On the scientific method

The defining features of science are the source of its practical value, but they are also its limitations. It takes for granted the separation of subject from object, of an observer from the thing observed, that is the basis of the “common sense” human worldview. Ironically, this same separation is what Buddhists call avidyā or not-knowing, our basic error of failing to recognise phenomena as our own creations. So it might be said that, although science is a method of gaining knowledge, it has been built on a foundation of not-knowing.

Data by itself is not knowledge. Even facts committed to memory are just one step beyond facts stored in books on a shelf. The evaluation of data is as important as the data itself. But to evaluate anything we have to start from at least one datum that is known with certainty. And that presupposes some system of metaphysics (what’s real?) and epistemology (how do we know it?), neither of them prominent in the current intellectual landscape.

The scientific method was often taught in schools as a balance or alternation between deduction from the more general to the specific, and induction from the specific to the general.

But in practice, science proceeds mainly by gathering data and making deductions, rather in the tradition of Sherlock Holmes. Consequently it often appears that each generation of researchers is focussing on smaller and smaller questions in greater and greater detail. There is a lack of any formal process for drawing conclusions from observations and experiments, explicitly transmissible from teacher to student. Inductive thought in science has often been informal, and based on individual inspiration that dares an occasional leap beyond the safe ground of deduction. Think of Kepler’s elliptical planetary orbits, Kekulé’s dream of the benzene ring, Mendel’s digital model of inheritance, or Faraday’s sizeless electron.

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