More on the demarcation problem

Here’s another note on the contemporary ubiquitous desire (especially among scientists and “experts”) to demarcate science (and with it “expertise”) from everything else. You know my take: it cannot be done. We currently have no (interesting and principled)[1]way to demarcate scientific inquiry from other kinds and there is little reason to believe that a (non-trivial bright) line will be discovered anytime in the near (or distant) future. FWIW, philosophers have been trying to find this border for a very long time (you can imagine there is a professional interest in being able to distinguish sense from nonsense), and the current wisdom in the philo community is that there is no there there. Here is a recentish short provocative piece on the topic that goes over the familiar ground (henceforth DS). As I read it, it provoked a few questions: Why should we care to demarcate the scientific from the non-scientific? Is this an urgent project for Science (note the big ‘S’) or for individual sciences? And if so, why? And if not, why does it appear to be sprouting everywhere one looks?  Let’s expatiate.

First, we can ask the factual question: what if anything unifies what we collect under the term ‘Science’? The short answer is not much. DS goes over the usual suspects. To the degree that there is a scientific method, it is not refined enough to distinguish things that lie on what those desirous of the demarcation line would put on one side or the other. “Do your best in the circumstances” is probably all that one can milk out as general methodological advice. This is Feyerabend’s familiar (and correct) observation.

If not a single method, what of communal methods? This too is of little help. As DS notes (2):

The methods used to search for subatomic components of the universe have nothing at all in common with field geology methods…Nor is something as apparently obvious as a commitment to empiricism a part of every scientific field. Many areas of theory development, in disciplines as disparate as physics and economics, have little contact with actual facts, while other fields now considered outside of science, history and textual analysis, are inherently empirical.

So, there is no general method and few robust methods that cut across domains of inquiry to be of use. 

Second question: does this matter? Not obviously. An inquiry requires some questions, puzzles, facts, and methods/technology. These are all generally justified in unison. Given a question prompted by an observation, yields a puzzle, that might be explained by deploying a particular method generating a more refined question, leading to a deeper puzzle, …. Of course, one can start someplace else. A puzzle prompts an observation that clashes with an inchoate “theory” that suggests other facts, that enforce/dispel the puzzle etc…. Or an observation suggests a puzzle that provokes an inquiry that leads to a hypothesis that… All of this can be locally monitored and justification can and does take account of the rich circumstantial detail. Engaging in such inquiry requires making the rules up as you go along, including establishing the requisite standards for the clarity of the questions at hand, deciding what counts as a good explanation relative to these questions, an adumbration of the relevant kinds of data, sample examples of what might resolve the puzzles, all leading to refinements of the initial questions and a restart of the process. The aim is not to avoid circularity (it cannot be done) but to progressively widen the circle so that it is not vicious. Anything goes that gets one going, though how one measures whether one is going and in what direction(s) one is moving in is also up for constant negotiation. 

So, within a particular program all the issues relating to method become important for they end up defining the enterprise. There is nothing outside of this process to adjudicate the activity, or at least nothing principled. But this does not mean that within it there are not better and worse arguments or that dispute between conceptions must be irrational. One can, must, and does argue about the interest of the question being asked. One can, must and does argue about the methods being deployed to answer that question. One can, must and does argue about whether proposals actually address the question being asked. And one should do all of this most of the time. However, and this is the main point, none of this requires that we have rich general methodological principles or that what is good in domain A will be of any consequence or relevance in domain B. Of course, looking at other domains to see what they do can be useful and suggestive (IMO, physics envy is an excellent research attitude), but so can banging your head against the wall while reciting the Lord’s Prayer.[2]

Moreover, none of this local wrangling will be useful in evaluating what counts as Science. If justification is local then demarcating the good from the bad in a general manner that applies across domains is likely to be question begging. As any academic knows, all fields have their methods and questions. If these are the measure of Science, then everything is Science. Christian (and Political (and dare I say, Language)) Science included.

So, there is no general Scientific Method and, luckily, as regards individual inquiries it does not matter. So why the endless quest among non-philosophers? Why is it important to demarcate where science ends and non-science begins. As DS notes this is a particularly hot issue for scientists (and “technology and policy oriented intellectuals” [3]).

I can attest to this worry. The whole obsession with STEM and spreading the STEM gospel is testament to this. I get daily appeals from STEM candidates running for congress. There is even an organization that supports getting STEMers elected (314 Action). The idea seems to be that being STEM gives one a leg up on rationality and political insight. In fact, the presupposition seems to be that having STEM endows special authority on those that have it. And where does the authority come from? Well, STEM implies scientific and this implies having expertise of a kind generally applicable to political matters. So demarcating science from non-science is there to separate “those who are granted legitimacy to make claims about what is true in the world from the rest us…” (2). If this is the goal, then the need for global standards becomes apparent and the demarcation problem becomes urgent. Why? Because only then can science be used to protect the enlightened from the unwashed by endowing some with authority and removing it from others. And this needs an objective basis (or at least a perceived objective basis). 

And not only for those on the receiving end.  It is critical that those at the receiving end of authoritative pronouncements believe that these are legit. Grounding them in Science makes them legit. Hence being scientific is critical. Moreover, those that wield authority must also believe that they are doing so legitimately to mitigate cognitive dissonance. This is an important line, and the harder it is to draw the more a blanket justification of some views over others teeters.

Note that none of this is intended to say that all reasons are on a par without being able to demarcate the scientific from all else. Even without a demarcation, there is excellent reason to believe that the planet is getting warmer due to human activity, that evolution operates, that austerity policies during depressed economic times is self-defeating, that FL/UG exists that generates hierarchical Gs exists and that humans have it, etc. These conclusions are not hard to defend. But they are not defended by noting that they are the products of scientific inquiry, but by noting the evidence and the theory for them. That’s what does the work and claims backed by little evidence or theory are of little value regardless of the methods used to generate them. 

Nor does any of this mean that being in a position to adjudicate proposals might not require quite a bit of technical expertise. It might and often does. But, again it is not because the technical expertise is what makes something scientific but because some expertise is grounded in real questions addressed by good theories backed by good data. Technical wizardry can be an indication of cargo cultism rather than insight, as anyone in any mildly technical domain can attest.

So, onereason for the urgency of the demarcation issue today is the challenge to “authority” that is in the air and the hope that cloaking it in “science” will serve to stifle it by lending it legitimacy.

There is another reason as well. Many domains of inquiry are suffering from internal problems. By this I mean problems internal to the domains of inquiry themselves. There is the “replication” crisis in many sciences that is beginning to undermine their status as “sciences” in the public mind (and this has a spillover effect into the public status of (big ‘S’) Science more generally). There is also the fact that some domains seem to have hit an impasse despite their overwhelming success. Fundamental physics seems to be in this position nowadays if the public toing and froing is any indication (see herefor short version of the angst regarding work in this area). So the legitimacy issue is hitting Science form both ends. The replication crises stems from a purported problem with the data. On the other end, fundamental physics is suffering from an unhealthy obsession with beauty (aesthetic benchmarks concerning “simplicity,” “naturalness” and “elegance” (see here)). Both critiques point to an uncomfortable conclusion for many: science as currently practiced is getting away from the “facts” and the results should be treated very skeptically (and what is wrong with a good dose of skepticism anyhow?). But, IMO, this is the wrong conclusion. 

The right one is that we sometimes run into walls where our methods fail us. Or, when we really don’t know what’s going on, then nothing much helps except a good idea that gets us going again. And if a problem is really hard, then good ideas might be very hard to come by. Big surprise! But this idea, it appears, is tough to swallow. Why?

There is a tacit assumption among scientists that there is a scientific way of doing things and if we just do things in this way then insight must follow. Scientists are particularly prone to this point of view. Not only is it self-flattering (thought it is, it really is) but it is also is very hopeful. Given this view, all setbacks are temporary. All mistakes will self-correct. All obstacles will eventually be overcome and all questions will receive deep and insightful answers. No domain is impenetrable. All problems are solvable. There are no limits to knowledge. Ignorance is temporary, even if hard to dispel. This is a very hopeful message as it encourages the idea that there is always something that can be done that if done right will get us moving forward.  

This moral optimism is the decent side of the belief in a scientific method. And this optimism is what these current failures within the sciences challenges. Add to this (i) that nobody likes pessimists (they are such downers), and (ii) that it is never possible to prove that more hard work, more careful experiments and stats etc. won’t get us moving again and the allure and psychic rewards of the hopeful attitude win the day. So, given the positive spin we place on optimism (“Morning in America”) and the negative one we place on pessimism, there is little surprise that when things get tough there is a desire to justify, which in this case means demarcate. This allows us to segregate the rot and justify optimism for the newly refurbished (rot removed) enterprises.

There is, as always, one further ingredient: Money!! Today money is tight. When money is tight you look to defend your share. Science (big ‘S’ again) is a weapon in the funding wars. Sure, lit and history and philosophy and whatever are fluffy and only valuable when we are flush, but Science, well that needs no defense. Of course, this only works if we can tell what is Science and what isn’t, and hence the obsession on demarcation by scientists. 

So what makes the demarcation issue hot again? The trifecta of the perceived decline in the authority of experts, the current failure in some domains of the traditional methods and declining support together provide more than enough reason to motivate the hunt for a methodological grail.

One of the consequences of Rish conceptions of inquiry is the idea that it comes with implied natural limits.[4]Scientific “success” is always a bit of a miracle (for Descartes, only God guaranteed it (Darwin has often been invoked to similar ends, but his powers are decidedly less expansive)). For people like me, this makes cherishing every apparent explanatory breakthrough deserving of the utmost respect. In practical terms, this leads me to firmly hold onto possible explanations even when confronted with a lot of (apparent) counter evidence. Others dump potential explanations (i.e. theories) more quickly. This is partly a matter of scientific taste. However, there are times when tried and true methods fail. Then doing useful work that meets accepted criteria becomes harder. This should not come as a surprise. It’s the flip side of being able to gain non-trivial understandings of anything at all. It’s what any self conscious Rist who does not have faith in divine harmony would expect.

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[1]There are many uninteresting ways: what the NSF and NIH fund, who the NYT designates an “expert” worth quoting, what Andrew Gelman take to be scientific, etc. It is not excessive, IMO, to observe, that currently, what is scientific sits in the same category as what is prurient: it is at bestknown when seen. And not even then.

[2]The main utility of looking around is to prevent being bullied by methodological sadists and being tripped up by those insisting that asking a question on some particular way or pursuing a program with some particular emphasis falls outside the “scientific.” The best answer to this is to appreciate that there is no obvious way to fall outside the relevant pale as there is no principled border. However, the second bestway is to observe you're your proposals comport with those utilized by other more obviously successful inquiries. The principle goal of physics envy is defensive. It cuts short all sorts of nonsense (e.g. falsifiability, anti-theory hogwash, Eish concerns with idealization, etc.). 

[3]See here.

[4]Though this does not imply that we can know what these limits are. Chomsky has discussed this a lot (scope and limits stuff). It is often derogatorily labeled ‘mysterianism.’ As Chomsky has repeatedly noted, the idea that there are limits to what we can understand is the flip side of noting that we can understand some things deeply. 

Methodological sadism

Methodological sadism (MS) is quite fashionable nowadays and nothing gets practitioners more excited than the possibility that someone somewhere is proposing something interesting (i.e. something that reaches beyond the sensory surface of things and that might possibly reveal some of the underlying mechanics of reality). You’ve all met people like this,[1] and one of their distinctive character traits is a certain (smug?) assurance that when it comes to the philosophy of science, they are on the side of the angels. They love to methodologically demarcate the boundaries of legitimate inquiry so as to protect the weak minded from fake science.

Of course, the standard demeanor of MSers is severe. Yes they are tough. But standards must be maintained lest we slide joyfully to our scientific perdition. Like I said, you’ve all met MSers. Nowadays, at least in my little domain of inquiry, they are the media stars and have done a pretty good job convincing the outside world (and some on the inside) that GG is dead and that there is really nothing special about the cognitive powers required for language. I think that this is deeply wrong, and will write another brief arguing as much in the next post. But for now, I want to, once again, offer some prophylaxis against the most rabid form of MS, falsification.  Here is a useful short antidote, a paper (which I will refer to as ‘AB’ (Adam Becker is author)) that touches all the right themes. Its main claim is that trying to demarcate science from non-science is a mugs game that relies on ignoring how real successful domains of inquiry have grown.

So what are the main themes?

First AB points out that SMers (my term not AB’s) adhere to a basic erroneous principle: “that a new theory shouldn’t invoke the undetectable” (2).[2] Why? Because this makes it “unfalsifiable.”  So, observability underlies falsifiability and both are used by “self-appointed guardian[s], who relish dismissing some of the more fanciful notions in physics, cosmology and quantum mechanics [and linguistics! NH] as just so many castles in the sky” in order to protect science from “from all manner of manifestly unscientific nonsense” (2).

There are ways of understanding falsifiability that seem unobjectionable, namely that theories that never can have observable consequences are thereby undesirable. Well, yeah. The problem is that this is a very low bar, and any stronger version that “turn[s] ingenuity into fact” must be “much more nuanced” (2). Why? Because falsifiability is hardly ever possible and observability is undefinable. Let’s consider both of these facts seriatim.

First falsifiability. This is impossible for scientific theories for the simple reason that any falsification can be patched up with the right ad hoc statement, leaving the rest of the theory the same. As AB puts it (correctly) (2):

Falsifiability doesn’t work as a blanket restriction in science for the simple reason that there are no genuinely falsifiable scientific theories. I can come up with a theory that makes a prediction that looks falsifiable, but when the data tell me it’s wrong, I can conjure some fresh ideas to plug the hole and save the theory.

Any linguist knows how true this is. Moreover, it is easier the less brittle a theory is, and our current theories tend to be very labile. You can bend them in many directions without ever hearing a creak let alone inducing a crack or a break. You loose nothing when adding a bespoke principle to explain recalcitrant data because the only thing there is to loose in doing this is explanatory power and there was not much of this to begin with in flexible theories. However, even with good theories that have some oomph, it is generally possible (I would say “always possible” but I am being mealy mouthed here) to plug the hole and carry on.  One of the virtues of AB is that it provides some nice historical examples of this happening. As AB notes, the history of science is full of them.

AB recounts the famous one where Uranus’ odd (apparently non Newtonian) orbit begats Neptune, which in turn begats Vulcan to explain Mercury’s perihelion which finally fails when General Relativity replaces Newton. AB notes that each historical move makes sense and that looking for Neptune (victory!) and looking for Vulcan (failure!) were both rational despite the different outcomes.  Of course, with hindsight, Neptune is a bold prediction that strengthens the theory and Vulcan turns out to have been just an unfortunate wrong turn. But Vulcan did not lead to people jumping the Newtonian ship. Rather “astronomers of the time collectively shrugged and moved on” (4). And rightly so. Do you really want to give up Newton just because Vulcan was impossible to spot? What then do you do with all the other stuff it does explain?

Note that this means that there is an asymmetry between potentially falsifying experiments that succeed and those that don’t. The former are declared as triumphs of the scientific will, while the latter are quietly shelved and de-emphasized (or, more accurately, added to the ledger of anomalies that a discipline collects as targets for yet unknown superior explanations yet to come). No reason to show these off in public and take the shine from the powerful rational methods of scientific inquiry.

Of course, one might eventually hit the jackpot and find the anomalies resolved with the right new theory. Mercury was a feather in General Relativity’s cap. And well it should have been, for it allowed us to dump Vulcan and replace it with a story that allowed us to also keep all the good parts of Newton. So yes exceptions prove the rule in the sense that Newtonian exceptions prove (justify) Relativity’s rules.

AB provides other examples, one of the best being Pauli’s proposal to save the Law of the Conservation of Energy via the neutrino. It took over 25 years to prove him right (it’s good to have descendants like Fermi who get interested in your ideas). But what is interesting is not merely the long wait time, but why it took so long: the neutrino had no properties at the time that Pauli proposed it that could have allowed it to be detected. So when Pauli proposed it, the theory was unfalsifiable because its basics were unobservable. But, as history shows, wait 25 years and who knows what unobservables might become detectable. As AB again, rightly, puts it (5):

It’s certainly true that observation plays a crucial role in science. But this doesn’t mean that scientific theories have to deal exclusively in observable things. For one, the line between the observable and unobservable is blurry – what was once ‘unobservable’ can become ‘observable’, as the neutrino shows. Sometimes, a theory that postulates the imperceptible has proven to be the right theory, and is accepted as correct long before anyone devises a way to see those things.

Not only is ‘observable’ irreparably vague, but MSers also often make a second more extreme demand concerning its applicability. They require theory to only postulate constructs with directly observable magnitudes. Laws of nature then simply relate “directly observable quantities” and make no reference “to anything unobservable at all” (6). This was essentially Mach’s views and, in hindsight, they served to hamstring scientific insight. For example, as AB notes, Mach opposed atomic theory as unscientific. Why? Well you cannot “see” atoms. Of course, as many pointed out, there is lots to be gained by postulating them (e.g. you can derive the principles of thermodynamics and explain Brownian motion). But this was not good enough for Mach, nor for current day MSers. So how did Mach’s views hold up? Well, it cost Walter Kaufman a Nobel Prize apparently and might have led to Boltzmann’s suicide, but aside from that it did not do any real damage because the scientific community largely ignored Mach’s injunctions.

But isn’t postulating unseen elements unscientific? Well no. Note: even if we all agree that theory must have discernible (aka observable) consequences so that it can be tested/verified, this does not imply that every part of the theory must invoke elements whose properties are directly observable. Of course, it is nice if one can do this. It is always nice to be able to measure. But the idea that the only thing worth doing is relating (perhaps statistically) the magnitudes of observable quantities is something that would sink our best sciences if implemented. And this is a good reason not to do it![3]

One can go further, and AB does. The notion of an observable is itself fundamentally obscure. It cannot mean, observable given “current” technology, for that is too strong. As the history of the neutrino “discovery” indicates, taking this position would have led away from the truth, not towards it. But it cannot mean “observable in principle” for this is irremediably vague. If we mean that it is not “logically possible” to observe what but contradictions will fail. If we mean given current technology or current theory it is too strong. So what then? AB, quotes Grover Maxwell as observing” “There is no a priori or philosophical criteria for separating the observable form the unobservable.” The best we can say is that theories with observable consequences are better situated than those without ceteris paribus. But what goes into the ceteris paribus determination is forever up for grabs, and subject to the inconclusive (yet critically important) vagaries of judgment. No method, just mucking around, always.

AB makes a last observation I’d like to highlight: unlike many, AB emphasizes that part of the scientific enterprise is building “sky-castles.” This is not a scientific aberration, nor an example of science misfiring, but part of the central enterprise. For the scientist (including the linguist see here) “[s]pinning new ideas about how the world could be – or in some cases, how the world definitely isn’t – is central to their work” (2). Explanation leans heavily on the modal ‘could’ in the quote. Not just what you see or mild extensions thereof, but what could be and couldn’t. That’s the stuff of understanding and as AB notes, again rightly, “[the] goal of scientific theory is to understand [my emphasis, NH] the nature of the world with increasing accuracy over time.”

Methodological sadists, if given power, would sink scientific inquiry. They would make it nearly impossible to uncover unobservable mechanisms for they are an inherent part of all decent explanation in the sciences. MSers undervalue explanation and hence distrust the speculation required to get any. As AB notes, their dicta are at odds with the history of science. They are also deeply obscure. So historically misguided and irredeemably obscure? Yes, but also sadistically useful. MSers sound tough minded (just the facts kinda people) but really they are hopeless romantics, stuck with a view of method and inquiry that successful inquiry has largely ignored, as linguists should as well, at least if they want to get anywhere.

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[1] Pullum, Haspelmath, Tomasello and Everett are prominent examples of such in my own little world.

[2] The strong form would say that no theory should, not only new ones. However, MSers generally aspire to be gatekeepers and, in practice, this means keeping out the new. Facing out, rather than in, also has one important advantage. It is pretty hard to argue that accepted results are suspect without making one’s methodological injunctions sound dumb (recall, that every modus ponens comes with an equally powerful modus tolens). Consequently, fire is reserved for the novel, which is always deemed to differ from the accepted in being methodologically deficient. Note that being methodologically deficient has its virtues in argument. It relieves the critic of actually having to go into details, of having to do the hard work of arguing against actual results. MSers generally paint with a broad methodological brush, and I would argue that this is the reason why.

[3] Linguists here should be thinking of those that take Greenberg universals to be the only kinds that are legit (e.g. the crowd in note 1). Why do this? Well because as MSers they demand that science eschew the unobservable. Greenberg universals just are estimates of co-occurrence (either categorical or probabilistic) among surface visible language properties. Chomsky universals are not, and this is why for MSers Chomsky Universals are verboten.

Scientific myths

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)[1] 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.[2] 

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.[3]

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.

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[1] 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.”

[2] 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.

[3] 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.”

Is linguistics a science?

I have a confession to make: I read (and even monetarily support) Aeon. I know that they publish junk (e.g. Evans has dumped junk on its pages twice), but I think the idea of trying to popularize the recondite for the neophyte is a worthwhile endeavor, even if it occasionally goes awry. I mention this because Aeon has done it again. The editors clearly understand the value (measured in eyeballs) of a discussion of Chomsky. And I was expecting the worst, another Evans like or Everett like or Wolfe like effort. In other words I was looking forward to extreme irritation. To my delight, I was disappointed. The piece (by Arika Okrent here) got many things right. That said, it is not a good discussion and will leave many more confused and misinformed than they should be. In what follows I will try to outline my personal listing of pros and cons. I hope to be brief, but I might fail.

The title of Okrent’s piece is the title of this post. The question at issue is whether Chomskyan linguistics is scientific. Other brands get mentioned in passing, but the piece Is linguistics a science? (ILAS), is clearly about the Chomsky view of GG (CGG). The subtitle sets (part of) the tone:

Much of linguistic theory is so abstract and dependent on theoretical apparatus that it might be impossible to explain

ILAS goes into how CGG is “so abstract” and raises the possibility that this level of abstraction “might” (hmm, weasel word warning!) make it incomprehensible to the non-initiated, but it sadly fails to explain how this distinguishes CGG from virtually any other inquiry of substance. And by this I mean not merely other “sciences” but even biblical criticism, anthropology, cliometrics, economics etc.  Any domain that is intensively studied will create technical, theoretical and verbal barriers to entry by the unprepared. One of the jobs of popularization is to allow non-experts to see through this surface dazzle to the core ideas and results. Much as I admire the progress that CGG has made over the last 60 years, I really doubt that its abstractions are that hard to understand if patiently explained. I speak from experience here. I do this regularly, and it’s really not that hard. So, contrary to ILAS, I am quite sure that CGG can be explained to the interested layperson and the vapor of obscurity that this whiff of ineffability spritzes into the discussion is a major disservice. (Preview of things to come: in my next post I will try (again) to lay out the basic logic of the CGG program in a way accessible (I hope) to a Sci Am reader).

Actually, many parts of ILAS are much worse than this and will not help in the important task of educating the non-professional. Here are some not so random examples of what I mean: ILAS claims that CGG is a “challenge to the scientific method itself” (2), suggests that it is “unfalsifiable” Popper-wise (2), that it eschews “predictions” (3), that it exploits a kind of data that is “unusual for a science” (5), suggests that it is fundamentally unempirical in that “Universal grammar is not a hypothesis to be tested, but a foundational assumption” (6), bemoans that many CGG claims are “maddeningly circular or at the very least extremely confusing” (6), complains that CGG “grew ever more technically complex,” with ever more “levels and stipulations,” and ever more “theoretical machinery” (7), asserts that MP, CGG’s latest theoretical turn confuses “even linguists” (including Okrent!) (7), may be more philosophy than science (7), moots the possibility that “a major part of it is unfalsifiable” and “elusive” and “so abstract and dependent on theoretical apparatus that it might be impossible to explain” (7), moots that possibility that CGG is post truth in that there is nothing (not much?) “at stake in determining which way of looking at things is the right one” (8), and ends with a parallel between Christian faith and CGG which are described as “not designed for falsification” (9). These claims, spread as they are throughout ILAS, leave the impression that CGG is some kind of weird semi mystical view (part philosophy, part religion, part science), which is justifiably confusing to the amateur and professional alike. Don’t get me wrong: ILAS can appreciate why some might find this obscure hunt for the unempirical abstract worth pursuing, but the “impulse” is clearly more Aquarian (as in age of) than scientific. Here’s ILAS (8):

I must admit, there have been times when, upon going through some highly technical, abstract analysis of why some surface phenomena in two very different languages can be captured by a single structural principle, I get a fuzzy, shimmering glimpse in my peripheral vision of a deeper truth about language. Really, it’s not even a glimpse, but a ghost of a leading edge of something that might come into view but could just as easily not be there at all. I feel it, but I feel no impulse to pursue it. I can understand, though, why there are people who do feel that impulse.

Did I say “semi mystical,” change that to pure Saint Teresa of Avila. So there is a lot to dislike here.[1]

That said, ILAS also makes some decent points and in this it rises way above the shoddiness of Evans, Everett and Wolfe. It correctly notes that science is “a messy business” and relies on abstraction to civilize its inquiries (1), it notes that “the human capacity for language,” not “the nature of language,” is the focus of CGG inquiry (5), it notes the CGG focus on linguistic creativity and the G knowledge it implicates (4), it observes the importance of negative data (“intentional violations and bad examples”) to plumbing the structure of the human capacity (5), it endorses a ling vs lang distinction within linguistics (“There are many linguists who look at language use in the real world … without making any commitment to whether or not the descriptions are part of an innate universal grammar”) (6), it distinguishes Chomsky’s conception of UG from a Greenberg version (sans naming the distinction in this way)  and notes that the term ‘universal grammar’ can be confusing to many (6):

The phrase ‘universal grammar’ gives the impression that it’s going to be a list of features common to all languages, statements such as ‘all languages have nouns’ or ‘all languages mark verbs for tense’. But there are very few features shared by all known languages, possibly none. The word ‘universal’ is misleading here too. It seems like it should mean ‘found in all languages’ but in this case it means something like ‘found in all humans’ (because otherwise they would not be able to learn language as they do.)

And it also notes the virtues of abstraction (7).

Despite these virtues (and I really like that above explanation of ‘universal grammar’), ILAS largely obfuscates the issues at hand and gravely misrepresents CGG. There are several problems.

First, as noted, a central trope of ILAS is that CGG represents a “challenge to the scientific method itself” (2). In fact one problem ILAS sees with discussions of the Everett/Chomsky “debate” (yes, scare quotes) is that it obscures this more fundamental fact. How is it a challenge? Well, it is un-Popperian in that it insulates its core tenets (universal grammar) from falsifiability (3).

There are two big problems with this description. First, so far as I can see, there is nothing that ILAS says about CGG that could not be said about the uncontroversial sciences (e.g. physics). They too are not Popper falsifiable, as has been noted in the philo of science literature for well over 50 years now. Nobody who has looked at the Scientific Method thinks that falsifiability accurately describes scientific practice.[2] In fact, few think that either Falsificationism or the idea that science has a method are coherent positions. Lakatos has made this point endlessly, Feyerabend more amusingly. And so has virtually every other philosopher of science (Laudan, Cartwright, Hacking to name three more). Adopting the Chomsky maxim that if a methodological dictum fails to apply to physics then it is not reasonable to hold linguistics to its standard, we can conclude that ILAS’s observation that certain CGG tenets are falsifiable (even if this is so) is not a problem peculiar to CGG. ILAS’s suggestion that it is is thus unfortunate.

Second, as Lakatos in particular has noted (but Quine also made his reputation on this, stealing the Duhem thesis), central cores of scientific programs are never easily directly empirically testable. Many linking hypotheses are required which can usually be adjusted to fend off recalcitrant data.  This is no less true in physics than in linguistics.  So, having cores that are very hard to test directly is not unique to CGG. 

Lastly, being hard to test and being unempirical are not quite the same thing. Here’s what I mean. Take the claim that humans have a species specific dedicated capacity to acquire natural languages. This claim rests on trivial observations (e.g. we humans learn French, dogs (smart as they are) don’t!). That this involves Gs in some way is trivially attested by the fact of linguistic creativity (the capacity to use and understand novel sentences). That it is a species capacity is obvious to any parent of any child. These are empirical truisms and so well grounded in fact that disputing their accuracy is silly. The question is not (and never has been) whether humans have these capacities, but what the fine structure of these capacities is.  In this sense, CGG is not a theory, anymore than MP is. It is a project resting on trivially true facts. Of course, any specification of the capacity commits empirical and theoretical hostages and linguists have developed methods and arguments and data to test them. But we don’t “test” whether FL/UG exists because it is trivially obvious that it does. Of course, humans are built for language like ants are built to dead reckon or birds are built to fly or fish to swim.  So the problem is not that this assumption is insulated from test and thus holding it is unempirical and unscientific. Rather this assumption is not tested for the same reason that we don’t test the proposition that the Atlantic Ocean exists. You’d be foolish to waste your time.  So, CGG is a project, as Chomsky is noted as saying, and the project has been successful as it has delivered various theories concerning how the truism could be true, and these are tested every day, in exactly the kinds of ways that other sciences test their claims. So, contrary to ILAS, there is nothing novel in linguistic methodology. Period. The questions being asked are (somewhat) novel, but the methods of investigation are pure white bread.[3] That ILAS suggests otherwise is both incorrect and a deep disservice.

Another central feature of ILAS is the idea that CGG has been getting progressively more abstract, removed from facts, technical, and stipulative. This is a version of the common theme that CGG is always changing and getting more abstruse. Is ILAS pining for the simple days of LSLT and Syntactic Structures? Has Okrent read these (I actually doubt it given that nobody under a certain age looks at these anymore). At any rate, again, in this regard CGG is not different from any other program of inquiry. Yes, complexity flourishes for the simple reason that more complex issues are addressed. That’s what happens when there is progress. However, ILAS suggests that contemporary complexity contrasts with the simplicity of an earlier golden age, and this is incorrect. Again, let me explain.

One of the hallmarks of successful inquiry is that it builds on insights that came before. This is especially true in the sciences where later work (e.g. Einstein) builds on early work (e.g. Newton). A mark of this is that newer theories are expected to cover (more or less) the same territory as previous ones. One way of doing this for newbies to have the oldsters as limit cases (e.g. you get Newton from Einstein when speed of light is on the low side). This is what makes scientific inquiry progressive (shoulders and giants and all that). Well linguistics has this too (see here for first of several posts illustrating this with a Whig History). Once one removes the technicalia (important stuff btw), common themes emerge that have been conserved through virtually every version of CGG accounts (constituency, hierarchy, locality, non-local dependency, displacement) in virtually the same way. So, contrary to the impression ILAS provides, CGG is not an ever more complex blooming buzzing mass of obscurities. Or at least not more so than any other progressive inquiry. There are technical changes galore as bounds of empirical inquiry expand and earlier results are preserved largely intact in subsequent theory. The suggestion that there is something particularly odd of the way that this happens in CGG is just incorrect. And again, suggesting as much is a real disservice and an obfuscation.

Let me end with one more point, one where I kinda like what ILAS says, but not quite. It is hard to tell whether ILAS likes abstraction or doesn’t. Does it obscure or clarify? Does it make empirical contact harder or easier?  I am not sure what ILAS concludes, but the problem of abstraction seems contentious in the piece.  It should not be. Let me end on that theme.

First, abstraction is required to get any inquiry off the ground. Data is never unvarnished. But more importantly, only by abstracting away from irrelevancies can phenomena be identified at all. ILAS notes this in discussing friction and gravitational attraction. It’s true in linguistics too. Everyone recognizes performance errors, most recognize that it is legit to abstract away from memory limitations in studying the G aspects of linguistic creativity. At any rate, we all do it, and not just in linguistics. What is less appreciated I believe is that abstraction allows one to hone one’s questions and make it possible to make contact with empirics. It was when we moved away from sentences uttered to judgments about well formedness investigated via differential acceptability that we were able to start finding interesting Gish properties of native speakers. Looking at utterances in all their gory detail, obscures what is going on. Just as with friction and gravity.  Abstraction does not make it harder to find out what is going on, but easier.

A more contemporary example of this in linguistics is the focus on Merge. This abstracts away from a whole lot of stuff. But, it also by ignoring many other features of G rules (besides the capacity to endlessly embed) allows for inquiry to focus on key features of G operations: they spawn endlessly many hierarchically organized structures that allow for displacement, reconstruction, etc.  It also allows one to raise in simplified form new possibilities (do Gs allow for SW movement? Is inverse control/binding possible?). Abstraction need not make things more obscure. Abstracting away from irrelevancies is required to gain insight. It should be prized. ILAS fails to appreciate how CGG has progressed, in part, by honing sharper questions by abstracting away from side issues. One would hope a popularization might do this. ILAS did not. It made appreciating abstractions virtues harder to discern.

One more point: it has been suggested to me that many of the flaws I noted in ILAS were part of what made the piece publishable. In other words, it’s the price of getting accepted.  This might be so. I really don’t know. But, it is also irrelevant. If this is the price, then there are worse things than not getting published.  This is especially so for popular science pieces. The goal should be to faithfully reflect the main insights of what one is writing about. The art is figuring out how to simplify without undue distortion. ILAS does not meet this standard, I believe.

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[1] The CGG as mysticism meme goes back a long way. I believe that Hockett’s review of  Chomsky’s earliest work made similar suggestions.

[2] In fact, few nowadays are able to identify a scientific method. Yes, there are rules of thumb like think clearly, try hard, use data etc. But the days of thinking that there is a method, even in the developed sciences, is gone.

[3] John Collins has an exhaustive and definitive discussion of this point in his excellent book (here). Read it and then forget about methodological dualism evermore.