Further Reading: The Epistemic Health Checklist

Tier 1: Verified Sources

Ioannidis, John P. A. "Why Most Published Research Findings Are False." PLoS Medicine 2, no. 8 (2005): e124. The foundational paper for understanding why entire fields can produce systematically unreliable findings. Ioannidis's framework — which considers study power, effect size, bias, and the number of teams investigating — provides the statistical foundation for the Epistemic Health Checklist's emphasis on replication culture and incentive alignment.

Nosek, Brian A., et al. "Promoting an Open Research Culture." Science 348, no. 6242 (2015): 1422–1425. The Transparency and Openness Promotion (TOP) Guidelines provide a concrete framework for assessing Dimension 10 (Process Transparency) — with specific levels of data sharing, code sharing, pre-registration, and replication that can be used as scoring criteria.

National Academies of Sciences, Engineering, and Medicine. Fostering Integrity in Research. National Academies Press, 2017. A comprehensive assessment of the structural conditions that support or undermine research integrity. Directly relevant to Dimensions 2 (Replication), 3 (Incentives), and 10 (Transparency).

Fleck, Ludwik. Genesis and Development of a Scientific Fact. University of Chicago Press, 1979 (originally 1935). A pioneering analysis of how scientific communities construct knowledge — including the social mechanisms that sustain both correct and incorrect consensus. Fleck's concept of "thought collectives" anticipated many of the dimensions in the Epistemic Health Checklist.

Kuhn, Thomas S. The Structure of Scientific Revolutions. University of Chicago Press, 1962. The classic work on paradigm shifts and the resistance of scientific communities to paradigm change. Kuhn's framework provides the theoretical foundation for Dimensions 1 (Dissent), 7 (History), and 8 (Falsifiability).

Tier 2: Attributed Claims

The concept of scoring organizational "epistemic health" has precedents in quality improvement frameworks (ISO standards, Malcolm Baldrige criteria) and in organizational learning theory (Chris Argyris, Peter Senge). The specific dimensions in this checklist are derived from the failure modes documented in Parts I-III of this book.

Medicine's "17-year bench-to-bedside gap" has been widely cited since a 2001 report by the Institute of Medicine (Crossing the Quality Chasm), though the specific timeline has been debated.

The concept of "dissent tolerance" as a predictor of organizational health is supported by research on psychological safety (Amy Edmondson) and team decision-making quality.

  1. Start with Ioannidis (2005) — for the statistical framework showing why fields produce unreliable findings
  2. Then Nosek et al. (2015) — for the concrete transparency standards
  3. Then Kuhn (Structure of Scientific Revolutions) — for the theoretical foundation
  4. Then the National Academies (2017) — for the institutional integrity framework
  5. Then Fleck (Genesis and Development) — for the deepest treatment of how knowledge communities work