Archive for the ‘Science’ Category

Think first about the following question: Why do we take seriously the claims to approximate truth of many natural scientific theories? We do so, in my view, mostly when such theories make predictions about observable phenomena that exhibit accuracy, precision, reliability, etc. These qualities do not exhaust the virtues of good natural scientific theories, but when a theory enjoys them to a great extent, its verisimilitude is hard to deny. The striking fact of a theory’s extraordinary predictive success cries out for explanation. The only non-miraculous explanation for this success, really, is that it is approximately true. A theory may have other features to recommend it, even if its predictions come up short, but the less compelling a theory’s predictive track record, the easier it is to explain its good qualities without invoking its approximate truth.

What, then, should be our view of social scientific models, the overwhelming majority of which fail to meet ordinary natural scientific standards of predictive success? If a model is internally consistent, then it correctly describes some possible world. One view of good social scientific models is that, even though they do not correctly describe our world (perhaps due to intrinsic complexities in our world), they correctly describe very similar (but much simpler) worlds. The natural sciences take this approach from time to time. Consider the ideal gas law—no one seriously believes that any gas in our world is ideal in the relevant sense, but most chemists believe that the world of ideal gases is very similar to our world. Social scientists may defend a model, knowing that it is not strictly correct in every particular, by insisting that the world of the model is so similar to reality that the model is still of great scientific value.

One problem with this defense is that the ideal gas law, like other successful natural scientific theories, makes very, very good predictions. Such successful predictions are very few and far between in the social sciences. If social scientists want to persuade others of the similarities between the worlds of their models and the real world, predictive success has to be the centerpiece of their argument.

A second, perhaps more serious problem with this defense is that social scientific models frequently incorporate ideas that we not only know to be false, strictly speaking, but also know to be not even approximately true. In rational choice models of human decision-making, for example, it is supposed that humans have complete, transitive preferences over their options. We know this is not true—indeed, we know this is not even approximately true.  Yet it continues to maintain a remarkable presence in many prominent social scientific models. Examples of this kind severely undermine the case outlined above for garden variety models in the social sciences.

If social scientific models do not qualify as successful scientific descriptions of our world—indeed, not even approximately true abstractions—then what ought we to make of them? The key to understanding social scientific models, in my view, is to recognize that many phenomena of interest need not occur only in our world, or only in very similar worlds. It is conceivable, for example, that recessions much like the ones that take place from time to time in our world take place from time to time in other, very different worlds. Some of these worlds may be much simpler than the real world, in that they obey only a handful of basic laws. Studying the properties and behavior of recessions in these worlds is more feasible than doing so in the real world, in which they co-occur with countless other complicating factors, even if these worlds have little else in common with the real world.

The challenge with investigating recessions in very different worlds is that features of recessions in those worlds may not carry over to the real world. These features may be intricately linked with the world in which they’re embedded, a world very different from our own. This is why robustness is important in such investigations. If we study a range of worlds that differ from each other along many of the same dimensions along which they each differ from the real world, then we may conclude that robust features of the phenomena being studied can conceivably carry over to our world, even if every world we study happens to be very much unlike our world.

As social scientists produce many such characterizations of phenomena of interest, each of which has properties and behaviors that do not necessarily depend upon the idiosyncrasies of the worlds in which they’re being studied, these characterizations may be compared with respect to their likeness to real world phenomena. The closer the match, the more compelling the characterization—though short of meeting ordinary scientific standards of predictive success, these characterizations need not enjoy the epistemic credentials of established physics, chemistry, etc.

On this understanding of social scientific models, it makes sense to separate two distinct kinds of debate. The first concerns the extent to which the account of phenomena embedded in the model corresponds to reality. The second concerns the extent to which the world of the model is a suitable environment in which to study the phenomena of interest. Note that this does not include debating the extent to which the world of the model corresponds to reality. The greater the extent to which this is the case, the better (of course), but the cost of this is typically greater analytical complexity. In light of this, it seems appropriate for some researchers to err on one side of this tradeoff, while the rest err on the other side.

This may not be the only way to do good social scientific research. This may not even be the best way to do social scientific research. It is, however, one way—one that is practiced much more often than other ways in some social sciences (e.g., economics), while playing a more minor role in others (e.g., cognitive psychology). In the end, I’m a pluralist. No one way of conducting social scientific inquiry has proven its worth to such a degree that other ways must be swept into the dustbin of history. The ‘model phenomena realistically, albeit in unrealistic settings’ method, if you will, has its limitations, to be sure, for which it ought to be criticized, if only to keep researchers’ eye on the prize, but it has something intellectually valuable to offer, too. Proponents of this approach do not consistently practice what they preach—this, too, ought to be extensively criticized—but when they do, they frequently yield novel perspectives on challenging problems, insights into which are always welcome, however they may be found.


The new riddle of induction

Posted: February 10, 2012 by alephnaughty in Philosophy, Science
Tags: , , ,

Suppose every blueberry you’ve observed to date has been blue. You take this to be evidence for:

(H1) All blueberries are blue.

As a consequence, you predict:

(P1) The first blueberry I observe on February 11, 2012 will be blue.

Now, define “bleen” to mean “blue until February 10, 2012–green thereafter”. By this definition, every blueberry you’ve observed to date has been bleen. You take this to be evidence for:

(H2) All blueberries are bleen.

As a consequence, you predict:

(P2) The first blueberry I observe on February 11, 2012 will be bleen.

A blueberry that will be bleen on February 11, 2012, though, will be green–not blue. Thus, (P2) flatly contradicts (P1). Is there any evidence that favors (H1) over (H2)? We might complain that (H2) is couched in terms of a derivative property–“bleen” is defined in terms of “blue” and “green”. We might take this observation to favor (H1), and therefore (P1).

But define “grue” to mean “green until February 10, 2012–blue thereafter”. Imagine a culture that only understands “bleen” and “grue”–not “green” and “blue”. To them, “green” means “grue until February 10, 2012–bleen thereafter”, while “blue” means “bleen until February 10, 2012–grue thereafter”. Their complaint about (H1) is that it is couched in terms of a derivative property–“blue” is defined in terms of “bleen” and “grue”. They take this observation to favor (H2), and therefore (P2). Could we really be right, and they really be wrong?

What else could favor (H1) over (H2)? If nothing, isn’t this a problem for every hypothesis of the form “All X are Y”? And don’t we (implicitly) make predictions founded upon such hypotheses in our everyday reasoning? Doesn’t this problem undermine the very way in which we learn from our observations and experiences?

Nukes for the environment

Posted: February 9, 2012 by nullpointerexceptional in Politics, Science, Very important
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So the US approved the first nuclear reactors since 1979 with the Three Mile Island boogie. The real question is why this is the first approval since then? Why does this approval come so close to the near catastrophe in Japan? Heck Germany (the ones trying to tell everyone else how to run their balance sheets) has gone as far to say they are going to shut down all of their reactors to avoid the same potential fate as Japan. Now that the approvals are out in the open, I suspect you’ll start seeing more sensational news reporting on radiation leaks at existing plants – heck in VT there were reports of radioactive fish being caught right outside the cooling towers sparking mass hysteria. A majority of media outlets are leaving out details, such as testing at the facilities report no radiation leaks and that other fish in the same stream at the other end of the state, 150 miles away, have the same radiation levels – good little tidbit which changes the severity of the situation. Not to mention, in America we don’t build reactors on fault lines or earthquake central.

Not all that long ago, I lived 10 miles from an aging plant. Sure it wasn’t the greatest landmark the area has known, but I really didn’t mind it. Some of my lesser intelligent friends were even concerned for my life, I was moving so close to a reactor after all. These same friends also think that radiation causes three legged frogs and birth defects: lead and fertilizers cause that stuff, all radiation does is kill you or give you cancer. All I have to say is it’s about damn time the flukes on capital hill moved along something that is actually beneficial to the prosperity of this great nation. There has never been a better thing for the environment than nuclear power – it’s basically steam on steroids. No real waste products, no hazardous green house gases and jigga-what-whats (see what I did there?) of power for the masses. Sure you need to bury the spent fuel rods in barren deserts forever, but is that really all that bad?

All I can say is, mother nature loves nuclear power and I’m sure the tree huggers are loving this. Plus it just might drive the cost of electricity down to where plug-in electric cars are cost effective in a person’s lifetime.

Suppose I have two containers, both full of (what I believe to be) a single fluid. Each container’s volume is 500 mL. I then empty the contents of the two containers into a third, the volume of which is 1000 mL. To my surprise, the container is only 75% full–it holds just 750 mL of the fluid. How should I revise my beliefs in light of this discovery?

Among my presumptions was that volume is additive when mixing a single fluid. One conclusion that suggests itself is that the two containers in fact contained different fluids. Another is that volume is not necessarily additive.

A third conclusion, however, does not suggest itself: 500 + 500 = 750. Why not? What is it about 500 + 500 = 1000 that justifies my willingness to concede that the fluids were different, or that volume is not necessarily additive, but not that 500 + 500 = 750? The surprising outcome of my experiment shows that at least one of my presumptions is incorrect, but it does not indicate which. What is it about this experiment that prevents it from lending support to the hypothesis that 500 + 500 = 750?

…that we nailed Nevada, Groundhog Day, and the Super Bowl winner. So…word to ya motha.

Onto Colorado and Minnesota we go:

1st: Rom Mittney

2nd: Sant Rickorum

3rd: Ging Newtrich

4th: Pan Roul

Same for bof states. Be amazed, y’all.

Groundhog Day 2012 prediction

Posted: February 1, 2012 by pleonasty in Important, Science
Tags: ,

Punxsutawney Phil, perhaps the most famous groundhog (aka whistle-pig), is due to make his appearance this Thursday, Feb. 2nd. The appearance the country is really awaiting with bated breath is that of his shadow.

The grand holiday of Groundhog day takes its roots from a similar European tradition, wherein a badger or some other non-groundhog little rat guy comes out, does a little dance and then the elders determine whether or not you’re going to need to wear a parka for the next few days. The American version of this exciting time dates back to as early as the mid-19th century in the middle of nowhere, Pennsylvania. Since then, many cities have adopted their own groundhog to come out and try to spy his shadow. However, Punxsutawney Phil, or Seer of Seers Prognosticator of Prognosticators Weather Predictor Extraordinaire as he’s sometimes known, is by far the most revered. He is so revered, in fact, that the so-called Inner Circle was established to protect and advise him. The Inner Circle is comprised of 15 members with such meaningful titles as “Stump Warden,” “Thunder Conductor,” and my personal favorite, “Big Chill.”

(SPOILER ALERT: If you do not wish to know the outcome of this year’s coming Groundhog day, navigate yourself away from this page. Perhaps one of our other gripping and timely posts would better interest you and possibly your friends.)

Here at Defeasible Reasoning, we take pride in knowing things before you do and then rubbing your face in it telling you about it. To that end, we’ve pored over recent trend data to bring you such predictions as the outcome for the Florida Republican Primary and the Nevada Republican Caucus. Whether Punxsutawney Phil will see his shadow is equally important. After months of observing the trends in atmospheric pressures, barometric altitudes, cloud form patterns, Sun illumination angles and temperature inversion data, we’ve come to the conclusion that Punxsutawney Phil will indeed see his shadow at approximately 7:22am EST. Go get those heavy winter coats out of the attic, folks, it’s going to be a 6 week longer Winter.



EDIT: As predicted, Punx Phil crawled out of his hidey hole to be surprised by his shadow, thus predicting 6 more weeks of Winter. You’re welcome for the heads up.

There are two kinds of Americans. The first are autistic. The second are drunk, drugged up, and manically depressed. Why? Don’t ask me. But, here’s a theory: the economy hates the second group, just like you hate your drunk, drugged up, and manically depressed cousin (and yes, the Oxford comma is absolutely essential) who just eats all your food and complains about life being unfair.

Now, Mr. Scientist (you might say), what use is this theory? Just seems like you’re hating on people who already hate themselves. Well, I am doing just that. But, I’m also doing science. If my theory is right, here’s a prediction it makes: the second group has shitty economic fortunes compared with the first. Ta da…

From personality to neuropsychiatric disorders, individual differences in brain function are known to have a strong heritable component. Here we report that between close relatives, a variety of neuropsychiatric disorders covary strongly with intellectual interests. We surveyed an entire class of high-functioning young adults at an elite university for prospective major, familial incidence of neuropsychiatric disorders, and demographic and attitudinal questions. Students aspiring to technical majors (science/mathematics/engineering) were more likely than other students to report a sibling with an autism spectrum disorder (p = 0.037). Conversely, students interested in the humanities were more likely to report a family member with major depressive disorder (p = 8.8×10−4), bipolar disorder (p = 0.027), or substance abuse problems (p = 1.9×10−6). A combined PREdisposition for Subject MattEr (PRESUME) score based on these disorders was strongly predictive of subject matter interests (p = 9.6×10−8). Our results suggest that shared genetic (and perhaps environmental) factors may both predispose for heritable neuropsychiatric disorders and influence the development of intellectual interests.

You know whose economic fortunes are better than humanities majors? Science majors. Just look at those p-values. Hot damn. I didn’t pay much attention in AP statistics (I just remember gems like “power is desirable”, and “we want small Ps”), but this looks pretty sciency to me. And the authors are from Princeton!

OK, so, my theory sucks. Granted. But how about them p-values? And for the record, I belong to the first group, have shitty economic fortunes, and I spend my days eating other people’s food and complaining about the unfairness of life. I am the two Americas.