Like any other organized body of doctrine, science has its founding myths. Modern science has two central ones: (i) That there exists a non-trivial scientific method (SM) and (ii) that theory in science plays second fiddle to observation/experiment. Combine (i) and (ii) and we reach a foundational principle: good science practice discards theories when they clash with experimental observation. And, maybe just as important, bad science involves holding onto theories that conflict with experiment/observation. Indeed, from the perspective of SM perhaps the cardinal irrationality is theoretical obstinacy in the face of recalcitrant data.
There are several reasons for the authority of this picture. One is that it fits snugly with the Empiricist (E) conception of knowledge. As I’ve noted before (much too often for many of you I suspect) E is both metaphysically (see here) and epistemologically (see here) suspicious of the kind of generalizations that required by theory.
Metaphysically, for E, observation is first, generalizations are second, the latter being, summations of the former. As theories, at least good ones, rest on generalizations and given that they are only as good as the data that they “generalize” it is not surprising that when they come in conflict, theories are the things that must yield. Theories and laws are, for E, useful shorthand compendia of the facts/data/observations and shorthands are useful to the degree that they faithfully reflect that which they hand shortly.
Epistemologically, generalizations are etiologically subsequent to observations. In fact they are inductively based on them and, in the limit, should do nothing more than summarize them. Good scientific practice should teach how to do this, should teach how to eliminate the “irrationalities” that waylay legit inductions forcing them away form the data that they are (or should be) built on. So again, in practice, when data and generalization/theory conflict, the problem likely lies with some illegitimate bias tripping up the induction from data to generalization/theory.
There is a less highfalutin reason that makes the two fold myth above attractive to scientists. It lends them authority. On this view, scientists are people who know how to see the world without illusion or distortion. They are privy to a method that allows them to find the truth (or at least not be distracted from it. So armed, scientists have a kind of epistemological expertise that makes their opinions superior to those of the untrained. The speculations of scientists are grounded in and regulated by the facts, unlike the theories (and prejudices) of the unwashed. Observe that here the scientific opinion is grounded in reality, and is not just one opinion among many. Being scientific endows legitimacy. Being non-scientific removes it.
This thnking is a holdover from the old demarcation debates between science and non-science (i.e. religion, ethics, prejudice, etc.) that the Positivists loved to engage in. Within philosophy proper the idea that there exists a sharp demarcation between science and non-science is not well regarded anymore. In fact, it has proven very difficult to find any non-circular ways of establishing what belongs on either side of the divide. But scientists don’t always hold the wisdom of philosophers in high regard, especially when, IMO, it serves to puncture their self-regard and forces them to reconsider the degree to which their scientific credentials entitles them to automatic deference in the public sphere. Most everyone enjoys the deference that legitimate authority confers, and science’s access to such revolves around the combo of (i) and (ii) above. The bottom line is that the myth buttresses a very flattering view: scientists think more clearly and so see better because their views are based in the facts and so deserve deferential respect.
So here are two reasons that the founding myth has proven so strong. But there are other reasons too. We tend to tell our stories (at least our mythical ones) about how science advances largely in terms that fit this picture. A recent short Aeon paper discusses one such founding myth involving that great scientific hero Galileo and the Copernican world view. Btw, I am one of those that count both as heros. They really were pretty great thinkers. But as this paper notes, what made them such is not that they were unafraid to look at the facts while their opponents were mired in prejudice. Nope. There was a real debate, a scientific one, based on a whole series of interacting assumptions, both empirical and theoretical. And given the scientific assumptions of the time, the push back against Galileo’s Copernicism was not irrational, though it proved to be wrong.
The hero of the short piece is one Johann Locher. He was a Ptolemeian and believed that the earth was the center of the universe. But, he made his case in purely scientific terms, the biggest problem for the Copernican vision being the star-size problem which it took some advances in optics to square away. But, as the piece makes clear, this is not the view we standardly have. The myth is that opposition to Galileo/Copernicus involved disregard for the facts driven by religious prejudice. This convenient account is simply false, though it part of the reason it became standard is Galileo’s terrific popular polemic in his Dialogues Concerning the Two Chief World Systems.
Christopher Graney, the author of the short piece, thinks that one baleful result of the scientific caricature Galileo unleashed is today’s science skepticism. He believes that today’s skeptics “… wrap themselves in the mantle of Galileo, standing (supposedly) against a (supposedly) corrupted science produced by the ‘Scientific Establishment’” (3). This may be so. But I doubt that this is the only, or most important problem with the myth. The real problem (or another problem) is that the myth sustains a ghostly version of the demarcation criterion among working scientists. Here’s what I mean.
As I’ve noted before, there is a general view among scientists that data trumps, or should trump, theory. The weak version of this is unassailable: when data and theory clash then this constitutes a prima facie problem for theory. But this weak version is compatible with another weak view: when data and theory clash this constitutes a prima facie problem for the data. When there is a clash, all we know, if the clash is real, is that there is either a problem with the theory or a problem with the data and that is not knowing very much. No program of action follows form this. Is it better to drop/change the theory to handle the data or to reanalyze the data to save the theory? Dunno. The clash tells us nothing. However, due to the founding myth, the default view is that there is something wrong with the theory. This view, as I’ve noted, is particularly prevalent in linguistics IMO and leads the field to dismiss theory and to exalt description over explanation. So, for example, missing a data point is considered a far worse problem than having a stilted explanation. Ignoring data is being unscientific. Eschewing explanation is just being cautious. The idea really is that facts/data have an integrity that theories do not. This asymmetric attitude is a reflection of Science’s founding myths.
So where does this leave us? The aim of science is to understand why things are as they are. This involves both data and theory in complex combinations. Adjudicating between accounts requires judgment that rarely delivers unequivocal conclusions. The best we can do is hold onto two simple dicta and try to balance them: (i) never believe a theory unless grounded in the facts and (ii) never believe a fact unless grounded in a theory. It is the mark of a truly scientific temperament, in my view, that it knows how to locally deploy these two dicta to positive effect in particular circumstances. Unfortunately, doing this is very difficult (and politically it is not nearly as powerful as holding the first of these exclusively). As Graney notes, “science has always functioned as a contest of ideas,” not just a contest of competing observations and data points. Facts (carefully curated) can tell us how things are. But scientific explanation aims to explain how things must be, and for this, facts are not enough.
 By this I mean a substantive set of precepts rather than cheers of the sort “do your best in the circumstances at hand,” or as Percy Bridgeman said “use your noodle and no holds barred.”
 The reply to this is well known: a theory is responsible for relevant data and what exactly counts as relevant often requires theory to determine. But I put such niceties aside here.
 A most amusing discussion of this period can be found in Feyerabend’s writings. He notes that there were many reasons to think that looking through a telescope was hardly an uncontroversial way of establishing observtions. He is also quite funny and does a good job, IMO, of debunking the idea that a non-trivial SM exists. By non-trivial I intend something other than “do your best in the circumstances.”
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