This guide is for students, staff, and faculty who are incorporating an anti-racist lens at all stages of the research life cycle.

How to use this guide

This guide was developed in response to librarians fielding multiple requests from UMN researchers looking to incorporate anti-racism into their research practices. Conducting research through an anti-racism lens is a long-term and ongoing process and must be considered as part of a complex system which oppresses people and groups in multifaceted ways (i.e., classism, ethnocentrism, capitalism, casteism, etc.). While some disciplines, mainly in the humanities and social sciences, have mitigated racism through a depth of understanding of critical race theory, others have not. If you're new to this work, consult the Related Guides and Resources call-out box in the left pane for reading lists to help form a baseline understanding. You can also reach out to your subject librarian for individualized help locating anti-racism learning experiences. This guide shares racist research systems and practices, followed by resources for mitigating those problematic systems and practices, but we acknowledge that this is not a solution to the issues of racism embedded in research.

De-center whiteness in primary research

We are often taught that Black, Indigenous, and People of Color (BIPOC) distrust science and refuse participation in studies because they have experienced research atrocities (e.g. UMN land grabTuskegee Study, forced sterilization), but this shifts blame to those communities and ignores current medical racism (e.g., pharmacy deserts, Dr. Susan Moore’s death due to COVID). This notion distracts from the fact that researchers have often left communities of color out of research due to white centering. The strategies below are designed to decenter whiteness, think inclusively, and build trust between researcher and communities of color when conducting primary research. 

 

Evaluate whether your research is WEIRD

Most published research is not representative of the majority of populations because it was conducted with WEIRD societies:  Western, Educated, Industrialized, Rich, Democratic. WEIRD can be applied to behavioral research based on cultural, environmental, and socioeconomic factors, but has also been critiqued for not acknowledging values and research practices informed by whiteness, not including race and ethnicity, and not addressing diversification of contexts as well as samples. Additionally, the research community can take steps to welcome non-WEIRD researchers into mainstream literature.  

When developing a research design, ask yourself how you can decenter the status quo characteristics described by WEIRD. 

  1. As a researcher, are you making an effort to bridge the cultural gaps between researcher(s) and communities of color?
  2. To what extent is your research question shaped by the needs and priorities of marginalized people, particularly those who will be most directly affected by the research?
  3. Are members of that community involved in the creation process and being compensated for their work?
  4. Are your promotional materials and communications in the language(s) and the medium (i.e., email, poster, text) that your target populations can understand and engage with?
  5. Are you actively engaging the communities being researched to ensure an appropriate and meaningful outcome? 

 

Recruit BIPOC people and communities for inclusion in studies

Funding agencies are implementing policies that require diversity in study recruitment (e.g., National Institutes of Health Inclusion of Women and Minorities as Participants in Research Involving Human Subjects), particularly for clinical trials. The following studies highlight strategies for decentering whiteness in clinical trial recruitment (note that the use of the term "minorities" is still white centering):

 

Utilize research methods and practices that decenter whiteness

A Toolkit for Centering Racial Equity Throughout Data Integration, by Actionable Intelligence for Social Policy, helps researchers embed questions of racial equity throughout the data life cycle: planning, data collection, data access, algorithms/use of statistical tools, data analysis, and reporting and dissemination. It includes exercises and examples, and encourages a community engaged framework. See the excerpt below:

 

For more information on decentering whiteness in primary research, see:

De-center whiteness in secondary research

Secondary research involves the summary, collation, and/or synthesis of existing data or research, and often involves deep dives into existing literature. The strategies below are designed to de-center whiteness, think inclusively, and build trust between researcher and communities of color when conducting secondary research. Mitigate this problematic practice:

 

Evaluate whether your research is WEIRD

Henrich, Heine, and Norenzayan (link to article below) propose that most published research is not representative of the majority of populations because it was conducted with WEIRD societies.

  • Western
  • Educated
  • Industrialized
  • Rich
  • Democratic

The WEIRD acronym can be applied to behavioral research based on cultural, environmental, and socioeconomic factors, but first a few criticisms of the acronym should be understood. WEIRD has been critiqued for not acknowledging values and research practices informed by whiteness. Clancy and Davis (link to article below) write that acknowledging whiteness is needed to "push for a more inclusive and scientifically rigorous future." Syed and Kathawalla (link to article below) critique the WEIRD acronym for not including race and ethnicity and encourage skepticism for convenient acronyms. Others have written about the need to diversify contexts as well as samples (link to article below). Additionally, more focus could and should be on diversifying the research community and overcoming "the invisibility of non-WEIRD scientists" (link to article below). 

When developing a literature search, ask yourself how you can de-center the status quo characteristics described by WEIRD. 

  1. Who are the authors and the organizations which supported (financially or otherwise) the work?
  2.  What are the backgrounds and identities of the authors?
  3. How many parts of the WEIRD acronym can you check off when you read about the populations that were studied? 

 

Follow the praxis put forth by the Cite Black Women Collective

  1. Read Black women's work
  2. Integrate Black women into the CORE of your syllabus (in life & in the classroom)
  3. Acknowledge Black women's intellectual production 
  4. Make space for Black women to speak 
  5. ​Give Black women the space and time to breathe

These principles from the Cite Black Women Collectivewhich aim to amplify the frequently marginalized voices of Black women, can be applied to all Black, Indigenous, and People of Color (BIPOC).

 

Use inclusive citation practices

Craven (2021) studied the Cite Black Women movement from the perspective of the field of Anthropology and wrote about antiracist citational politics and praxis. Craven gave the following (and more) suggestions.

  • Look online to see how author's self-identify
  • Make a spreadsheet to identify your own citation trends
  • Be explicit that citing black women is not an add-on. Cite because their scholarship is valuable and central
  • Read promiscuously, critically, and counter the observed inequities
  • Look outside of academic books and articles (because of the history of Black women's scholarship being excluded from those venues)

 

Consult research found in non-Western journals

The Journals Online Project - aimed at providing increased visibility, accessibility, and quality of peer-reviewed journals published in developing countries so that the research outputs produced in these countries can be found, shared, and used more effectively - was launched by the International Network for Advancing Science and Policy (INASP) in response to voices not heard, wasted talent, and unused research.

 

Search for existing collections

Collections of BIPOC-centered resources may already exist in your discipline, and a thorough Google search should lead you to them. For example, the Diverse BookFinder is a database of picture books published since 2002 featuring BIPOC characters that is useful for education disciplines, including early childhood education, elementary education, English education, ESOL/bilingual education, and reading and literacy education programs.

 

For more information on de-centering whiteness in secondary research, see:

Acknowledge that data is not objective

Data (even quantitative data) is not neutral, objective, or free of bias. Humans are involved in all aspects of data creation - we decide what data gets collected and from whom, how that data is analyzed, and where and how that data is presented or shared. Mitigate this problematic practice:

 

Learn the racist history of statistics

Francis Galton, Karl Pearson, and Ronald Fisher are three of the statisticians who established the fundamental basis and techniques of modern statistics, and they were all eugenicists. Daniel Cleather, in Is statistics racist?, presents us with the idea that "The tools that we use on a day to day basis to interrogate data and understand the world, were developed by white supremacists for the express purpose of demonstrating that white men are better than other people." There is significant discourse on the racist history of statistics and data collection methodology, many of which are linked below in the Additional reading section. It's important to understand the history of a methodology relied on so heavily by researchers, and examine how statistics relies on underlying assumptions turned into real world interpretations (Cleather; Sullivan).

 

Put the "human" back in human participant research

While we cannot scrap statistics as a data analysis method, there may be other ways to center the data we collect on the humans who provided that data, rather than just the numbers themselves. Gillborn, Warmington, & Demack note that "voice and insight are vital: data cannot 'speak for itself' and critical analyses should be informed by the experiential knowledge of marginalized groups." See how others are doing this:

  • Cleather proposes causal modeling
  • Gerido applies a #QuantCrit lens to past medical research with Black women
  • Sablan developed a survey combining critical race theory and quantitative methods
  • Sullivan critiques educational policy development through critical race theory and critical policy analysis
  • Fully engage research participants in the entire research process following the CARE principles for Indigenous data governance

 

Utilize a data equity framework

We All Count’s Data Equity Framework claims to reduce information overload and missed steps; be more democratic, efficient, and comprehensive; make unconscious decisions explicit; and apply tools to data stages that ultimately lead to better data science. This framework is perhaps a more accessible equal to A Toolkit for Centering Racial Equity Throughout Data Integration.

 

Present data visualizations to make data accessible

Data visualizations summarize the important and interesting research findings - identifying patterns, enhancing comprehension, and broadening communication for big takeaways. They can be presented via infographics, executive summaries, pamphlets, etc. and are easily made accessible to not only policymakers and the public, but also the people and communities being studied.

 

For more information on bias in data, see:

Acknowledge that scholarly publishing is racist

Peer review in the publication process is meant to ensure rigid methodology and low bias in what gets published, but that system is flawed. According to the Association for Psychological Science, Murray et al., and Lee & Low Books, most editors are white and/or from Western nations (links to articles below). Lee & Low Books and Wu report that 66-80% of peer reviewers are also white (links to articles below). These gatekeepers control the authorship and content of scholarly journals and books, which ultimately favor white, Western authors - even in works focused on race - according to Boyd, Lindo, Weeks, & McLemore; Wu; Williams; Murray et al.; Heath-Stout; Salinas, and the Association for Psychological Science (links to articles below). Mitigate this problematic system:

 

Look outside peer reviewed literature for perspectives from marginalized voices and groups

Researchers should look at the gray literature for perspectives from Black, Indigenous, and People of Color (BIPOC) communities. Gray literature refers to works published outside traditional methods, and the easiest way to access it is through Google. There is no perfect solution, and many strategies will be attempted before useful information is found. Google search tips:

  • Keep in mind that Google itself uses biased algorithms, so searching must be specific and incorporate various terms to represent one concept.
  • The following example shows one possible search strategy for housing discrimination: "marginalized voices in housing."
  • You can utilize Boolean operators and other search functionality as you do in literature databases. For example: (marginalized OR underrepresented) AND (hous* OR rent*). See more Google search refinement tips.
  • You might also try using keywords of interest plus "site:org" which tells a search engine that you are looking for an organization rather than a company or government site. Keep in mind that prior to 2003, ".org" was reserved for non-profit organizations, but since then this top-level domain has been obtainable for other purposes, including private companies.

Archives also feature marginalized voices through collections of oral histories, documents, and interviews. Where to start:

 

Search for BIPOC scholars through professional organizations

It is not yet possible to search for an author's race in literature databases - the following is a flawed, yet workable, solution to that problem: 

  • Search Google for organizations that represent marginalized groups and search their websites for special interest groups, experts, publications, data, etc. For example, perusing the digital magazine available on the National Society of Black Engineer's website to find leaders in the field.
  • Seek out a networking organization, such as ColorComm, which is an essential organization for women of color in all areas of communications including public relations, advertising print media, broadcast, and more. To look for such groups, use a variety of terms - one might be "research organizations run by people of color."
  • It can be helpful to look for underrepresented speakers at conferences. One example is this interactive tool by Diversify STEM Conferences which has compiled a list of prominent underrepresented researchers across every field of STEM and medicine.
  • Search for biographies that are led by BIPOC non-profits, such as SACNAS, an online archive of first-person stories by and about Chicano/Hispanic and Native American scientists with advanced degrees in science.

 

Utilize smaller, lesser known databases 

The list below is not exhaustive, but it features a handful of indexes focused on BIPOC issues as well as a selection of local BIPOC-led news outlets that - by nature - feature scholars who are BIPOC:

 

Incorporate community-engagement principles into research dissemination
The Community-Centered Dissemination Toolkit recommends that researchers proactively and mindfully engaging with communities to develop effective dissemination plans. Their Resource Directory includes individuals and groups that could help with creating and sharing community-focused outputs.

 

Publish openly
Some scholarly research resides behind paywalls. Alternatively, publishing open access means removing a barrier for the people and populations being studied.

 

Publish in journals dedicated to anti-racism

Some journals have made anti-racism pledges promising to diversify their editorial teams and authorship. Publishing in these journals, when applicable to your work, shows your support for their efforts toward anti-oppressive practices.

  1. Search for an anti-racism pledge or statement (example from Written Communication)
  2. Conduct a broader search for reactions/responses to that pledge (example from Journal of Occupational Science)
  3. Look at the editorial board make-up
  4. Browse journal website for anti-racism language
  5. Contact editor-in-chief to ask about their commitment to anti-racism (specific actions they're taking)

 

Engage in anti-racist peer review

Consult Anti-racist scholarly reviewing practices: a heuristic for editors, reviewers, and authors which recommends prioritizing humanity over production, transparency, and valuing labor.

 

For more information on bias in scholarly publication, see: 

Acknowledge that search algorithms are racist

Algorithms existed pre-internet, but in today's world, they serve as a sequence of instructions to perform computation. There is evidence that algorithms - even those in academic databases - are sometimes racist. Proprietary algorithms (e.g., Google) are customized to users and lack transparency, making it unclear why search results vary from person to person. For this reason alone, you may be missing important information unless you know to search specifically for it. Mitigate this problematic system:

 

Use inclusive search terminology on topics of racism

Terminology used to describe race and ethnicity have evolved over time. This variability in language can make searching comprehensively for literature on race/ethnicity difficult. If you are performing a comprehensive literature search (e.g., systematic review, scoping review, historical perspective), you must include outdated terminology in your search strategy or check to see if old terminology has been included in the databases’ subject headings (e.g., illegal aliens). And other times, you will need to use terms that were common from the preferred date range of the research.

This health sciences example from Ovid MEDLINE shows that older terminology from 1963 forward has been added to the new subject heading "African Americans."

Searching for literature about racism requires a sophisticated search strategy to not only include "racism," but also biases and discrimination against specific races and ethnicities. The example below is a search strategy for racism in Ovid MEDLINE. It uses both MeSH terms and keywords for racism, and also MeSH terms and keywords for bias, discrimination, stigma, stereotyping, and prejudice grouped with MeSH terms and keywords for specific races and ethnicities. Remember that terms evolve. For example, BIPOC (Black, Indigenous, and People of Color) and BBIPOC (Black, Brown, Indigenous, and People of Color) should be added to the racism search example below, which was only constructed a year ago.

 

For more information on bias in algorithms, see: 

Acknowledge that library cataloging systems are racist

When incorporating anti-racism into research, it’s important to acknowledge the context in which information has been shared through library systems. Dewey Decimal, the Library of Congress, and smaller discipline-specific cataloging approaches were designed in a racist and white-centered system. In the case of the Library of Congress, the classification is built based on existing holdings and United States publishing output. This "literary warrant," as it is termed, is a reflection of the white male dominance of American culture and publishing since its founding. Library cataloging systems have always evolved as terminology and attitudes change, but the process can be slow and is often inadequate to meet the needs of all researchers. As new disciplines emerge, classifications can be expanded to accommodate them.

Know that librarians are fighting for change

As a researcher, it is important to be aware of this information. Know that librarians are advocating for anti-racist cataloging, a long-term process. Some libraries have opportunities for users to report racist terminology in catalogs. Our Archives and Special Collections has guidance for notifying library staff about racist language found in descriptions of materials.

 

For more information on bias in cataloging, see: 

Who we are

This guide was developed by two librarians, Shanda Hunt and Amy Riegelman, and Soph Myers-Kelley, a library intern, from the University of Minnesota (UMN), - all white-identifying - with invited input from all other UMN librarians. We approached this project from the perspective of library staff at a large research institution within the cultural context of the United States of America. Ours is not the only perspective - perhaps we are not seeing the ways that this guide misses or marginalizes other points of view. We invite you to contact us to share your input for consideration for website content (Email addresses in the left pane).

Last Updated: Sep 15, 2021 1:17 PM