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cRam Session: Health Science in the Time of Uncertainty – Public Health and the Politicization of Science

3 questions, 2 minutes, 1 lesson with Kevin Brosnan, whose course showcases how the humanities can deepen our understanding of medicine, science and public trust.

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cRam Session is a VCU News feature that highlights the breadth of offerings in the VCU Bulletin course catalog and the wide-ranging expertise of the instructors. Associate professor Kevin Brosnan, Ph.D., teaches in the Department of Philosophy and is affiliated faculty with the Institute for Women’s Health. He shares quick insight from Health Science in the Time of Uncertainty: Public Health and the Politicization of Science, a course he co-developed with sociology associate professor Susan Bodnar-Deren, Ph.D.

Give us an insightful connection between past and present on this subject.

We examine the famous mid-20th-century debate between statistician R.A. Fisher and epidemiologist Bradford Hill over whether smoking causes lung cancer. Hill argued that it does, on the basis of the strength and consistency of their association. Fisher argued otherwise, demanding more rigorous, randomized evidence — and he ultimately testified on behalf of the tobacco industry.

This debate connects to many contemporary ones, as it concerns the following general question: When is scientific evidence strong enough to support a causal claim? Contested answers to this question crop up regularly in clinical and public health policy contexts, as illustrated by contemporary debates about evidence-based medicine, the efficacy of masking and the harmful effects of ultra-processed foods.

The debate between Fisher and Hill also illustrates how the language of scientific rigor can be weaponized to manufacture doubt. For example, the rhetorical strategies used by the tobacco industry to sow public doubt about the risks of smoking have since been adopted by fossil fuel companies to undermine public trust in climate science.

But distrust in science doesn’t stem only from misinformation. It is also rooted in the long history of medical racism, from the Tuskegee Syphilis Study to ongoing racial disparities in care. In exploring these issues, students learn that such mistrust is often justified — but that this fact has been exploited by conspiracy theorists and authoritarian actors who seek to erode trust altogether.

The challenge is not to reject science but to reclaim it. When practiced with integrity, scientific methods remain among our most powerful tools for uncovering truth and resisting exploitation. The task is to distinguish misuse from method — to critique science without discarding its democratic and emancipatory potential.

What is your favorite assignment you have students do?

It’s a collaborative poster presentation in which students explore major philosophical and ethical challenges in the health sciences. Topics have included vaccine hesitancy; medical colonialism; the replication crisis, which concerns the failure to reproduce a study’s findings; and the problem of discordant evidence, where the same study is interpreted to both support and oppose a policy, such as a mask mandate.

This year, the work culminated in a student-led undergraduate research conference on the crisis of trust in medicine and science. Michael Fine, M.D., former director of the Rhode Island Department of Health and founder of Primary Care for All Americans, served as our keynote speaker, visited our class and spoke at VCU’s School of Medicine.

How does an element of this subject intersect intriguingly with a different field?

This course investigates how foundational debates in statistics shape public health policy. For instance, the routine use of p-values in clinical research reflects a deeper philosophical commitment about what counts as evidence.

But this commitment is controversial: Many philosophers of science and statisticians argue that p-values are routinely misinterpreted and that they obscure more than they reveal. These debates raise conceptual questions that can’t be settled by empirical data alone — questions that live at the intersection of philosophy, statistics and the experimental sciences.

Our course invites students to explore these tensions and understand how our most pressing scientific debates often rest on unexamined philosophical foundations.