Redlining, Equity, and Open Educational Resources
Contributed by: Dr. Rajiv Jhangiang, Pro Tem Vice Provost, Teaching & Learning & Associate Vice Provost, Open Education at Kwantlen Polytechnic University
On the surface, the argument for Open Educational Resources (OER) as a force for equity is straightforward and powerful: Ensure free, immediate, and permanent access to educational resources and disadvantaged students will benefit, in both economic and educational terms.
However, alongside this great promise lies several pitfalls, including the assumption that all learners enjoy reliable access to the internet and the necessary technology to avail of free digital resources. This digital divide is a stark reminder that, unless we approach the work of open education through a critical lens, we risk perpetrating harm with the best of intentions, exacerbating the very inequity that we seek to redress.
Dispiritingly, these inequities are often deliberately created and reinforced, as in the case of what Chris Gilliard and Hugh Culik refer to as “digital redlining” (2016):
“Digital redlining is not a renaming of the digital divide. It is a different thing, a set of education policies, investment decisions, and IT practices that actively create and maintain class boundaries through strictures that discriminate against specific groups. The digital divide is a noun; it is the consequence of many forces. In contrast, digital redlining is a verb, the "doing" of difference, a "doing" whose consequences reinforce existing class structures.”
Another form of redlining, what Safiya Noble refers to as technological redlining, concerns the ways in which data is used to profile those from marginalised groups, including “the racial- and gender-based profiling enacted by the algorithms that run Google Search” (Garrett, 2019, p. 1). Consider, for example, that if you search for an image of a professor or a doctor, Google will prioritise images of white males instead of women or BIPOC in its search results. And as bias amplifies bias, Google’s decidedly non-neutral algorithm amplifies the lack of diversity in stock photos and sends a message about who belongs in those professions, and about whose experiences are valid and valued.
Building on these ideas, I wrote about yet another form of exclusion that is masked by the pretence of neutrality: implicit creative redlining. In this case I refer to an effect of the open education movement’s continual reliance on uncompensated (or at least severely under-compensated) labour. Specifically, if we continue to rely on the generosity and time of volunteer educators to create OER, we can reasonably foresee that educators who enjoy more privilege (e.g., tenured faculty who can afford to forgo the extra income) will be over-represented in collections of OER and, further, that the experiences and world-views associated with that privilege will predominate the texts of available OER. While we may not immediately think of this as a big problem (surely generosity is a good thing!), it is yet another example of the subtle ways in which biases are amplified and harm done with the very best of intentions.
This systemic issue—of equitable access to OER creation, brings to mind the difference the distinction between ameliorative and transformative responses to injustice discussed by Cheryl Hodgkinson-Williams and Henry Trotter (2018) in their important article about a social justice framework for OER. This reminds us that while the use of OER might widen access to education, by itself this does not equate to parity of participation for those farthest from justice.
As Okuno (2018) puts it:
“Equity isn’t for all. Equity is for those farthest from justice, and if we are working towards true equity those farthest from justice can define for themselves what they need to be whole, healthy, and in just relations with others.”
References
Bali, M., Cronin, C., Czerniewicz, L., DeRosa, R., & Jhangiani, R. S. (Eds). (2020). Open at the margins: Critical perspectives on open education. Rebus Community. Retrieved from: https://press.rebus.community/openatthemargins/
Crawford, S. (2016). When Comcast’s business as usual turns out to limit minority access. Wired. Retrieved from: https://www.wired.com/2016/02/when-comcasts-business-as-usual-turns-out-to-limit-minority-access/
Garrett, Y. C. (2019). Review of Algorithms of Oppression: How Search Engines Reinforce Racism. Journal of Contemporary Archival Studies, 6, Article 8. Retrieved from: https://elischolar.library.yale.edu/jcas/vol6/iss1/8
Gilliard, C. & Culik, H. (2016, May 24). Digital redlining, access, and privacy [Blog post]. Retrieved from https://www.commonsense.org/education/privacy/blog/digital-redlining-access-privacy
Hodgkinson-Williams, C. A., & Trotter, H. (2018). A Social Justice Framework for Understanding Open Educational Resources and Practices in the Global South. Journal of Learning for Development , 5(3). Retrieved from https://jl4d.org/index.php/ejl4d/article/view/312
Jhangiani, R. S. (2018, April 6). OER, equity, and implicit creative redlining [Blog post]. Retrieved from https://thatpsychprof.com/oer-equity-and-implicit-creative-redlining/
Noble, S. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.
Okuno, E. (2018). Equity doesn’t mean all. FakeQuity. Retrieved from: https://fakequity.com/2018/11/16/equity-doesnt-mean-all/