Data science can be defined as a multidisciplinary approach to producing insight and solving problems combining statistics, computer science and programming, domain-based knowledge, and data-driven storytelling. Applied at scale to capitalist business use-cases by multinational corporations, data science has produced highly sophisticated, globally integrated systems of real-time planning, organization, and exploitation as exemplified by Amazon or Walmart.
At the outset of the 2020s, the theory and practice of using data science for public good is still in infancy. What might happen if we plugged historical materialism into the domain knowledge slot of the data science model? Can the emergent discipline of data science play a meaningful role in the struggle for socialism in the 21st Century? At this point, there are no easy answers to the question. The aim of this site is to contribute in three ways:
Sharpening criticism of capitalism with data-based approaches and using data storytelling, with emphasis on data visualization, to mobilize that critique.
Serving as an educational resource for those on the left wanting to get started on finding, preparing, and using data in their writing and practice.
Seeking insight into the potential of data science and information technology to inform visions of rationally planned socialist economies and strategies for socialist practice required to achieve them.
I don’t consider myself, at this point in time, to be a practicing data scientist. Rather, I am a sociologist and research analyst with personal and professional interest in the theory and practice of data science and coding. I hope that this site will be useful both for my own self-guided learning and as a resource to readers.
As I am a citizen of the Canadian settler-state, residing in Toronto (Tkaronto) on the the traditional land of the Haudenosaunee, Anishinaabek, the Huron-Wendat, the Seneca, and Mississaugas of the Credit, the content of this site will feature criticism of Canadian settler-capitalism prominently.
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