Dani Bassett (12/5/2023): Science as branched flow: A case study in citation disparities

Science is a beautiful rational process of highly structured inquiry that allows us to learn more about our world. By it, we see past old theories, and build new ones. We realize a phenomenon occurs because of this, and not that. Perennially the skeptic, we spar with our own internal models of how things might happen: always questioning, ever critical, rarely certain. What if we were to turn this audacious questioning towards—not science—but how we do science? Not broadly a natural phenomenon but more specifically a human phenomenon? This query is precisely what drives the field of the science of science. How does science happen? How do we choose scientific questions to pursue? How do we map fields of inquiry? How do we determine where the frontiers are, and then step beyond them? In this talk, I will canvas this broader research agenda while foregrounding recent advances at the intersection of science of science, machine learning, and big data. Along the way, I’ll uncover gender, racial, and ethnic inequalities in the most obvious of places (the demographics of scientists) and also in the most unexpected and out-of-the-way places (the reference list of journal articles). I will consider what these data mean for the way we think about science—for our theories of what science is. What opportunities might we have to see past old theories and build a new one? What possibilities to lay down a new praxis for a science of tomorrow?