“A Balance between Data & Theory”
“In all of science, we’re looking for a balance between data and theory.” ~ Michael Shermer, PhD.
Science, I think, is misnamed, and I think a better name for it would be simply and much more inclusively “reality,” since that, more than anything else, is what science deals with, and better than any other human endeavor. Better than politics or religion by far, and much better than pretenders to science stemming from either.
Science is something we humans do very well, better and more often than any other species. I fail to understand the reasoning behind claims that science dehumanizes us, as uniquely human an activity as it is. It’s the best way we have to date at understanding the many regimes of reality…
…not just tangible, physical reality, limited to the input of the basic human senses…but also the realm of numbers and logic, and the realms of reality in which human interaction, experience, thinking and feeling exist — there are objective facts even of those things typically thought deeply personal, like dreams and seeming premonitions, both traceable to neurological events and explainable in terms of brain function and the often counterintuitive laws of chance.
Science deals too with realms of reality beyond our everyday perceptions and experience — extrasolar planets; galaxy clusters millions, or billions of light years away; tiny microorganisms; atoms and molecules, only registering to our ordinary senses in the things they compose; ionizing radiation — these things completely imperceptible to us directly, but revealed by instrumentation we create with our minds and hands, to extend the power, range and accuracy of our senses into worlds of awareness once closed to us.
Even if science will never explain absolutely everything, it’s not Scientism™ to say that it can inform us on those matters that most concern us, even areas to which it may seem inappropriate, like love, esthetics, and those questions formerly the domains of religion, politics, economics, and myth, where these make testable claims with meaningful answers.
Politics sometimes has its occasional reality-checks, when policies enacted have practical consequences, and these can be tested to see if they ‘work’, but lately it amounts to little more than public relations and cynical appeals to the electoral base for votes and money.
This is especially so when scientific findings with implications for policy decisions are ignored or suppressed for short-term gain, ironically justified by lobbyists and office-holders by projecting the very same onto scientists while themselves promoting junk science to cast doubt on inconvenient facts and figures.
But far better a harsh truth than reassuring lies and tu quoque fallacies…
It’s the old and tired “I know you are but what am I?” game. Old and tired, but still in need of pointing out when it happens. Labeling argument strategies is a good way of reducing their rhetorical effectiveness.
Even some scientists get involved in this sometimes for reasons of strong ideological conviction, other times, less scrupulously, for favors or money from corporate sponsors, with most of them acting outside their own field of expertise — a thing even scientists need to avoid if they are to have any basis to make their statements — expertise in one field is not global, and does not carry over to other fields, even closely related ones.
This is why you don’t ask a molecular biologist out of touch with the current research, much less an intelligent design creationist, to correctly and honestly inform you about the evolution of the bacterial flagellum, or mousetraps and bicycles, and the reason you don’t ask someone with a degree in nuclear physics to tell you about the Truth™ of UFOs as extraterrestrial spacecraft.
Both are examples of pseudoscientists with an over-dependence on theory at the expense of data and sustained by poor argumentation. And not even coherent, testable theory…
As with the quote above, science seeks a balance between data and theory, neither arbitrarily changing facts to suit immutable theories, nor in making theories ad hoc patchwork quilts neither testable nor fertile in the predictions they make.
The former is functionally dishonest even when sincere motives are involved, and the latter illogical, unparsimonious and scientifically uninteresting, though often very interesting to ideologues.
Data without theory is useless — you cannot make anything of it until you know what it should explain, what it should mean and how it should do that — and theory without data to support it does not stand a good chance of being correct until that problem is resolved, and it is the difficult work of bringing these to a workable equilibrium with each other that the methods and tools of science, used collectively and over time by thousands of researchers in multiple fields, rather than the archaic notions of the lone genius in his (or her) attic workshop, that thus far have achieved just that in areas thought insurmountable by human inquiry.
And that’s what it does: Pushes back old frontiers only to open up entirely new ones to our wonder and scrutiny, as it
should does when working at its best.