Further Reading: The Speed of Truth

Tier 1: Verified Sources

On Correction Speed and Planck's Principle

Azoulay, Pierre, Christian Fons-Rosen, and Joshua S. Graff Zivin. "Does Science Advance One Funeral at a Time?" American Economic Review, 2019. The most rigorous empirical test of Planck's principle. Azoulay and colleagues found that the death of a prominent scientist in a field leads to an influx of new entrants and a change in the direction of research — supporting the idea that generational replacement plays a significant role in paradigm change. Essential empirical complement to this chapter's theoretical framework.

On the Montreal Protocol and Ozone Correction

Andersen, Stephen O., and K. Madhava Sarma. Protecting the Ozone Layer: The United Nations History. Earthscan, 2002. A comprehensive history of the Montreal Protocol, including the political negotiations, industry opposition, and scientific debates that preceded it. Provides the detailed context that the "clean version" of the ozone story typically omits.

Molina, Mario J., and F. Sherwood Rowland. "Stratospheric Sink for Chlorofluoromethanes: Chlorine Atom-Catalyzed Destruction of Ozone." Nature, 1974. The original paper that proposed the mechanism for CFC-driven ozone depletion. Worth reading as an example of high evidence clarity — the chemical mechanism was clear, specific, and testable from the beginning.

On Forensic Science and Slow Correction

National Research Council. Strengthening Forensic Science in the United States: A Path Forward. National Academies Press, 2009. The landmark NAS report that documented the lack of scientific basis for many forensic techniques. The report's recommendations have been only partially implemented, illustrating the model's prediction of slow correction when defender power is high and crisis probability is low.

President's Council of Advisors on Science and Technology (PCAST). Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods. 2016. A follow-up report that found continued use of scientifically unsupported forensic methods seven years after the NAS report. Demonstrates the reform exhaustion effect (Chapter 19) and the structural barriers to correction in the legal system.

On Metascience and Correction Mechanisms

Ioannidis, John P. A. "Why Most Published Research Findings Are False." PLoS Medicine, 2005. The most-cited paper in the metascience literature. Ioannidis's analysis of how statistical practices, publication bias, and incentive structures produce unreliable research findings is foundational for understanding the "evidence clarity" and "switching cost" variables in the Correction Speed Model.

On Paradigm Change

Kuhn, Thomas S. The Structure of Scientific Revolutions. University of Chicago Press, 1962. The foundational work on paradigm change. Kuhn's model — normal science → anomaly accumulation → crisis → revolution → new normal science — is the intellectual ancestor of the Correction Speed Model. This chapter both builds on and extends Kuhn's framework by making the variables explicit and testable.

Tier 2: Attributed Claims

Research on "correction speed" in metascience is a growing field. Studies have examined how quickly retracted papers stop being cited (slowly — retracted papers continue to accumulate citations for years), how quickly disproven claims are removed from textbooks (very slowly — textbook revision cycles are long), and how quickly reformed practices are adopted across a field (variable, depending on institutional incentives).

The concept of "acceleration levers" for correction draws on several bodies of research: the Open Science movement's work on outsider access and transparency, the science policy literature on funding heterodox research, and the organizational behavior literature on institutional reform.

Comparative studies of correction speed across fields are rare — most metascience research focuses on single disciplines. The cross-field comparative analysis in this chapter draws on historical case studies rather than systematic quantitative comparison, which represents a limitation and an opportunity for future research.