The Ordinary Language Test

The Ordinary Language Test

How can you tell whether scientific-sounding language explains something or merely sounds impressive?

An ordinary-language test starts by asking what the claim means. Consider a research paper titled “Transgressing the Boundaries: Towards a Transformative Hermeneutics of Quantum Gravity.” The paper begins as follows:

“There are many natural scientists, and especially physicists, who continue to reject the notion that the disciplines concerned with social and cultural criticism can have anything to contribute, except perhaps peripherally, to their research. Still less are they receptive to the idea that the very foundations of their worldview must be revised or rebuilt in the light of such criticism. Rather, they cling to the dogma imposed by the long post-Enlightenment hegemony over the Western intellectual outlook, which can be summarized briefly as follows: that there exists an external world, whose properties are independent of any individual human being and indeed of humanity as a whole; that these properties are encoded in “eternal” physical laws; and that human beings can obtain reliable, albeit imperfect and tentative, knowledge of these laws by hewing to the “objective” procedures and epistemological strictures prescribed by the (so-called) scientific method.

But deep conceptual shifts within twentieth-century science have undermined this Cartesian-Newtonian metaphysics; revisionist studies in the history and philosophy of science have cast further doubt on its credibility; and, most recently, feminist and poststructuralist critiques have demystified the substantive content of mainstream Western scientific practice, revealing the ideology of domination concealed behind the façade of “objectivity.” It has thus become increasingly apparent that physical “reality,” no less than social “reality,” is at bottom a social and linguistic construct; that scientific “knowledge,” far from being objective, reflects and encodes the dominant ideologies and power relations of the culture that produced it; that the truth claims of science are inherently theory-laden and self-referential; and consequently, that the discourse of the scientific community, for all its undeniable value, cannot assert a privileged epistemological status with respect to counter-hegemonic narratives emanating from dissident or marginalized communities. These themes can be traced, despite some differences of emphasis, in Aronowitz’s analysis of the cultural fabric that produced quantum mechanics; in Ross’ discussion of oppositional discourses in post-quantum science; in Irigaray’s and Hayles’ exegeses of gender encoding in fluid mechanics; and in Harding’s comprehensive critique of the gender ideology underlying the natural sciences in general and physics in particular.”

It concludes after a few pages with:

“Finally, the content of any science is profoundly constrained by the language within which its discourses are formulated; and mainstream Western physical science has, since Galileo, been formulated in the language of mathematics. But whose mathematics? The question is a fundamental one, for, as Aronowitz has observed, “neither logic nor mathematics escapes the ‘contamination of the social.’ And as feminist thinkers have repeatedly pointed out, in the present culture this contamination is overwhelmingly capitalist, patriarchal and militaristic: “mathematics is portrayed as a woman whose nature desires to be the conquered Other.”

Thus, a liberatory science cannot be complete without a profound revision of the canon of mathematics. As yet no such emancipatory mathematics exists, and we can only speculate upon its eventual content. We can see hints of it in the multidimensional and nonlinear logic of fuzzy systems theory; but this approach is still heavily marked by its origins in the crisis of late-capitalist production relations. Catastrophe theory, with its dialectical emphases on smoothness/discontinuity and metamorphosis/unfolding, will indubitably play a major role in the future mathematics; but much theoretical work remains to be done before this approach can become a concrete tool of progressive political praxis. Finally, chaos theory—which provides our deepest insights into the ubiquitous yet mysterious phenomenon of nonlinearity—will be central to all future mathematics. And yet, these images of the future mathematics must remain but the haziest glimmer: for, alongside these three young branches in the tree of science, there will arise new trunks and branches—entire new theoretical frameworks—of which we, with our present ideological blinders, cannot yet even conceive.”

Phew! Clever stuff, right? Just look at all those science words, for a start. There are also more than a hundred very serious-looking references.

You might glance at material such as the above and conclude that some very specialized theoretical physicists must be doing some very smart, very complicated work on . . . something. The paper was published in Social Text in 1996. The paper was a deliberate hoax: Alan Sokal combined scientific references with unsupported claims to test whether the journal would accept it. A bona fide physics professor at New York University, Sokal wanted to test the intellectual integrity of the journal but also point out how postmodern jargon could undermine the path of genuine scientific inquiry.

Feynman’s teaching technique offers a way to examine what such language actually explains. Feynman believed it was too easy for laypeople to get confused and led astray by words that sounded intelligent and scientific. Simon Oxenham at Big Think uses Deepak Chopra as an example of someone who uses scientific language in a way that makes his statements sound deep . . . but have no meaning.

Oxenham tells us about a speech Feynman gave at a meeting of the National Science Teachers Association in 1966 as a counterpoint to such statements. Instead of asking people who aren’t scientists to deal with claims that sound scientific on their own terms, Feynman would have us translate them into ordinary language. This would force any person making the claim to focus on the underlying logic of what they’re saying, rather than obscuring a weak point behind impressive but empty language.

The example Feynman uses is from the most basic source: a "first grade science textbook" that ”begins to teach science in an unfortunate way” by showing a picture of a “windable toy dog,” then a picture of a real dog, and then a picture of a motorcycle.

“What makes it move?” is asked of each student. Feynman tells us that the answer was in the book’s teacher’s edition: “Energy makes it move.” But few students had an in-depth understanding of the word energy, and being able to give this answer doesn’t prove they have any real understanding of what energy is and how it works. Feynman says,

“I finally figured out a way to test whether you have taught an idea or you have only taught a definition. Test it this way: You say, ‘Without using the new word which you have just learned, try to rephrase what you have just learned in your own language. Without using the word “energy,” tell me what you know now about the dog’s motion.’ You cannot. So you learned nothing about science. That may be all right. You may not want to learn something about science right away. You have to learn definitions. But for the very first lesson, is that not possibly destructive?

I think for lesson number one, to learn a mystic formula for answering questions is very bad. The book has some others: ‘gravity makes it fall;’ ‘the soles of your shoes wear out because of friction.’ Shoe leather wears out because it rubs against the sidewalk and the little notches and bumps on the sidewalk grab pieces and pull them off. To simply say it is because of friction, is sad, because it’s not science.”

Feynman says that the answer in the back of the book could have just as equally, and just as uselessly, been “God makes it move” or “The ability to move makes it move.” A science lesson should explain what happens and how, so students learn more than a name for the process.

Since so much misunderstanding and faulty thinking occurs on the level of language, we can use a modified version of the above test to help us discern real science from pseudoscience. This version goes like this: Can we explain the thing in ordinary, plain terms? If we cannot, we have a reason to ask which terms, assumptions, or mechanisms we have not understood. Plain language helps us inspect the claim; evidence is still needed to evaluate it.

If you encounter any explanation in the world, ask yourself—can it be explained to an ordinary person in plain language so that they broadly understand it? If you cannot, identify what background knowledge is needed and which parts can be explained more clearly. Some topics require technical concepts; each term should contribute to the explanation.

If you want to test yourself and determine whether you have actually learned something, try to say what you just learned in your own words, but don’t use the new word you just learned. In the same way as a student answering “energy” doesn’t prove that a student understands the phenomena in question, you might betray a lack of understanding if you merely parrot the scientific-sounding words you’ve picked up along the way.