Dan Sarewitz contributed to a recent Slate edition on science education with a critique of how science literacy is typically construed. Framed by a visit to a racetrack, Sarewitz argues in the piece that what scientific literacy is usually considered to be – a general understanding of the fundamentals of science – doesn’t effectively speak to a person’s ability to navigate the world. Besides the specific knowledge of horse racing, and the charts that communicate performance information, Sarewitz relates several interactions with people at the track that suggest people can and do have a solid understanding of certain areas of science. But these areas are pretty context-specific. For instance, someone understands the problems of cigarette smoking because they can’t quit.
Yet, the idea that increasing scientific literacy, like many other notions connected to science and technology policy, will lead to better public engagement with science – persists. Related to this notion of general science knowledge contributing to better citizens (or at least those who would be more inclined to pick the same kinds of policies science literacy proponents prefer) is the so-called ‘deficit model’ of the public understanding of science. But to focus on the literacy angle we can also look at the notion of technological literacy. The challenge with this idea, from my perspective working in computer science policy, is a flexibility in meaning. While it could be used to mean an understanding of how technology is created and how it operates, it can just as easily be used to mean an ability to use technology. Put another way, its the difference between being able to create a computer program or smartphone application versus knowing how to operate those programs on the relevant devices.
Sarewitz does not advance an alternative definition or conception of scientific literacy, but I think his larger point (or one of them) is to emphasize the value of context. For me it serves as another reminder that there remain many conceptual devices or maxims within science and technology policy that are accepted uncritically, or resist criticism. I’m not sure what benefits may come from properly deconstructing them for the mass audience (i.e., policymakers), but it could help with my increasing cognitive dissonance.