The Structure of Scientific Revolutions book notes
I finally got around to reading Thomas Kuhn’s classic of the philosophy of science. I found it somewhat hard to follow at times because the syntax does not flow as mellifluously as it could. Nevertheless, the book has too many insightful points to be tossed aside due to such petty issues. Here are some of my notes. Assume it is a direct quote unless otherwise noted with brackets.
[T]he practice of astronomy, physics, chemistry, or biology normally fails to evoke the controversies over fundamentals that today often seem endemic among, say, psychologists or sociologists.
To be accepted as a paradigm, a theory must seem better than its competitors, but it needs not, and in fact never does, explain all the facts with which it can be confronted.
Mopping-up operations are what engage most scientists throughout their careers… that enterprise seems an attempt to force nature into the preformed and relatively inflexible box that the paradigm supplies.
These three classes of problems–determination of significant fact, matching of facts with theory, and articulation of theory–exhaust, I think, the literature of normal science, both empirical and theoretical.
[Scientists solve puzzles, science solves problems]
The first, X-rays, is a classic case of discovery through accident, a type that occurs more frequently than the impersonal standard of scientific reporting allows us easily to realize.
Proliferation of competing theories… [is] the concomitant of crisis.
Almost always the men who achieve these fundamental inventions of a new paradigm have been either very young or very new to the field whose paradigm they change. And perhaps that point need not have been made explicit, for obviously these are men who, being little committed by prior practice to the traditional rules of normal science, are particularly likely to see that those rules no longer define a playable game and to conceive another set that can replace them.
Without commitment to a paradigm there could be no normal science. Furthermore, that commitment must extend to areas and to degrees of precision for which there is no full precedent. If it did not, the paradigm could provide no puzzles that had not already been solved.
Since no paradigm ever solve all the problems it defines and since no two paradigms leave the same problems unsolved, paradigm debates always involved the question: Which problems is it more significant to have solved?
Scientists are not, of course, the only group that tends to see its discipline’s past developing linearly toward its present vantage. The temptation to write history backward is both omnipresent and perennial.
What all of Dalton’s accounts omit are the revolutionary effects of applying to chemistry a set of questions and concepts previously restricted to physics and meteorology. That is what Dalton did, and the result was a reorientation toward the field, a reorientation that taught chemists to ask new questions about and to draw new conclusions from old data.
“A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.” - Max Planck
Probably the single most prevalent claim advanced by the proponents of a new paradigm is that they can solve the problems that had led the old one to a crisis. Copernicus thus claimed that he had solved the long-vexing problem of the length of the calendar year, Newton that he had reconciled terrestrial and celestial mechanics, Lavoisier that he had solved the problems of gas-identity and of weight relations, and Einstein that he had made electrodynamics compatible a revised science of motion. [Especially if a quantitative solution is presented.]
Because scientists are reasonable men, one or another argument will ultimately persuade many of them. But there is no single argument that can or should persuade them all. Rather than a single group conversion, what occurs is an increasing shift in the distribution of professional allegiances.
Probably the most deeply held values [of scientists] concern predictions: they should be accurate; quantitative predictions are preferable to qualitative ones; whatever the margin of permissible error, it should be consistently satisfied in a given field; and so on. [In] judging whole theories: they must, first and foremost, permit puzzle-formulation and solution; where possible they should be simple, self-consistent, and plausible, compatible, that is, with other theories currently deployed.
Is the current debate between Ed Vul and the social neuroscience community (first summarized here, retort here, counterpunch here) a paradigm shift? Perhaps, but I think what it will most accomplish is to make everyone involved in science be more vigilant about their methods of data analysis. There are thousands of science bloggers on the web these days, waiting to scrutinize ill-informed results.
Although this may be bad for some individual scientists, ultimately it will improve the quality of science.