5 items with this tag.
The research industrial complex describes the self-reinforcing system of incentives across universities, funding bodies, journals, and publishers that rewards publication volume and impact metrics over meaningful scientific progress. The term draws on Eisenhower's military-industrial complex to highlight how interconnected institutional interests can sustain a system that actively works against its own stated mission.
Academic publishing treats scholarship as a finished, individually owned artefact. This post describes a writing and publishing workflow built on a different premise: that a scholarly corpus could work like an open source project — readable, contributable, forkable, and never permanently owned by anyone.
Academic culture has converged on the peer-reviewed journal article as the default unit of scholarly output, creating a hierarchy that excludes many valuable forms of intellectual work. This post makes the case for essays as a legitimate form of scholarship—not as a lesser alternative to empirical research, but as a distinct mode that enables exploration, synthesis, and engagement with audiences that traditional publishing cannot reach. Drawing on Boyer's model of scholarship, it argues for a more generous conception of what counts as scholarly contribution.
Academic publishing has converged on the written journal article as the dominant form of scholarly output, but knowledge has always been transmitted through conversation, dialogue, and oral communication. This post explores whether audio scholarship—podcasts, recorded dialogues, oral histories—deserves recognition as legitimate scholarly work. Drawing on Boyer's model of scholarship, it argues that format matters less than the rigour, intention, and intellectual contribution behind the work, and considers what it would take for academic culture to broaden its definition of what counts.
The introduction of generative AI into scientific publishing presents both opportunities and risks for the research ecosystem. This essay argues that scientific journals must transform from metrics-driven repositories — prioritising publication volume over meaningful progress — into vibrant knowledge communities using AI to facilitate discourse. AI can support this by surfacing connections between research, making peer review more dialogic, and enabling multimodal knowledge translation. Meaningful change requires coordinated action across institutions, funding bodies, and journals willing to prioritise scientific progress over quantitative metrics. By reimagining journals as AI-supported communities rather than article-processing platforms, the research ecosystem can better serve scientific knowledge development and clinical outcomes.