The question remains: While the total number of women receiving college degrees increases, what hinders the expansion of diversity in the data science field?
implores scientists from all fields to demand interdisciplinary approaches in data science, and to make sure that human perspectives are centered. Aragon intends to increase the number of women in data science by advocating for diversity in STEM, and by dismantling harmful hierarchies and binaries in academia.
Although Aragon now considers herself a data scientist, there was no “data science” or even “computer science” major when she attended college. However, while pursuing her undergraduate degree in mathematics, she received advice from mentors that computer science was too risky to pursue, and guidance that the field could be a ‘fad.’
Today, she realizes the advice she received continues to have relevance for current students, compelling them to doubt their abilities, and holding back the inclusion of diverse voice in data sciences. Women regularly encounter this dichotomy in academia and are more likely to be encouraged to pursue liberal arts as opposed to fields in STEM. Aragon says we should questioninformation that is oversimplified into a binary. In the case of the ‘hard’ versus ‘soft,” she believes science is a continuum, and in the case of all binaries, she believes that they “impose a hierarchy that doesn’t exist.”
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