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Data fields may be taking off, but they’re leaving behind minoritized groups. We have a set of recommendations and calls to action detailed below.


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More Public Data.

There are so few publicly available datasets, that we don’t really have a full picture of who is in these programs and who is excluded. Without this data, our efforts to obtain parity in data education are likely to just end up perpetuating systems of inequalities. More data leads to a better understanding of what needs to be done to achieve parity. 

Meanwhile, There Are Datasets Available For Purchase:

Better Course Content.

 Invest in anti-racist pedagogies. Data instruction needs revision to center culturally competent pedagogy, including social context and algorithmic accountability.

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HBCU’s Are Getting It Right!

Historically Black Colleges and Universities have much higher levels of representation for Black men and women in data fields. Yet these institutions are under supported and undervalued.

We know that the student environment fit is very important for student success, so other institutions should look to HBCUs to create a supportive, safe, and welcoming environment for their students and faculty. 

LGBTQ+ and nonbinary data is glaringly absent from the body of research.

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