Modern science’s ability to produce, store, and analyze big datasets is changing the way that scientific research is practiced. Philosophers have only begun to comprehend the changed nature of scientific reasoning in this age of “big data.” We analyze data-focused practices in biology and climate modeling, identifying distinct species of data-centric science: phenomena-laden in biology and phenomena-agnostic in climate modeling, each better suited for its own domain of application, though each entail trade-offs. We argue that data-centric practices in science are (...) not monolithic because the opportunities and challenges presented by big data vary across scientific domains. (shrink)

Robustness with respect to climate models is often considered by philosophers of climate science to be a crucial issue in determining whether and to what extent the projections of the Earth’s future climate that models yield should be trusted. Parker (2011) and Lloyd (2009, 2015) have introduced influential accounts of robustness for climate models with seemingly conflicting conclusions. I argue that Parker and Lloyd are characterizing distinct notions of robustness and providing complementary insights. Confidence, if warranted, need be by virtue (...) of causally consistent climate models rather than by agreement upon projections by a diverse range of models. (shrink)

Peter Railton (1978) has introduced the influential deductive-nomological-probabilistic (DNP) model of explanation which is the culmination of a tradition of formal, non-pragmatic accounts of scientific explanation. The other models in this tradition have been shown to be susceptible to a class of counterexamples involving intervening causes which speak against their sufficiency. This treatment has never been extended to the DNP model; we contend that the usual form of these counterexamples is ineffective in this case. However, we develop below a new (...) version which overcomes these difficulties. Thus we claim that all of the models in this tradition, DNP included, have an equal status with respect to sufficiency. (shrink)

There is another set of entities that needs to be brought into the conversation about the ethical, legal, and social implications of scientific conduct. This widely varied group includes not‐for‐profit educational, academic, public‐service, and philanthropic organizations other than the type mentioned above as well as for‐profit businesses. Despite their major differences, these organizations may all be in a position to make decisions, directly or indirectly, about the conduct of scientific research. And those decisions may have a significant impact on the (...) parties normally involved in thinking and talking about obligations and concerns—the researchers, the subjects, and the general public. Yet there are few if any conceptual frameworks to help organizations address the ethical, legal, and social issues related to conducting scientific research. There are also few resources to help organizations find and develop the expertise required to make responsible decisions or communicate those decisions in ways that could support and advance the ethical conduct of research.In what follows, we try to identify and explore the duties, rights, and interests of one such organization, the Center for Talented Youth at Johns Hopkins University, when asked to play a supporting role in research on the genetics of intelligence. As central agents in this case, we hope to demonstrate why organizations like CTY cannot be neglected in the broader effort to ensure trustworthy research into the genetics of intelligence. (shrink)