Scientists often seek predictively accurate models, rather than models that are true.

It is an interesting fact about model selection that the evidence at hand can indicate that a model known to be false will be more predictively accurate than a model known to be true. This opens the door to a kind of instrumentalism.

Evolutionary biologists often appeal to parsimony when they seek to explain why organisms "match" with respect to a given trait. For example, why do almost all the organisms that are alive today on our planet use the same genetic code? If they share a common ancestor, the code could have evolved just once and then been inherited from the most recent common ancestor that present organisms share. On the other hand, if organisms in different species share no common ancestors, the code must have evolved repeatedly.

Trait X is fitter than trait Y in a population of organisms if those organisms have other biological traits T and live in an environment that has properties E. The theory of natural selection is filled with statements of this form.

Our own species evolved under the influence of group selection, as Darwin emphasized when he discussed the evolution of altruism.

One influential philosophical position about the use of probability in science holds that probabilities are objective only if they are based on micro-physics; all other probabilities should be interpreted subjectively, as merely revealing our ignorance about physical details. I have argued against this position, contending that the objectivity of micro-physical probabilities entails the objectivity of macro-probabilities.

It can be a necessary conceptual truth that pains are painful without this ruling out the physicalist thesis that immaterial minds are impossible or the thesis that conscious states supervene on physical states. The necessity involved in these claims is nomological necessity, not metaphysical necessity (assuming that these are different).