Visualizing the intellectual influence of women pedagogues through metadata mapping

For centuries, historical attempts have been made to counteract the effects of gender inequality, with more recent initiatives including the ratification of the 1972 Equal Rights Amendment and the recognition of Women’s History Month every March. However, living in a sociopolitical climate where their intellectual contributions are often obscured by their “mobile, ethnocentric, raced, institutional or extra-institutional status” (LWP “About,” 2023), women educators in certain disciplines remain underrepresented, even in the macrohistories of their fields. Such underrepresentation, specifically in the form of digital patriarchy, misconstrues feminist historiography and can reinforce ideas about the intellectual growth of their disciplines that may be false. That is why navigating the migration of archival works by women pedagogues is critical— the effort to ascertain its mobility provides clarity on their intellectual influence.

Dr. Tarez Graban, associate professor of English and former affiliate to the digital humanities master’s program at FSU, has worked with her team to develop the Linked Women Pedagogues (LWP) project, a “data-discovery tool” that brings light to women educators and their contributions from the Progressive Era to the end of the 20th century. This time frame is especially important for the field of rhetorical studies, Graban says, because these programs began increasingly offering women a way to pursue higher education and thus influence much of the reform that took place. In particular, not only does the tool allow users to locate the lifecycle of their work—the physical locations of the work, the writers’ intentions, historians’ motives for locating their work, etc.— but the “ongoing interactions” of their work as well. This includes historians’ insight on where a particular text or curricular item has been used, where pedagogical performances took place, or any topical shifts in thinking over time. With a new scope of information accessible, users can gather meaningful insight about the influence of these figures and develop deeper connections with feminist perspectives, unconstrained by information bias.

The power of the LWP project, Graban says, lies within its ability to “limn the dual narrative of researchers and their subjects.” From a technical view, it can utilize crowd-sourcing and data input from users, which can then be visualized in the form of multi-linear projections or digital ecologies. These visualizations are versatile based on their data type, format, size or source, significant in their ability to depict complex relationships between abstract concepts such as time and motivation. Practically speaking, this means users may have greater access to less traditionally visible aspects of women’s careers, including their mobility, their changing affiliations, and their national and transnational activities. This added visibility allows for users to reorganize the discovered data to create new research questions and find other researchers looking into similarly underrepresented women pedagogues.

While the LWP project was originally conceptualized in 2010, its development would not have been possible without the help of the FSU Research Computing Center (RCC). “I have benefited mostly from the RCC’s expanding human infrastructure, and I can’t emphasize enough how valuable that is for this project and at this juncture,” Graban remarks. Meanwhile, she gives her gratitude to Marcelina Nagales, one of the RCC’s current team members, who aided in the development of data analyzing models for the LWP. “Her knowledge of 3D modeling for cultural heritage artifacts and digital reconstruction … allows her to play a critical role in educating me about the resources required by this kind of data discovery tool. In addition, I find that data extraction—especially from large data sets, in both stable repositories and dynamic Web-based interfaces—is a constant struggle. Yet this is precisely what LWP must be able to achieve, in as many ways as possible, and for as long as possible. Her training in computational archaeology and data science has equipped her to help me develop an incremental infrastructure for the project.”