The idea that ambiguity can be productive in data science remains controversial. Efforts to make scientific publications and data intelligible to computers generally assume that accommodating multiple meanings for words, known as polysemy, undermines reasoning and communication. This assumption has nonetheless been contested by historians, philosophers, and social scientists, who have applied qualitative research methods to demonstrate the generative and strategic value of polysemy. Recent quantitative results from linguistics have also shown how polysemy can actually improve the efficiency of human (...) communication. I present a new conceptual typology based on a synthesis of prior research about the aims, norms, and circumstances under which polysemy arises and is evaluated. The typology supports a contextual pluralist view of polysemy’s value for scientific research practices: polysemy does both substantial positive and negative work in science, but its utility is context-sensitive in ways that are often overlooked by the norms people have formulated to regulate its use, including prior scholars researching polysemy. I also propose that historical patterns in the use of partial synonyms, i.e. terms with overlapping meanings, provide an especially promising phenomenon for integrative research addressing these issues. (shrink)

At the beginning of the twentieth century, the biologist Joseph Grinnell made a distinction between science and sentiment for producing fact-based generalizations on how to conserve biodiversity. We are inspired by Grinnellian science, which successfully produced a century-long impact on studying and conserving biodiversity that runs orthogonal to some familiar philosophical distinctions such as fact versus value, emotion versus reason and basic versus applied science. According to Grinnell, unlike sentiment-based generalizations, a fact-based generalization traces its diverse commitments and thus becomes (...) tractable for its audience. We argue that foregrounding tractability better explains Grinnell’s practice in the context of his time as well as in the context of current discourse among scientists over the political “biases” of biodiversity research and its problem of “reproducibility.”. (shrink)