Incorporating Underrepresented Populations in Teaching and Research

In this post, the Write Where It Hurts editorial team reflects on their experience advocating strategies for teaching to and about marginalized populations often left out of mainstream educational materials, research protocols, and data sets (see our recently published Teaching Sociology article on this topic here) in hopes of facilitating dialogue about the incorporation of marginalized and otherwise underrepresented populations in teaching and research.

As people who belong to, write about, teach, study, and engage in advocacy related to varied populations marginalized or otherwise often left out of mainstream education and scholarship (i.e., donor conceived people, adopted people, transgender and non-binary people, people managing chronic physical and / or mental atypical experiences, etc.), we have become intimately aware of the limitations or missing elements within much existing scientific data and educational resources. At the same time, we know all too well the structural and ideological barriers that slow alteration and revision of existing educational rituals, traditions, and structural patterns in concrete settings. As we did in our recently published Teaching Sociology article focused on strategies for inclusive teaching about gender via the use of survey data that often does not explicitly measure the gender diversity of our shared world, we would like to encourage our colleagues to consider strategies for overcoming existing structural and ideological traditions in hopes of continuing dialogue about methods for creating greater diversity and inclusivity within and beyond scholarly and educational materials.

As we note in our recent article, many data sets called “representative” and used to make far-reaching claims often do not contain and / or do not explicitly measure people like us. If, for example, Xan seeks to learn about social patterns related to donor conceived or agender people, such data sets offer no answers despite the use of such data to “represent” national or other whole populations. Likewise, if J seeks to learn about the experiences of transgender, adopted, or sexually fluid people, all ze will learn from data is that such people are not part of the representation of this society. Similarly, if Lain seeks to ascertain attitudes concerning or held by genderqueer and / or bisexual people, most data sets called “representative” will only offer a “representation” wherein such groups do not exist in any identifiable manner. Despite these “missing” populations, researchers, teachers, and advocates will often utilize these sets to make claims about, for example, families, gender, and sexualities that – we would guess unintentionally – ultimately reproduce existing power structures as well as the marginalization of the groups left out of the official representation contained in the data. In fact, we can see similar problems for other marginalized groups including but not limited to homeless people, neuro-atypical people, and multi and inter racial people despite the use of such data to make claims about housing, mental and physical health, and racial dynamics on a regular basis.

Alongside growing recognition of issues with calling limited collections of people and measurements “representative,” we have heard some advocate doing away with these data sets while establishing more inclusive and diverse forms of data collection, measurement, and sampling. Doing so, however, would require massive changes structurally, ideologically, and institutionally, which will likely take much time, debate, and discussion to accomplish. At the same time, we have heard others advocate for maintaining existing practices or rituals while seeking to explain away the limitations or problems with existing data collection, measurement, and coding practices. Doing so, however, would require accepting the ongoing marginalization and erasure of many sections of the population from official representations. In our article, we propose a middle ground between these two extremes wherein we utilize the existing limitations to illustrate important patterns, power dynamics, and structural issues in contemporary society while continuing to push for revisions in existing data collection, measurement and sampling procedures and encouraging scholars, teachers, and others to talk about such data sets in more inclusive ways within publications and classrooms.

With this information in mind, we invite dialogue, commentary and discussion on strategies for inclusive teaching with existing data limitations and issues. Whether one seeks to join this conversation on this site or in relation to our call in Teaching Sociology or in any other space, we invite and appreciate other educators’ perspectives on these matters. To this end, ask yourself what do we say to unrepresented populations when we call data sources devoid of their presence or measurement representative of our world? What institutional and structural steps might we need to take to make our data sources and educational materials more inclusive of marginalized, underrepresented, and otherwise “missing” populations? Why do we push so hard for generalizations instead of seeking to empirically map the complexities, nuances, and diversity of our shared world, and is this pursuit of “representative” or “generalizable” claims worth the potential negative effects such practices may have on marginalized populations? While we will not pretend to have some “right” or “absolute” answers to these questions, our experiences to date within and beyond classrooms tell us these questions might be incredibly important and useful in many ways. Thus, we encourage members of our intellectual and activist communities to engage openly in these (admittedly challenging) conversations in order to move us closer to truly understanding the complexities of our social world and challenging the inequalities that exist within it.

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