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Increasingly, biomedicine has become the hegemonic paradigm under which international institutions like the WHO approach global health problems. Technocratic frameworks position doctors and biomedical academics as “experts” whose knowledge constitutes the gold standard when designing interventions. Although biomedicine constitutes global health’s “present,” history shows that there have been (and continue to be) global traditions of healing where expert knowledge is rooted in different understandings of health and illness.

Lately, international institutions like the World Health Organization (WHO) have begun acknowledging these “alternative” frameworks, which they term “traditional, complementary, and integrative medicine (TCIM).” The WHO has integrated TCIM into its policy and practice by standardizing and benchmarking systems like Ayurvedic and traditional Chinese medicine. However, this development is recent and there is little work documenting and analyzing the organization’s previous stances on this topic. This project fills the gap by using archival data to generate a timeline of the WHO’s engagement with TCIM. Generating a historical narrative of the organization’s engagement with TCIM is one step towards unpacking the taken-for-granted status of biomedicine as the inevitable manifestation of “modern” global health. As part of this project, I collected, cleaned, and performed preliminary corpus analysis on a sample of documents from the WHO’s organization archives dealing with the search term “traditional medicine.”

Over the course of my research, I learned four main things (two about the substance of my project, and two about the nature of digital humanities work): first, that the WHO’s engagement with TCIM has been distinctly bound geographically (in terms of what regions and practices are most often the subject of policymaking) and temporally (there are distinct historical phases of engagement with TCIM). Second, that the WHO rarely self-identifies its operational framework using the term “biomedicine,” instead opting to use more oblique terms such as scientific, technological, modern, or standard. In this case, corpus analysis revealed an absence that has meaning in and of itself.

Third, regarding the process of engaging in digital humanities work – good data is hard to find, and even harder to make. The foundation of good digital humanities work is often built on the sometimes rote and mundane acts of cleaning data and cataloguing metadata. Fourth, the value of digital humanities tools is twofold: it enables us to find, collect, and analyze data in unique ways, but in doing so also forces us to confront broader philosophical questions about the tension between precision and scale when creating and engaging with data involving meaning-making processes.