A new study claims that most people misunderstand the environmental impact of the food they eat—and that better labeling could fix the problem. But does the evidence actually support that conclusion?

In this episode, we break down the logic behind that claim using LSAT-style analysis. We look at the study’s design, including its small and localized sample, the use of controlled sorting tasks instead of real-world behavior, and the assumption that scientific models of environmental impact provide a definitive benchmark.

From there, we explore deeper reasoning issues: the difference between heuristics and errors, the gap between stated intentions and actual behavior, and the risks of overgeneralizing from limited data.

The result is a classic LSAT problem hiding in plain sight: when a study shows that people’s beliefs don’t perfectly match the data, does that mean they’re wrong—or just simplifying a complex system in a practical way?

If you want to get better at spotting flawed reasoning in research, policy, and everyday claims, this episode is a perfect place to start.