Data, Information, and Knowledge: Reframing Narratives about Women of Color in STEM
Angela B. Ginorio
By Angela B. Ginorio, associate professor of women studies at the University of Washington
Fifteen years ago, in Warming the Climate for Women in Academic Science, I shared an allegory that I first developed in 1991 while working with faculty members in a science department at my university. In the allegory, I envisioned academic science as a plant conservatory and offered a take-home lesson via a line attributed to the story’s most successful gardener. Standing in for an educator, the gardener remarks: “I try to provide what each plant (that is, what each student) needs” (Ginorio 1995, 1).
When I first used that statement, I was thinking in particular of a woman of color graduate student whose needs had been egregiously ignored by her department. The department had focused its energies on maintaining institutional practices that had been developed before students like her were present, thus leaving her needs and the needs of other women unaddressed. I did not think the women’s needs were particularly difficult to meet, but they would require faculty members to give students the same careful attention they gave the conditions under which they ran their experiments.
In considering what I know now that I did not know then, I have come to reflect on the different kinds of narratives that can be told based on different types of data. I want to offer some perspective on the roles data play in forming information and knowledge pertinent to women of color in science, technology, engineering, and mathematics (STEM). In doing so, I return to the allegory of the gardener. In today’s parlance, “I try to provide what each student needs” too often becomes “I try to provide for the needs of underrepresented women of color students.” But these statements are not equivalent, and their differences have important implications for women of color’s work in STEM fields.
The Trouble with Demographic Data
“I try to provide what each student needs” versus “I try to provide for the needs of underrepresented women of color students”: How do these statements differ? The first begins with the understanding that the gardener’s success relies on having enough knowledge to create healthy growing environments for all plants. Similarly, the successful educator needs to know how individual differences and group dynamics, local institutional conditions, and historical trajectories affect each student’s experiences within her particular academic institution. With that knowledge, educators can create the conditions for each student to grow, and can measure success by how each student fares. In contrast, the second statement too often stems from a limited understanding of what is needed for women of color to succeed in science. It suggests that STEM educators simply need to understand how underrepresented women of color students differ from the norm as it is currently defined. In this model, the educator would measure success by the degree to which the student conforms to the norm—a focus that places the onus of change on the individual rather than on the normative group.
Allow me to leave unproblematized for the moment the existence of a norm, particularly one that centers on the experiences of white American males despite the increased presence of those who are not white, American, or male (see, for example, Fiegener 2009, table 2). Let me focus instead on the consequences of the norm for those who don’t meet it, offering as an example the often-reported fact that women of color students and faculty in STEM fields are isolated. Within academe and industry, the higher the level, the lower the number of women and of women of color in particular—and the higher the concomitant numerical isolation. This pattern has existed for as long as data have been collected, and it is precisely the kind of long-documented fact that leads Musil to state, “Higher education now has all the data it needs to make significant changes” (2010). Referring to the benchmark 1975 conference The Double Bind, MacLachlan makes a similar observation: “All of the issues raised then are still with us today[;] some are exactly the same, some now have a different emphasis. Change has occurred…[but] how great the changes are remains to be assessed” (2000, 1).
Women of Color in STEM
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The exasperation detectable in these statements comes from knowing that although the data have long illustrated women of color’s numerical isolation, this information has yet to be translated into the kind of knowledge that leads to good policies or practices. When based solely on quantitative data, reports on the topic do little more than document how underrepresented women of color students differ from a norm and inform us about the slow demographic shifts happening incrementally in many areas of STEM (see, for example, Fiegener 2009). These publications, like Warming the Climate, may make multiple recommendations, but the resulting changes are uneven and often hard to assess.
Barriers to Assessment
The changes that result from a report’s recommendations may be hard to assess because they involve many different institutional contexts, including recruitment processes, retention in majors or careers, graduation from college, or promotion within jobs. Any solution and its measure should be designed specifically for the institutional context in which it will be applied, and with the sources of isolation that exist in that particular context in mind. Yet despite the need to measure progress within specific and discrete contexts, in most cases, isolation is measured using the number of women of color in a larger population. From that number, which is usually very small, researchers conclude not only that specific women are isolated—which is true by definition for any woman of color who is the only one or one of a few—but also that these women feel isolated. Flowing from that conclusion is the assumption that the individual’s feeling of isolation, rather than the cause of isolation, is what must be addressed.
Consider the example of recruitment (or access, from the applicant’s perspective) and the tendency for isolation to be translated as invisibility. In order to attract students of color, colleges and departments may address invisibility by displaying in their websites’ portals pictures that reflect ethno-racial and gender diversity that is not necessarily present within the college or the department. In the retention context (or the context of inclusion, from the student or faculty perspective), many solutions likewise focus on addressing what women of color need—that is, their “neediness”—rather than on implementing truly inclusive practices within the STEM fields. In the context of professional promotion, solutions may likewise address the “special needs” of women, offering mentoring or networking for support. These solutions focus on teaching women of color how to live under conditions that were not designed with them in mind, rather than on changing the conditions themselves.
The effects of changes in policy or practice are also hard to assess due to the small numbers of women of color in STEM. Researchers studying women of color in academic science face difficulties inherent in research conducted in small populations, including challenges to the accepted use of quantitative methods. Data disaggregated by gender and race or ethnicity yield the most useful information about women of color in STEM. But disaggregation often results in samples with fewer than five subjects, leading to data that are nonreportable according to the current standards of quantitative methods. By following standard guidelines, researchers are left without information or with partial answers. Even data on whole populations such as that collected by the National Science Foundation promptly lead to very small numbers when disaggregated by the parameters necessary to obtain information on women of color. No wonder, then, that Carey writes in the preface to The Double Bind that underrepresented women of color may be “falling somewhere in between the funded efforts to improve science opportunities for minorities and efforts to advance women in science” (1976, vii).
Documentation, but Little Knowledge
Let us turn our attention for a moment to the status of women of color STEM faculty. Even after fifty years of affirmative action, the number of faculty of color in STEM fields is appallingly small (see, for example, Nelson and Brammer 2010). Current practices that rule out the use of small numbers as bases for information have served as barriers to the knowledge these small numbers might provide. Aware that the dearth of information limits what advocacy is possible, my colleagues in the Social Studies of Science Research Group (Sara Díaz, Emma Flores, Allison Kang, Annie O’Connell-Torgersen, and Amanda O’Connor) and I set out to find scholarly information published between 1997 and 2006 on the participation of people of color as STEM practitioners. We focused on six academic disciplines in the social sciences: anthropology, communications, history, philosophy, psychology, and sociology (2008). Surely, we thought, we would find some interesting narratives about women and men of color in science that would help us not only document their experiences, but also move from information to knowledge.
Informed by existing quantitative data, we began by searching the available scholarship for materials that would go beyond numbers to elucidate more complicated narratives about the intersectionality of race, class, gender, and sexuality; the structure of science and of academia; and the mechanisms through which discrimination and bias operate in STEM fields. Perusing the materials generated by our research, we soon realized that many of the thousands of items we located had serious flaws that disqualify them from being included in bibliographies on women of color in STEM fields. We found many papers of the following three types, none of which provide the kind of information that can serve as a basis for generating knowledge about women of color in STEM:
- Papers that mention women of color in STEM fields as absent (as a group that was not included in the study because participants could not be found)
- Papers that mention women of color in STEM fields in passing (for example, “in the sample there were thirty Caucasians, twelve Asians, three African Americans, and two Latinas…”)
- Papers that mention women of color in STEM fields incidentally (for although they include these women, the questions driving them do not flow from concerns related to women of color in STEM fields)
Furthermore, the great majority of all articles on women of color in STEM are not about practicing women scientists but about students.
When we eliminated all materials that were flawed as listed above and all those focused solely on student access and retention, we were dismayed to find only twenty-eight sources from five disciplines (and none from anthropology) that met our criteria. These results told us that although the absence of women of color in STEM has been repeatedly documented over the past fifty years, such documentation has not led to the kinds of knowledge that would yield significant changes either in STEM practices or in the scholarship about such practices. Even the Journal of Women and Minorities in Science and Engineering, dedicated to the study of such populations, yielded only ten articles on women of color out of a total of 221 articles published from its inception in 1994 until December 2006 (Ginorio et al. 2008).
Our research demonstrates that under current prescriptions for data worth reporting, very little information exists that focuses on the efforts, successes, challenges, and perseverance women of color in STEM. Many narratives that draw on the data focus on women of color’s “special needs.” Yet like plants in a conservatory, all students and faculty members have their own individualized conditions that they need in order to thrive. One set of needs is more “normal” than another only if one kind of student or faculty member has greater value, a priori, than another.
Small Numbers, Significant Stories
I conclude my observations by returning to the discussion of isolation. Narratives that flow from data documenting small numbers often presume that numerical isolation is the main perceptual focus for women of color in STEM. But how do we know how each woman of color experiences isolation? How do we know that what she feels is isolation rather than exclusion? How do we know how she copes with either the numerical or the experienced isolation or exclusion? Is this knowledge not an important part of what we need to know about women of color in STEM fields?
By focusing data collection on numerical measures and framing narratives in terms of isolation rather than exclusion, researchers emphasize the “needs” of the individual rather than the institutional setting that interacts with those needs. At the same time, they suggest that the individual has no agency, as she cannot control how many other women of color are present in her particular context. By this type of accounting, it is hard to see women of color in STEM as agents of change.
Following from the public policy dictum “If you want to change policy, you need stories and you need numbers,” I am suggesting that even small numbers have their own stories, and that these stories are worth researching and reporting. Research that focuses on small numbers and qualitative measures offers one venue for telling the stories of women of color in STEM who have succeeded against all odds. These stories need to be told with all the rich contextual detail necessary to build understanding about how women of color practice science and how gender, race, class, and sexuality operate in science and in their lives.
The move from data to information to knowledge will shift social scientists away from the current narrative surrounding women of color in STEM fields, which focuses on their continued underrepresentation and difference from a norm. Such a move would result in new narratives that start from the assumption that the lives of women of color in STEM are worth studying. These new narratives are essential if we are to generate a complete accounting of STEM and build a world where the presence of women of color in these fields is recognized as significant. These narratives may also illuminate what is really needed if we are to increase the numbers of women of color in STEM.
Carey, William D. 1976. Preface to The Double Bind: The Price of Being a Minority Woman in Science, by Shirley Mahaley Malcom, Paula Quick Hall, and Janet Welsh Brown. Washington, DC: American Association for the Advancement of Science. http://web.mit.edu/cortiz/www/Diversity/1975-DoubleBind.pdf.
Fiegener, Mark K. 2009. "Numbers of US Doctorates Awarded Rise for Sixth Year, but Growth Slower." Washington, DC: National Science Foundation. http://www.nsf.gov/statistics/infbrief/nsf10308/.
Ginorio, Angela B. 1995. Warming the Climate for Women in Academic Science. Washington, DC: Association of American Colleges and Universities.
Ginorio, Angela B., Sara P. Díaz, Emma Flores, Allison Kang, Annie O’Connell-Torgersen, and Amanda O’Connor. 2008. “Interdisciplinary Social Sciences Approaches to the Participation of Ethnic Minorities in STEM.” http://depts.washington.edu/ssnet/3SR_report_for_SSN.pdf.
MacLachlan, Anne J. 2000. “The Lives and Careers of Minority Women Scientists.” Paper presented at the National Association of Women in Higher Education conference, New Orleans, LA, January. http://cshe.berkeley.edu/publications/docs/NAWEpaper.pdf.
Musil, Caryn McTighe. 2010. “A Chilly Climate? Adjust the Thermostat.” On Campus with Women 39 (2). http://www.aacu.org/ocww/volume39_2/director.cfm.
Nelson, Donna, and Christopher N. Brammer. 2010. A National Analysis of Minorities in Science and Engineering Faculties at Research Universities. http://chem.ou.edu/~djn/diversity/Faculty_Tables_FY07/FinalReport07.html.