Select any filter and click on Apply to see results
Table of Contents
Inclusive Research Excellence: Deconstructing the Research Enterprise to Facilitate Responsible STEM Research
Research is formalized curiosity. It is poking and prying with a purpose.
—Zora Neale Hurston
Knowledge can be transformed by shifting paradigms and philosophies, evolving disciplines and practices, emerging data and results, and prevailing theories and methods. Change, whether incremental or revolutionary, is the one construct researchers embrace unequivocally. Yet, as researchers, we also coexist in a contradictory state of mind that resists change. The operation of our intellect is caught up in our personal motivations, biases, emotions, images, and identities. Scholarly cognition is not cold or objective, but hot (Kunda 1999).
Placing Practices Under a Microscope
Our acts of teaching, applying, and disseminating knowledge may sometimes demonstrate this resistance to change. When these practices are placed under the microscope, our discomfort with change may cause us to embrace prevailing knowledge, despite obvious flaws. STEM research, in general, has been influenced by gatekeepers who control what knowledge will be disseminated, created by whom, through what venues, at what pace, and even at what cost. To the public, we celebrate peer review and tout its ethics and objectivity; in private, we discuss how research is undermined by implicit bias and so-called old-boys’ clubs. We have yet to establish ethical norms and standards to address what has become a serious lack of inclusion in STEM epistemology and axiology. This continued oversight accounts for bias and inequity in research outcomes.
Buolamwini (2016) discovered a major problem with facial detection software—the systems could not “see,” or process, faces with darker skin or those with bangs or other hair touching the face. The problem arose from coding and training data sets comprised of biases and, in particular, data sets with faces with a limited range of skin hues, primarily lighter skin. Buolamwini (2016) provides strong support for the need for diversity and inclusion in tech companies and universities. This is more than a moral imperative; it is a technological imperative. In her analysis of technological bias, Wachter-Boettcher (2017) describes technologies with designs that come from minimal cultural competence and inclusion. Technology failures include gender-biased card readers with algorithms that classified women with doctoral degrees as male, causing an incident where a female pediatrician’s card swipes were repeatedly denied for entry into the women’s locker room. Cathy O’Neil (2016) deconstructed recidivism algorithms used by judges and uncovered prejudices built into the algorithms. O’Neil describes how “quantitative” software applications predicted lower probabilities of re-arrest for White males whose risk scores correlated with higher recidivism, while Black males with lower risk scores had higher predicted rates of re-arrest. Because of technological failures like this, we do a grave injustice to those who truly matter: the public we serve. Furthermore, these historical contradictions in STEM are front and center for faculty of color and prospective faculty of color, who view the flaws and biases in scientific practice and the research enterprise as reasons to leave or never enter the profession.
If institutions are truly to be “centers of hope” (Bolman and Gallos 2011, 7) and apply their own power and privilege to produce knowledge, then we need academic leaders who are willing to learn, convey, and act to prepare institutions for more diverse and inclusive approaches to STEM research. Bolman and Gallos emphasize the need for strong academic leaders who will commit to seeing the “same situation in multiple ways and through different lenses” (2011, 13). Building an inclusive research culture needs to be an espoused goal of academic leadership. Academic leadership that understands multiple lenses in research could create an institutional climate with actions, procedures, processes, incentives, and infrastructures that support more inclusive research programs. For example, university research officers could integrate efforts with academic affairs in courses that build students’ strengths in the scientific method and in product and research design in ways that help students challenge prevailing (and often exclusionary) practices. Similarly, funding agencies, which provide significant monetary support and influence, should understand their role in advancing inclusive research as a practice and the impact this support may have on advancing societal benefits for all while avoiding negative consequences for some. In STEM, we are very much in need of a shift in mind-set toward more equitable ways and means to support, conceive, conduct, and disseminate research. Therefore, we offer a call to academic leaders to support inclusive research excellence (IRE).
Bolman and Gallos (2011) use four frames—human resource, structural, symbolic, and political—to describe cognitive schemas in academic leadership (see fig. 1). These frames can be used to engage academic institutions around an IRE model. For instance, a human resource frame values the contributions, talents, and capabilities of researchers within the institution. A political frame focuses on forming connections and relationships to achieve common ground. The symbolic frame may already fit a university that has moved significantly toward a climate of diversity, inclusion, and belonging. This frame would use an existing commitment to inclusion but could integrate research as a natural extension. And the structural frame would build operating models and processes to support collaboration across diverse faculty communities around interdisciplinary problems. The primary question of any stakeholder should be: Why is IRE especially important in STEM?
IRE is grounded in the Association of American Colleges and Universities’ (AAC&U) concept of inclusive excellence. IRE can be defined as systematic discovery that is valid, reliable, culturally responsive, useful, and meaningful for either the broadest range of target groups or explicitly identified target groups. While it overlaps somewhat with inclusive design, IRE is broader and more closely aligned with the AAC&U description of inclusive excellence, which addresses three fundamental needs:
- To broaden a previous definition of diversity and redefine what it means for the academy
- To be inclusive of more technologically focused universities
- To provide a framework to empower faculty, staff, students, and administrators to reform institutional practices, cultures, and climates
AAC&U describes elements composing inclusive excellence to enhance the flexibility of the concept (see fig. 2). Yet, their core message is to integrate excellence in all aspects of the university through actively involving groups whose presence and agency have been overlooked, marginalized, and downplayed. The elements are diversity (presence and representation), inclusion (engagement and social agency), equity (equal access and benefits), and equity-mindedness (active and consistent internalization).
Successful STEM-IRE rests on academic leadership embracing the four pillars in developing institutional research initiatives, infrastructure, and incentives. Such integration might have immediate impacts on research quality and student success, not to mention the equity and fairness of the outcomes (including technological outcomes). Implementation of such standards could help to attract and retain underrepresented minority faculty. It is possible (and, at some point, may be measurable in the traditional academic value system) that institutionalization of STEM-IRE could facilitate research agency and minimize marginalization among underrepresented faculty.
STEM-IRE is about reframing fundamental theories and practices around the activity of research, the process of innovation, and the enterprise of discovery. It includes integrating STEM with other disciplines such as the humanities, social sciences, and arts. STEM-IRE also involves sharing inclusive methods and practices and cultivating an intellectual landscape to advance the nation’s capacity to use its rich and diverse research infrastructure. The intent is to build an inclusive research culture and climate that meaningfully integrates the four pillars to attract, retain, and promote more underrepresented scholars to academia, research, entrepreneurship, innovation, and discovery.
Two common theories frequently applied in human-centered computing, human-computer interaction, and human factors are Bandura’s social cognitive theory and Maslow’s hierarchy of needs. These so-called fundamental theories are given significant value when included in proposals to funding agencies. In 2002, Bandura referred to “contentious dualisms” that pervade the application of social cognition in various cultural contexts. Social cognitive theory is not accurate across all cultures, yet most researchers overgeneralize the theory, measuring concepts such as self-efficacy or individual agency without regard for the myriad cultures in which other types of agency are more important than individual agency.
Bandura is not the first to refer to dualisms that impact how agency operates in the world. The concept of dualism was first referenced as “double consciousness” by W. E. B. Du Bois in 1903. Double consciousness is a sense of having to see oneself through the eyes of those with power in a system of oppression. This need to use a persona emerging from a double consciousness should lead scholars to question how we use or conceptualize design practices, psychometric instruments and models, cases for prototyping, or other activities when designing for users whose demographics and culture-bound lived experiences vary. Research has also shown that Maslow’s hierarchy of needs theory differs to a significant degree among Western-centric individualist cultures and non-Western cultures that are more collectivist (Gambrel and Cianci 2003). This is not surprising given that these theories were developed in universities with predominantly Western, White, and middle-to-upper-class human research subjects. Yet researchers, practitioners, and funding agencies still generalize these theories to all potential users regardless of context, culture, or lived experience.
Simply put, the currency of publication and dissemination, which is fundamental to survival in academia, can be undermined by biases introduced in the theories used to explain phenomena such as the underrepresentation of faculty of color in STEM. For instance, when faculty of color place value on decolonizing research methods or focus on social justice research in science and engineering, their efforts are often devalued and considered substandard (see figs. 3 and 4).
Conclusion and Recommendations
While the pillars present a framework for research to emphasize the importance of inclusion and being equity-minded, it is important to understand what is being challenged and what opportunities result from these challenges. There should be a systematic focus on reversing the damage done by research emerging from exclusionary and privileged perspectives. Reversal means redoing research and ensuring problem conceptualizations, lines of inquiry, methods, and outcomes are considered in the context of inclusivity. It is important to fully question epistemologies and axiologies driving STEM in order to undo some of this damage. Scholarly cultures that welcome these challenges and, for instance, funding agencies that fund such challenges, are key to advancing more inclusive agendas in research.
Recommendations to advance inclusive research excellence have been offered by many researchers in the past three decades with little recognition by the wider research culture. However, recent efforts by professional societies and research sponsors have motivated researchers to pay attention to the role of bias in their research. Chilisa (2012) called for the use of indigenous methods, or methods conducive to the populations or target groups who are ultimately the users or beneficiaries of the research. In fact, agencies such as the National Science Foundation (NSF) have funded projects utilizing indigenous research methods at Tribal Colleges. Clearly, discussions are increasing regarding the importance of avoiding the use of majority methods and approaches on populations who are not operating in the same cultural spaces and contexts, and this includes technological design. Funding is also moving toward more emphasis on equity (Ioannidis 2018).
Another example is shown by a “Dear Colleague” letter issued by the NSF calling for proposals focusing attention on fairness, equity, accountability, and transparency (FEAT) in research in computing, information science, and engineering (National Science Foundation 2018). The letter intended to advance more inclusive research in computing. Sponsors like the NSF must continue to expand representation of ideas in science and limit bias by populating the funded research domain with individuals from diverse backgrounds.
Ultimately, STEM-IRE is about redistributing privilege and power to create and disseminate knowledge claims. It is also about opening doors to allow new ways to conceptualize and conduct research using a more inclusive lens. The challenge to all STEM leaders in academia is to reflect on whether the act of “opening the doors” of science and the research enterprise to advance inclusion is more valuable to them than holding on to the privilege gained from allowing only a select few to fully participate and benefit.
This work is based on an action learning project implemented by the Center for the Advancement of STEM Leadership (CASL), and supported by the National Science Foundation. Thank you to Katherine McGraw, CASL writing coach, who provided valuable feedback and editing. Thank you also to Kelly Mack for leadership in this dissemination opportunity.
Association of American Colleges and Universities. 2005. “Making Excellence Inclusive.” Accessed April 12, 2017. https://www.aacu.org/making-excellence-inclusive.
Bandura, Albert. 2002. “Social Cognition Theory in Social Cultural Context.” Applied Psychology 51 (2): 269–90.
Bolman, Lee E. and Joan V. Gallos. 2011. Reframing Academic Leadership. San Francisco: Jossey-Bass
Buolamwini, Joy. 2016. “InCoding—In the Beginning: Whoever Codes the System, Embeds Her Views. A Call for Inclusive Code.” Medium. May 16, 2016. https://medium.com/mit-media-lab/incoding-in-the-beginning-4e2a5c51a45d.
Callister, Ronda Roberts. 2006. “The Impact of Gender and Department Climate on Job Satisfaction and Intentions to Quit for Faculty in Science and Engineering Fields.” Journal of Technology Transfer 31: 367−375.
Chilisa, Bagele. 2012. Indigenous Research Methodologies. Los Angeles: SAGE.
Du Bois, W. E. B. 1903. The Souls of Black Folk. Chicago: A. G. McClurg & Company.
Gambrel, Patrick, and Rebecca Cianci. 2003. “Maslow’s Hierarchy of Needs: Does It Apply in a Collectivist Culture?” Journal of Applied Management & Entrepreneurship 8: 143.
Hurston, Zora Neale. 1942. Dust Tracks on the Road: An Autobiography. New York: Harper Perennial.
Ioannidis, John P. A. 2018. “Rethink Funding: The Way We Pay for Science Does Not Encourage the Best Results.” Scientific American Special Report: What’s Wrong with Science and How to Fix It 319 (October): 53–55.
Kunda, Ziva. 1999. Social Cognition: Making Sense of People. Cambridge, MA: MIT Press.
Maslow, Abraham H. 1943. “A Theory of Human Motivation.” Psychological Review 50 (4): 370−396.
National Center for Education Statistics. 2017. “Characteristics of Postsecondary Faculty.” Accessed January 22, 2017. https://nces.ed.gov/programs/coe/indicator_csc.asp.
National Science Foundation. 2018. “Dear Colleague Letter: Fairness, Ethics, Accountability, and Transparency: Enabling Breakthrough Research to Expand Inclusivity in Computer and Information Science and Engineering Research.” November 2, 2018. https://www.nsf.gov/pubs/2019/nsf19016/nsf19016.jsp.
O’Neil, Cathy. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York, NY: Crown Publishing Group.
Perna, Laura W. 2001. “The Relationship Between Family Responsibilities and Employment Status among College and University Faculty.” Journal of Higher Education 72 (5): 584−611.
Stanley, Christine A. 2007. “When Counter Narratives Meet Master Narratives in the Journal Editorial Review Process.” Educational Research 36 (1): 14−24.
Thompson, Chastity Q. 2008. “Recruitment, Retention, and Mentoring Faculty of Color: The Chronicle Continues.” New Directions for Higher Education 143: 47–54.
Turner, Caroline Sotello Viernes, Juan Carlos González, and J. Luke Wood. 2008. “Faculty of Color in Academe? What 20 years of Literature Tells Us.” Journal of Diversity in Higher Education 1: 139−168.
Uriarte, Maria, Holly A. Ewing, Valerie T. Eviner, and Kathleen C. Weathers. 2007. “Constructing a Broader and More Inclusive Value System in Science.” Bioscience 57 (1): 71−78.
Wachter-Boettcher, Sara. 2017. Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech. New York: W. W. Norton and Company.
Tonya L. Smith-Jackson, Senior Vice Provost for Academic Affairs; Program Director, CISE-IIS, National Science Foundation; Professor, Industrial and Systems Engineering and Fellow, Center for the Advancement of STEM Leadership, North Carolina A&T State University; and Goldie S. Byrd, Professor, Wake Forest School of Medicine and Director, Maya Angelou Center for Health Equity, Center for the Advancement of STEM Leadership (CASL)