amassed over 299,000 followers on Spotify, and over 6 million plays on their top song Car Crash in G Major. Success stories like this can go a long way to show how powerful self-distribution can be in the digital streaming age, but is this story the same for the other 37,000+ musicians in Canada? Surely not, but why? Who are those being left behind and what are their stories? We’d be here for a while if we wanted to investigate every avenue that leads to success in the music industry, so instead I propose we look at the following question: how can we use data to better understand the Canadian music industry in terms of relationships between representation, documentation, and fan-engagement?
Before we jump into the data, let’s briefly take a time hop back to see how far we’ve come with music distribution.
With our data now positioned in present-day streaming conditions, we can move on to our analysis of the over 11,000 artists identified as Canadian in Chartmetric’s dataset. We will be looking at scatter plots comparing various variables that show trends in underrepresentation, as well as draw our attention to further areas of research. I will also then lead us into a short discussion of some individual artists which have both helped me to guide my research, and provide perspective as to who these numbers represent.