There has been a development over the last 10-15 years or so in the scientific peer reviewed literature that is short circuiting the scientific method.
The scientific method involves developing a hypothesis and then seeking to refute it. If all attempts to discredit the hypothesis fails, we start to accept the proposed theory as being an accurate description of how the real world works.
A useful summary of the scientific method is given on the website sciencebuddies.org.where they list six steps
- Ask a Question
- Do Background Research
- Construct a Hypothesis
- Test Your Hypothesis by Doing an Experiment
- Analyze Your Data and Draw a Conclusion
- Communicate Your Results
Unfortunately, in recent years papers have been published in the peer reviewed literature that fail to follow these proper steps of scientific investigation. These papers are short circuiting the scientific method.
Specifically, papers that present predictions of the climate decades into the future have proliferated. Just a two recent examples (and there are many others) are
Hu, A., G. A. Meehl, W. Han, and J. Yin (2009), Transient response of the MOC and climate to potential melting of the Greenland Ice Sheet in the 21st century, Geophys. Res. Lett., 36, L10707, doi:10.1029/2009GL037998.
Solomon, S. 2009: Irreversible climate change due to carbon dioxide emissions. The Proceedings of the National Academy of Sciences. Published online before print January 28, 2009, doi: 10.1073/pnas.0812721106
Such studies are even reported in the media before the peer reviewed process is completed; e.g. see in the article by Hannad Hoag in the May 27 2009 issue of Nature News Hot times ahead for the Wild West.
These studies are based on models, of which only a portion of which represent basic physics (e.g. the pressure gradient force, advection and the universal gravitational constant), with the remainder of the physics parameterized with tuned engineering code (e.g see).
When I served as Chief Editor of the Monthly Weather Reviews (1981-1985), The Co-Chief Editor of the Journal of Atmospheric Sciences (1996-2000), and as Editor-in-Chief of the US National Science Report to the IUGG for the American Geophysical Union (1993-1996), such papers would never have been accepted.
What the current publication process has evolved into, at the detriment of proper scientific investigation, are the publication of untested (and often untestable) hypotheses. The fourth step in the scientific method “Test Your Hypothesis by Doing an Experiment” is bypassed.
This is a main reason that the policy community is being significantly misinformed about the actual status of our understanding of the climate system and the role of humans within it.
One thing that is becoming very evident in this discussion is that the term ‘model’ is used differently in different disciplines.
anna v (22:17:55) :
The harmonic oscillator is an idealized mathematical model for a real physical systems. You may choose to forget the origin and simply talk about the solutions for the linear equation, but that is pure mathematics and has no intrinsic meaning from a physics standpoint.
The physical interpretation comes from the original formulation for the model.
Regardless, many people do not appreciate that the differential equation itself is a model for a physical system. It is not a “real” thing, any more than a climate model is a “real” thing. The important thing is understanding the limitations of the model formulation and how far it can (or cannot) be extended.
From your point of view, is continuum mechanics a theory or not?
oms (19:28:56) : “I don’t understand this point. How does one “prove” this type of scientific theory without at some point writing down the equations and then computing them?”
A theory is proved through experimentation or observation. Models executed on a computer are neither experimentation nor observation. They are calculation. They represent what we know (or think we know) in mathematical formulas. You can’t prove a model in an absolute sense but you can ‘validate’ it by comparing its results against known results or observations. In this way you can gain confidence in the validity of the model.
I have this mental picture of Sir Isaac Newton trying to figure out gravity. He is watching an apple fall out of a tree or dropping objects from a tower. I picture him taking out pen and paper and scratching down formulas to represent what he was seeing and then using the formulas to calculate a result and then duplicating the result through experimentation. That is modeling and science combined in a way that makes sense. The only difference between now and then is that if he was alive now it is highly likely Sir Newton would use a computer to perform his calculations.
Models, being human constructs, are always limited by our understanding of what we are modeling. If you remember a while back there was a story on this blog about a group that built a model of the sunspot cycle. They apparently thought the model was pretty good and were able to accurately reproduce several previous cycles. But their projection of the current cycle missed significantly. Their model was flawed. It was likely a lack of understanding of the drivers of sunspots but possibly some flaw in the way the model was built. Regardless, I know of no theory that was proven or disproven by the failure of that model. The theory could be represented in the model but it would be proven or disproven only by what happened on the sun.
After the Space Shuttle Columbia disaster the company I worked for provided support for reconstructing the descent so that NASA could get an understanding of what went wrong. Using sensor data and known flight characteristics the team was able to construct a model that matched what was observed. The model was a significant piece of evidence used in the final findings report. The methodology used to generate that model was to examine the evidence, hypothesize what happened, model the result and compare it to known data. The resulting model, along with the results of several other experiments, led to the final conclusions.
With regard to your statement of climate models being “a bit more exploratory.” Computers are exploratory only to the extent humans program them to be exploratory. There is not an ounce of creativity in any computer on earth. There are some programs that do a pretty good impression of being intelligent but that is because there are some pretty smart and creative programmers out there. Don’t confuse the genius of the person or persons who created the program with the program itself.
In summary, a model is a representation of what we know. It can help us validate our understanding of what we are modeling but it can’t provide that understanding in the first place. I don’t think this contradicts what Mr. Pielke said.
oms (22:57:29) :
From your point of view, is continuum mechanics a theory or not?
From Wikipedia:
“Continuum mechanics is a branch of mechanics that deals with the analysis of the kinematics and mechanical behavior of materials modeled as a continuum, e.g., solids and fluids (i.e., liquids and gases). A continuum concept assumes that the substance of the body is distributed throughout — and completely fills — the space it occupies.”
OK, I can see the semantic overlap in this entry, since extensive use of mathematics is made.
IMO it is a sloppy use of the term modeling, rather a use before the extensive appearance of models as we know them currently. The write up demonstrates for me the insidious erosion of strict language definitions , and probably the entry is made by a Climate model modeler 🙂 .
I went through all my college and graduate studies physics books. The word “model” is not in any of the indices, so there is a fuzzy logic on this term that has appeared recently, as it is currently applied .
>> anna v (23:09:16) :
I do not think it is controversy, just a load of sophistry on semantics of what gravity is, a theory or a model.
from webster:
. . . . <<
What we need are better definitions:
Model:
A systematic description of an object or phenomenon that shares important characteristics with the object or phenomenon. Scientific models can be material, visual, mathematical, or computational and are often used in the construction of scientific theories. (See also hypothesis, theory.)
The American Heritage Science Dictionary.
Theory:
In science, an explanation or model that covers a substantial group of occurrences in nature and has been confirmed by a substantial number of experiments and observations. A theory is more general and better verified than a hypothesis. (See Big Bang theory, evolution, and relativity.)
The American Heritage New Dictionary of Cultural Literacy, Third Edition.
Jim
Paul Vaughan (22:34:14) : It is an administrative challenge – even a serious burden – for disciplines to support the development of well-rounded hybrids.
I don’t think this arts-sciences divide can be fixed by college administrators. It’s not just a problem in the education system. It’s much deeper than that.
Somebody wrote upthread about how they’d grown up reading about science in their youth, and they’d looked forward to it solving all sorts of problems. I was the same. But for all the people who are optimistic about science, there are plenty who are deeply pessimistic. While you or I might point to all sorts of scientific advances, they would point to weapons technologies and all sorts of downsides to scientific and technological innovation.
The rise of a romantic sensibility in Western societies over the past few centuries is an expression of this pessimism. Environmentalism entails a rejection of technological progress, and a nostalgia for a simpler, greener, rural society. While lots of people want to go forward, environmentalists want to go back to a world that isn’t a totalitarian dystopia of concrete and motorways.
This isn’t an education problem. It’s a deep cultural issue. One might even say that the science guys are the people who optimistically look forward, and the arts guys are the people who pessimistically look back.
I’m someone who has shifted from optimism (when I was reading Isaac Azimov) to pessimism (when I was 60s hippy), and then back to optimism. And I’m not quite sure how I managed it. But it seems to me that if you are, for one reason or other, deeply pessimistic about the future of humanity, then you tend not to have much interest in science, which is essentially optimistic (We can find out! We can understand the universe!), and you inhabit a backward-looking world in which your utopia was something we said goodbye to a few centuries back, if not a few millennia back.
I think scientists are natural optimists. But they’re surrounded by a sea of pessimists. And they’re now fair set to get drowned by the rising tide of pessimism. I can’t see that this tide of pessimism can be rolled back except by the optimists addressing the fears and worries of the pessimists, and showing them that things don’t have to go the way they fear. But I don’t see that happening. And so the pessimism of the pessimists just deepens.
post-modernism = pre-hunter-gatherer IMHO
there are various ways to consider the divide and I’m not sure art/science is necessarily a good one to use. da Vinci comes to mind. one I’ve seen used is a masculinism/feminism description which is based upon philosophical concepts rather than on sex.
Having seen a few examples of what passes for secondary education in the past year, the TX textbooks aren’t even a problem. As stated, they weren’t being used, despite being quite adaquate in the subjects which are not being taught, or at least not being learned. I’m sure though that the kiddies were learning all about how man was destroying the planet and about how the cute little cuddly polar bears were drowning to extinction, marooned on little icebergs. Those books actually did present the scientific method and all sorts of information in the hard sciences. I think most ofthe problem was that the teachers didn’t understand any of it, having been education majors in college. That was obvious because they talked to the kiddies in education language jargon that I needed to translate. My guess is that Koresh cult in Waco had better (real) science education that the public school classes I visitied last year.
As for computer simulations or video games being called models, there is even more of a problem. It seems that many video games actually do use modeling and achieve some reasonable level of accuracy in the simulations when desired. As much as I prefer to use the term video game to refer to GCMs, it is a bit of an insult to the video game industry and professional video game programmers to lump them together with GCMs.
Then again, these gcm’s are incomplete as there are details which are not known, theory wise. Perhaps GCIS should be used for the name – General Climate Imitation Simulation, being that it’s not a real simulation and the only thing actually circulating is the reasoning.
“Other societies are RAPIDLY overtaking us as we INFIGHT. Many of my students have been from societies with ’superior’ education systems. They STAGGERINGLY outperform locals …& with both ease AND grace. ”
I taught English as a Second Language at the college level for two years, and thus had the opportunity to learn from first hand accounts what kids study in other educational systems. I had a Japanese student tell me that what passes for College Algebra in many universities in the States dealt with subject matter that they were familiar with from the equivalent of 8th grade.
There was a piece on the news yesterday about the ‘problem’ of ‘diversity’ at the UC campus at Irvine, where 40% of the students are Asian-American. Californians, in an uncharacteristic fit of good sense, passed a referendum a few years ago banning race-based admissions, and one outcome of merit-based admissions has been that Asian-Americans now constitute a proportion of all UC students far greater than their percentage of the statewide population.
It seems to me that if I were teaching physics (God help me!) I would rejoice in seeing, on the first day of class, Chinese faces. I know that is a ‘positive stereotype’, but there it is.
What do we want, then, from our universities, especially in the natural sciences, ‘diversity’ or excellence?
“Wasn’t the author Thomas Hardy?”
No, not the author of ‘Daisy Miller’, who was Henry James. Winterbourne is the male lead in that story. He is in love with Daisy, in his own Winterbournish way; as his frigid name suggests, he is not a man aflame with Byronic passions.
I am sure our Winterbourne is quite otherwise.
” [Gravity] It is not a description, it is a generator of descriptions that fits all possible data. It is used in models but is not a model.’
Hmmm, reminds me alot of the theory of grammar in contemporary liguistics, i.e. ‘generative grammar’ a la Chomsky.
‘Rule-bound creativity’.
By the way, Leif Svalgaard may sleep better for knowing that I have decided that the best adjective to attribute to ‘theory’ is not ‘true’ but ‘most adequate’. That theory is most adequate which accounts for the phenomena in question in the simplest way possible (Occam’s razor). Presumably, a geocentric model of the heavens can come up with accurate predictions of the positions of celestial objects (after all, astronomers were able to predict eclipses 4,000 years ago). The problem is that the apparatus of the model is exceedingly complex, with epicycle within epicycle. Kepler and Copernicus ‘saved the phenomena’ with a much simpler model, and Newton’s towering genius saw that the motions of the planets could be accounted for by the same, breathtakingly simple law that governed the fall of apples.
‘Niels Bohr had a singular insight and capitalized on it his whole life.’
The ‘Bohr effect’ is often cited to illustrate the divide between theoretical and experimental physics. Supposedly, Bohr was so inept in a laboratory that all he had to do was pass by a lab for something to break down.
This essay, published nearly half a century ago, has become a cult classic:
http://www.dartmouth.edu/~matc/MathDrama/reading/Wigner.html
The author, Eugene Wigner, opens with an eloquent quotation from Bertrand Russell (give that devil his due).
“Mathematics, rightly viewed, possesses not only truth, but supreme beauty, a beauty cold and austere, like that of sculpture, without appeal to any part of our weaker nature, without the gorgeous trappings of painting or music, yet sublimely pure, and capable of a stern perfection such as only the greatest art can show. The true spirit of delight, the exaltation, the sense of being more than Man, which is the touchstone of the highest excellence, is to be found in mathematics as surely as in poetry.”
David Holliday (23:03:02) :
You might take a numerical simulation as the high-ticket version of what used to be called a “thought experiment.”
Suppose so-and-so happens, we have three gravitational bodies or two twins or maybe one rise in CO2… if we just put that into the machinery, whether it be a variational principle or Lorentz transforms or some huge hodgepodge of parameterizations, what does the amalgamation of theory say will happen?
And I think we are in agreement that, as far as the “experimental” design is concerned, we ought to try to think up an experiment which confirms/disconfirms some portion of the underlying theory before we get ahead of ourselves.
I think we rarely (if ever) do any physical computation which uses our “full” knowledge. Always there are approximations made, guesses on the boundary conditions, unwanted scales and nonlinear terms tossed out, etc. For example, the Euler equations are already strictly “disproven” for physical fluid flows, since we know that viscosity exists; yet they remain a model which seems valid until… well, until the limits of the model. At that point it helps a great deal if one has not forgotten how the model was constructed in the first place.
The exploratory was in reference to their relevance in climate science. Climate models are useful for exploring the parameter space in a way that we (obviously) can’t do.
Arthur Glass (06:32:42) :
By the way, Leif Svalgaard may sleep better for knowing that I have decided that the best adjective to attribute to ‘theory’ is not ‘true’ but ‘most adequate’. That theory is most adequate which accounts for the phenomena in question in the simplest way possible (Occam’s razor).
with one modification: the theory must also have predictive power. The simplest theory [‘most adequate’ in your terms] is that Angles push the planets around according to God’s wishes, end of story.
anna v (23:30:33) :
Perhaps the traditional distinction is between “theory” and “observation.” And since most of my college and graduate physics and math textbooks seem to be about “theory,” I guess they wouldn’t spend much time talking about the distinction. 😉
“Model” with a capital “M” seems to be a most recent buzzword, yes.
Arthur Glass (06:32:42) :
Presumably, a geocentric model of the heavens can come up with accurate predictions of the positions of celestial objects (after all, astronomers were able to predict eclipses 4,000 years ago). The problem is that the apparatus of the model is exceedingly complex, with epicycle within epicycle.
Ironically, modern practicing astronomers [and engineers – at JPL] do not care one whit about philosophical issues and have resorted to the epicycle within epicycle within epicycle within epicycle within epicycle … formalism. An abbreviated description of Jupiter’s motion [which is enough for ordinary navigation – the full theory has an order of magnitude more terms] operates with 498 epicycles…
Arthur Glass (06:32:42) :
reminds me alot of the theory of grammar in contemporary liguistics, i.e. ‘generative grammar’ a la Chomsky.
Ah, the philosophy of language. a bit like going to a good restaurant…
And eating the menu.
😉
Arthur Glass (06:32:42) Newton’s towering genius saw that the motions of the planets could be accounted for by the same, breathtakingly simple law that governed the fall of apples.
And then along comes Einstein and upsets the apple cart with a fudged up crock of an explaination of the anomalous perihelion of Mercury.
What a thread!
@ur momisugly Jim Masterson (00:00:07) :
“Theory:
In science, an explanation or model that covers a substantial group of occurrences in nature and has been confirmed by a substantial number of experiments and observations. A theory is more general and better verified than a hypothesis. (See Big Bang theory, evolution, and relativity.)
The American Heritage New Dictionary of Cultural Literacy, Third Edition.”
There is that word model right in the definition of theory!!!
Whats going on here? So when I use math to predict the effects of a theory its not a model?
What I do is use math to predict how trace elements will behave in crystallizing magmas. All of the equations I use are based on the variables of those trace elements (size, charge, etc) and the composition of the magma, as well as the composition and modal abundance of the minerals that are crystallizing (woefully simplified description). So is this a model Anna? I would say yes without a doubt!
So there is a theory that dictates how elements will behave when forming minerals. I use math to model this behavior, but in one sense its just a model and not a theory? Or is it more complex than that? Models are a part of theories? Or is anytime a model is employed, its not a theory? Perhaps we need a new set of language here to say that some models are super duper (F=ma or F = GMm/R²) and some models (that we don’t like, like climate models) should be called something else?
I guess its my belief that anytime we try to simulate, or predict processes in the natural world we employ Math, and that math is a model!
Apparently I am wrong?
I am not trying to say theory and model are interchangeable. I am saying that we use models for the predictive aspects of theories. I am saying that in most cases, the theories we have come to love and know rely heavily on models for us to be able to use them.
And in reality, my original comments were to point out how silly it was for David Holliday (19:15:47): to say “Anyone who thinks a prediction based on a computer model is science is an idiot!” because computer models permeate almost every single field of science.
Benjamin P. (10:09:34) :
What a thread! […]
computer models permeate almost every single field of science.
Amen!
@Benjamin P. (10:09:34) :
Your crystallizing magma models are heavily constrained by known properties of elements, compounds, minerals, the rock cycle and the phase relationships within various different melts (brings back 30-year old phase diagram nightmares from igneous petrology).
General Circulation Models can’t really be so accurately constrained by known parameters. We don’t have enough observational experience with climate change to know how the models should work. The effects of important factors like clouds and water vapor are poorly understood. GCM’s are fine heuristic tools…But I don’t think they are comparable to the types of models used in petrology.
My POV on this
1) Let us take a langrangian that describes a theory.
2) From that Lagrangian we derive the equations of the theory.
3) Equations are differential ones and have to be integrated.
4) For specific problems, one has to take the solutions and impose boundary conditions so as to get values that can be compared with experiments.
Steps 3 and 4 are tools that allow the theory to be projected on the real world and models are used for this purpose extensively after the advent of computers. Since 1977 I have worked with Monte Carlo models. I never confused them with theory. I knew they were integration tools used judiciously to predict/fit experiments to solutions of the theory under consideration.
GCM include not only integrations (numerical ones) but also boundary conditions. In no way one can confuse them with the theory used.
BTW a theory can never be proven true. It is always up for falsification though. One contradiction can falsify a complete theory : a yoggi levitating for example.
idlex (02:29:10) “I don’t think this arts-sciences divide can be fixed by college administrators.”
Agreed …but there will eventually be a change-of-the-guard.
Also:
The divide is not just on one axis – the worst divides I’ve seen are between branches of science.
We are discussing several problems here — one of which is growing cynicism towards science-publication peer-review processes.
Maybe things look a little different from inside the education system. Students from non-science backgrounds are eager to learn & appreciate. They want to understand math & stats. The negative attitudes are born out of a system that fails them. (Let’s keep in mind that they are paying customers.)
If universities are only supposed to be ‘centres of excellence’, then our society has a serious problem in achieving its full potential. My experience has been that it is not the ‘excellent’ people who need help in understanding & leading. Resources are being allocated neither strategically nor equitably; while benefits go to very few, the cratering impact of the short-sighted squandering is on not only society, but even more critically on society’s potential, which is seriously reduced by unchecked idealism.
Brilliant leaders can’t do everything alone – they need armies of level followers who have the background they need to harmoniously & efficiently follow a valid argument. The divide of which you speak is a discord that need not exist; it is born out of the (organizational) nature of our education system.
As an anecdote:
I live in a jurisdiction with a carbon tax. It’s not what it seems (i.e. all about GHGs & warming) — it’s actually a deficit-&-traffic-fighting tool that is being wielded like a baseball bat. And trust me: The folks supporting it LOVE TECHNOLOGY, INDUSTRY, & CARS and aren’t terribly concerned with pollution that is not in their own back yard.
Gilbert (13:08:43) :
E.M.Smith (02:58:07) :
Wow!!!
Another rant like this and you will be well on your way to becoming my hero!
Thanks! (blush!). I just have a necessary and non-negotiable need to be brutally true to myself. The quickest way to lose money trading is to believe your own BS. To fall in love with a beautiful thesis and ignore when it is going wrong.
While it is impossible to avoid having a thesis, there is a very important market aphorism: “The first loss is the best loss.”
What this means is if I bet it will be warmer and Canada will have a bumper wheat crop, as soon as the data show it’s not warming and as soon as the prices start going the “wrong” direction: Step Aside. Just Step Aside. Take your loss, early and fast, and don’t think twice about why. AFTER you step aside, then you think about why and how to do the next trade better.
The longer you fret over how it just can’t be that way and you MUST be right, the more money you will lose. Period.
So what I see in the AGW crowd is a large and growing degree of self deception (not a judgmental term. EVERYONE is prone to self deception. It’s the hardest thing to iron out of yourself for trading discipline. “I” don’t exist and what “I” want means nothing to me… which makes it all the more funny to me when an AGWist accuses me of having an “agenda”… ) I also see an ever more panicked state as the AGW “trade” is going against them with the present climate / weather roll down into an Oh My God cold few winters to come… and no ability to “Take the first loss”. They are going to ride this puppy down into a horrid crash in a cold bitter end. OK, I did my moral duty to tell them; now I’m going to make money off of them.
Now I’ve spent close to 40 years developing a set of techniques for spotting trend reversals in highly noisy semi-stochastic data series. This means I’m a bit better than most at “calling a top” or “catching a bottom” (which is why I can make a living doing it against the best computer models money can buy at Goldman Sachs et. al. – it is literally “Me against the world” for a single trader with a lap top and a small stake – i.e. 6 figure, not 7… yet) so I fully expect to be:
1) Way ahead of the bulk of everyone else to see a turn. I must be to win.
2) Due to #1 – I will almost always be “outside the consensus”. Makes me just shake my head and chuckle when folks use “consensus” as a reason to believe AGW. I reliably use “consensus” as a warning flag to dump a position…
3) Due to #2 – Regularly told I’m wrong, an idiot, doing crazy things, stupid, etc. It isn’t a popularity contest and what folks think of my trades does not make me any money…
4) Due to #2 and #3 – I can’t let myself be driven by social or political motives. They would only “dirty up” my thinking about what will happen not what folks want to have happen. Neither pro “consensus” nor anti.
5) I’ve noticed the same techniques seem to work with temperature series.
6) Due to 1 – 5 I need to do much more complete and through analysis than most folks, i.e. work my butt off against negative sentiment, to win.
Given that: At this point, my belief is that the 30 year warming trend we had, has flipped to cold. It’s going to be cold for the next 30 years. There is an unknown, but possible, risk of a major cold as in little LIA but time to adapt as it evidences itself. The U.S. Government is headed off a cliff, partly based on the AGW nonsense, so you can be run over by that stupidity or you can position to take advantage of it and make some lunch money.
Easy to see? China, Russia, Eastern Europe (“emerging Europe”) all DISing AGW. They have clue. China and Russia DISing the U.S. Dollar and the overuse of the credit card of bonds. They have clue. Canada and Argentina having crop “problems” and a month early start of ski season in Australia and New Zealand. There’s a clue for you. Oh, and India and Brazil get a free pass on GW mitigation… So the E.U. and U.S.A. will take on $Trillions of debt and costs that Russia, China, Brazil, and India will not, based on a wrong thesis and timed exactly wrong – and done on the credit card.
I think I can make a trade out of that… (I’ve already had a “double” out of Brazil. It will likely hold flat for a while as India has become hot, then resume the up run in a couple of months. I’m reducing my position (rolling 1/2 into India) but not selling out. [ I have a trade rule: On a double, sell half. Non-negotiable rule. It’s not what I want, it’s what I must do…] And grains are shaping up for a nice rise as the crop failures get confirmed.
Though the recent election in Great Britain means they seem to be catching a clue… and I might need to look to buying into some LSE stocks. (London Stock Exchange…) We’ll see. It’s still a bit early. But the elections in India and G.B. put them both back on the radar as “Have Clue”…
So you see, I didn’t see that prior posting as so much a “rant” as being “absolutely and brutally honest to myself” … “To thyne own self be true” has a couple of meaning…
“I don’t think this arts-sciences divide can be fixed by college administrators.”
From my experience, all college administrators do is go to conferences onon ‘diversity’ and compose long, jargon-clotted, subliterate memos that no one ever reads. They have no more energy or capacity to fix anything than does a sloth hanging from a branch.
A ‘divide’ can only exist between two items. The rigorous natural sciences are thriving; the liberal arts, on the other hand, have been so eaten away by the termites of ideology (Black Studies, Gender Studues, Queer Studies) and post-modernist incoherence, that there is little left that is living. At many universities, you can get a Bachelor’s in English without having read a word of Chaucer or Shakespeare, Milton or Joyce. You cannot, however, avoid such luminaries as Toni Morrison or Rita Dove. You may be blissfully ignorant of the criticism of Johnson, Coleridge, Matthew Arnold and T.S. Eliot, but you can jabber on like a parrot about Barthes, Derrida and Foucault.