Philosophy of science

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The philosophy of science is concerned with the assumptions, foundations, methods and implications of science. It is also concerned with the use and merit of science and sometimes overlaps metaphysics and epistemology by relating to if scientific results are actually a study of truth. In addition to these central problems of science as a whole, many philosophers of science also consider problems that apply to particular sciences (e.g. philosophy of biology or philosophy of physics). Some philosophers of science also use contemporary results in science to reach conclusions about philosophy.

Although most practitioners are philosophers, several prominent scientists have contributed to the field and still do. Other prominent scientists have felt that the practical effect on their work is limited: “Philosophy of science is about as useful to scientists as ornithology is to birds,” according to physicist Richard Feynman.[1] Feynman's comment may be more witty than accurate. It is true that some focuses of the philosophy of science, such as metaphysics, are considered impractical, even tangential to real science. However, the focus on epistemic and semantic aspects of science, define when research results are believed as truth or rejected as fiction.

Epistemology is a key research topic in the philosophy of science. In practical application, epistemology defines the burden of proof, often set in relation to statistical confidence intervals used within the framework of the scientific method. For example, the second largest area of public science funding in the U.S. is health research. Most of this large body of research is geared towards that elusive holy grail of philosophy and science: causality. Practitioners of the scientific method seek to locate effects (i.e. the descriptive statistic of an illness rate) strongly associated to causes (i.e. the descriptive statistic of pathogens or carcinogens). This process of using a combination of means and variances to measure and analyze natural phenomena is inference. Correlation and regression are two common techniques used to try to link causes with effects.

A philosopher of science might ask an epistemic question such as: “How confident are scientists about the methods for deciding when to believe confidence intervals?” Even a hard scientist like Feynman must admit there are a number of persistent topics that cause significant doubt for the advocate of traditional statistical inference: Bayesian inference, Publication bias, representation theory, scientific modeling, spatial statistics, Ecological fallacy, Dynamical systems. The philosopher of science asks abstract questions: “How confident are we, that we can reduce the world into lists of numbers, analyze the numbers and make reliable decisions?” Such questions are abstract, but not impractical. Public health research is an undeniably concrete example of the utility of the philosophy of science. How confident are we that a certain drug, causes a side effect, or reduces an illness rate? Is the lack of a statistically significant result in an ecological study a good justification not to fund a more expensive randomized controlled trial? Does the width of confidence intervals bias the allocation of scientific funding towards some health studies at the expense of others? These are just a few examples of practical questions raised in this broad field.

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