Cutting Across Disciplines: Co-Production and the Rise of a Computational Culture

Over the past few decades, the academic landscape has been shaped by two concurrent trends: growing specialization into multiple disciplines and subfields, alongside increasing calls for collaboration. Parallel to these developments is the growing integration of advanced computational methods into research. Against this backdrop, this paper examines how this computational turn reshapes researchers’ fundamental understanding of scientific inquiry. Drawing on a comparative study that includes in-depth interviews with researchers from life sciences and the humanities, we investigate the definitions and meanings ascribed to computationalism, as well as how it changes the way researchers think and do science. Our findings reveal that computational is often viewed as a set of functional tools—primarily for data collection, generation, and analysis. Beyond this computational-as-tools approach, however, it also emerges as a distinct mode of thinking. In particular, it transforms the research questions, spurs a transition from hypothesis-driven to data-driven inquiry, and places models at the heart of scholarly work, being a technique for reducing complexity and fostering more abstract conceptualizations. In light of these shifts, we propose that a joint epistemic culture is on the rise—one that transcends traditional disciplinary boundaries and is shared by researchers from fields once considered worlds apart.