Physical scientists are well aware that only some areas of their disciplines are prescriptive and others remain descriptive, as they once were entirely. The difference is they can admit to uncertainty, in fact they have to seek it out for Ph.D thesis subjects.
The less firm the understanding social scientists have of cause and effect, the more adamant and defensive they are of their conclusions. They could be safely left alone to bicker if they weren't trying so hard to impose public policy.
A lot of astrophysicists will be relieved to hear that. And tell Clarke, while you're at it.
I'm waiting for the other shoe to drop here...
[clunk!]
Is that a testable hypothesis? d8-)
Your perception that they're "trying hard to impose" is not my perception, but vive la différence.
There's a lot more to be gained by noting the similarities between physical sciences and others before focusing on definitions and putting fields of science into boxes. All science at the frontiers is a blind seeking, and what is sought first is descriptive and analytical. When a cosmologist doesn't know what he's looking for (the source of dark energy, for example), he's at least as much in the dark (sorry for the pun) as an economist who's trying to analyze risk aversion. It turns out that understanding risk aversion is a matter of social psychology, so the economist gains understanding by fishing in the dark until he gains an insight -- in this case, the insight that another field of science can identify the phenomenon that's perturbing his analysis. He was looking for something along the lines of "rational action" -- the economist's traditional turf -- until he realized he was looking in the wrong place. Great science is done by the scientists who have the unanticipated insights and look in unsuspected places: charmed and blessed guesswork, as some of them have said. Risk aversion is not so lofty as a subject, but seeking insights outside of deductive science can be very lofty indeed.
Instrumentalism and its exclusive focus on testable hypothesis and predictability has a congealing effect on the mind. At the frontiers, not much is instrumental. It's mostly jazzing around by brilliant people. Then come the hypotheses. Sometimes they're even testable. Then the brilliant science enters the slog of empiricism and dreary labwork. Some engineers who look at science through their own set of lenses come to believe that it isn't science if it doesn't produce testable hypotheses that enable reliable predictions. They're wrong, of course. Within their narrow working world, almost everything is testable and will lead to predictability. But science is much larger than that.
When will astrophysicists be able to test the hypothesis that those distant planets they're discovering among the stars will have not only the conditions for life, but life itself? Maybe never. The planets are too far away. The means to detect life on them may never be found; a method may not exist at all. If they're never able to predict the existence of other life with certainty, will we decide someday that they weren't really scientists at all?
Of course not. Likewise, the social scientists who seem *always* to be on their frontiers, because they are limited in how they can detect and measure the effects of vast numbers of variables -- complexity. And, like quantum physicists, they're also dealing with random events and perturbations of unknown complexity -- the butterflies flapping their wings in Brazil, the unknown unknowns. Are they fractal or simply chaotic? Is there a way to test it? To make predictions?
Maybe, maybe not. Meantime, we go with the best knowledge we have, like doctors using the best antibiotics they know of to cure diseases on which those antibiotics don't work. We try our best. So do other life scientists, and social scientists.
We're the ones who press them for answers, not the other way around. We always want answers and we blame the sociologists, or the economists, or the medical researchers, for not having the answers we want. When they take their best shot and it doesn't work out, we blame them for imposing their policies on us.
But the political process is how we decide upon policies. The social sciences and life sciences just provide the best current knowledge. Sometimes -- often -- it's wrong. But it's the best we have. What's the alternative? To rely on complete ignorance?
Have you studied Chemistry? The texts are thick with Mix A with B to get C with little or no explanation of the thermodynamics that determine a reaction's stable end point. We learned that separately, but much of it was extensive memorization of complex details and procedural rituals, appropriate to Harry Potter or Paracelsus.
OTOH physics and electronics are very deterministic, testable and intensively complex. Mechanical engineering is in between because you are rarely certain of a material's properties.
Sure. Those are the physical sciences in which predictions and testing hypotheses are easiest. The whole point of this discussion was that there is more to science than that.
I can't speak to chemistry but electronics is, as you say, very deterministic. And it's not all that complex. Networks and filters can get hairy, with many interactive variables, but most of it is manageable by anyone who has studied it seriously. That's not the case when you're trying to determine the influences on consumption or financial trading, for example.
The point that started this is that applying the statistical and calculus tools of econometrics to data in political science has elevated the latter to a level of study that is truly scientific. Not all of poli sci or economics are subject to numerical or scientific methods, but applying those tools has opened a whole new level of understanding to some aspects of each.
If you think electronics isn't all that complex then you've never seen digital communications theory, which has spawned whole new branches of mathematics.
Simple telephone network design problem. Q: When is the system most congested? A: Mother's Day Q: What happens if the switch matrix that connects calls is too small? A: Callers who don't get a dial tone become very angry. Q: What is the correct response? A: F..k 'em, we're the phone company, we don't have to care.
Although that's a standard joke the problem of predicting statistical calling behavior in order to economically size the system for an acceptably small no-connect rate is real, and difficult.
An FAA system I worked on was like an aerial party line with every airliner radio yelling "Here I am" at once on the same channel. It attempted to resolve the confusion with a more sophisticated version of Ethernet collision detection. For that one the consequences of failures were a little higher. I was the hardware tech and don't claim to understand the math of it.
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I realized I was over my head on the complex problems when the guest lecturer from Qualcomm asked for a numerical energy value for the difference in entropy from a change in the number of possible states of a digital encoding scheme.
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's used in your cell phone.
This stuff is so far beyond instrumental determinism it might as well be from Star Trek.
Fine, you believe that something that does not produce falsifiable models is "science". Among philosophers of science I think you'll find yourself in the minority.
Certainly it's very complex, but electronics carried the mantle of objective, physical science long before digital technology became the mainstream.
Complexity may be a difficult basis on which to make the distinction I'm trying to make. Maybe a better way to put it is that electrical phenomena behave according to relatively simple laws of nature, even when those laws are woven into complex interactions and quantum effects or other uncertainties that involve probabilities and that require statistical treatment.
But electrons don't have bad-hair days, nor do they make a run on the bank when some talk-radio crackpot spreads a rumor on the air. They don't all decide to pile up on the starboard side of a microchip for unanticipated reasons and make it capsize.
So the number of variables involved in an econometric analysis is not only huge, with ever-changing cohorts of group behavior, but it's different every time -- the behavior itself is ever-changing, too. For the most part, electrons do the same thing every time, at least in groups larger than a couple of dozen taken at once.
Which is more complex to identify, measure, and implement in a model or even an observation? I'd vote for those things that involve human behavior. In the middle are those sciences that investigate other forms of life.
Ok, but the problem as you pose it is an economic problem, in the sense that Steven Levitt is an economist. In other words, if one is a business analyst or other researcher studying the problem, the methods they would use are the modern tools of econometrics.
Right. Now, relating it to the discussion, those are problems in probability that are the same kind of stuff that econometrics tries to model. Again, dealing with human behavior as a key part of the variables, the levels of certainty are much lower in economics. But statistical evaluations are a facet of science that's common among social sciences and the probabalistic side of the physical sciences.
To go back to the original point I disagreed with, the idea that something isn't science if it can't produce testable models is simply wrong, historically and in contemporary practice. And the reason that the physical sciences are more able, more often, to produce such models is not that they are "superior" sciences. It's because the things they study always behave the same, even if the sameness is some statistical value. When the singular or collective behavior of human beings are the subjects, or part of the subjects, that's rarely true. But those studies are still scientific in every essential meaning of the word, which is an elaboration on the ancient idea that science is a systematic investigation to increase the store of knowledge.
IIRC in the Ringworld series Larry Niven comments that engineers and lawyers solve similarly difficult problems, except that an engineer's problems don't actively evade solution. Then he mostly disproves that statement.
As I think you see now the science I'm familiar with encounters the same issues as the social sciences when policy makers seek and employ their advice as the rationale for expensive and nationally significant decisions, both socially and technically oriented.
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I was a lab manager there, not involved in decisions but not ignorant of them either, and also as an amateur historian I've investigated the background of air power and military electronics systems development. Currently I'm researching and debating the tradeoffs of WW2 armored vs unarmored aircraft carriers in rec.aviation.military.
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social issues these required firm timely decisions derived from incomplete and possibly wrong information plus good intuition. Much of the "logic" of opposing arguments masks their financial, professional or electoral self interest.
There is pressure to offer unjustifiably definite advice to avoid accusations of Analysis Paralysis (see Jimmy Carter). With some exceptions the physical sciences are more aware of and willing to admit the limited accuracy of predictions based on statistical methodology. Some good clues we pick up are numerical values with too many significant digits, or rounded percentages that add up to exactly 100%.
Political pollsters here report the margin of error as one over the square root of the sample size without relating it to confidence level, and are annoyed and suspicious when they are proven wrong. Experimental verification exposes such sloppiness by physical scientists and serves to keep us honest and careful.
Social scientists can be very certain, smug and arrogant about conclusions which we plainly see that their data does not adequately support. A common failing is that while the logic may be internally consistent its underlying assumptions are at least controversial. Chomsky is a fine example. And that is the basis for considering them less than real scientists, not the extensive complexity and uncertainty of their subject though they are trivial compared to human biochemistry. It's the results that matter, not the tools used to obtain them.
I accidentally took a statistics class meant for social scientists once. The mathematical rigor fell drastically short of what I expected and needed, but it was very interesting for the insight into sampling algorithms and the many intentional and inadvertent ways to bias the results, such as calling homes during the daytime when only unemployed people will answer. The pundits here repeatedly express their amazement at how so many of us can remain "undecided" right up until we enter the voting booth.
This exchange reminds me of the story about the old economics graduate returning to the campus and talking to the economics professor. They talked about how much the world has changed and how important it was to know economics. The professor was grading the final exam papers at the time and showed some to the graduate. Who exclaimed " Why these are the very same questions that were on my final exam ". And the professor answered " Well yes those are the same questions, but we keep changing the answers."
To me the thing that casts doubt on how scientific a subject is is how good is the repeatability of the theory. If the theory always explains what happens, then is is science. If things do not repeat the same way according to the theory, then it really is not science. It is history, perhaps with a great theory of why things turned out as it did. But not a science that can be used to see how things are going to turn out.
Well, there goes Newtonian physics. I guess Newton wasn't a scientist then, huh?
Unless your electrons suddenly develop personalities, you're in good shape. Stick to things that are dead or were never alive, and you won't have any trouble.
Science is about acquiring knowledge. If it can make predictions, that's great. But Louis Leakey would be disappointed to hear you say he doesn't do science, even though he wouldn't venture to predict the further evolution of the human race.
You're in the instrumentalist tank, Dan. It's good for dead things.
As I said, where chemistry was before 1800. Passive observations couldn't prove or disprove competing incorrect hypotheses like Caloric, Phlogiston or the AEther. We honor the early scientists for their contributions but their flawed ideas were discarded after precise experimentation led to the correct ones. At that time Adam Smith was as (or more) scientifically valid as Joseph Priestley, IOW chemistry was then where economics is now. We have seen the maturation process and know the intermediate stages.
My main point is that since they are still at the observational stage and demonstrably incapable of accurate prediction, social scientists shouldn't impose their unproven conjectures on us as though they were the laws of nature.
I aced it effortlessly. This is what was skipped that I needed.
So far, you're only proving my point about the narrow and smug attitude of many instumentalists.
Regarding engineering, this is also the reason I got out of it. There are few college programs that are narrower or that have less allowance for electives in fields other than engineering itself and the peripheral prerequisites and so on. Although the result is a very high level of vocational training, the education of an engineer depends mostly on how successful he is at learning things outside of his college program.
Some do, some don't. The ones who don't tend to see everything through that filter, and to be very defensive about it.
Chemistry before 1800 - easily with the Church - and with their high priest - Alchemy and early chemistry.
e.g. in May 1653, alchemist William Backhouse entrusts royalist 'Intelligencer' Elias Ashmole with the true secret of the Philosopher's Stone. And with that under his belt, begins a rise in fame and fortune - Becoming the most knowledgeable man in England, Founder member of the Royal Society, Windsor Herald, Astrologer to the King, fosterer of science and inspiration to Isaac Newton (his student).
Known a Magus and preserver of his country.
A good book on this man is ISBN 0954330927
Mart>> On Thu, 12 Jan 2012 10:48:10 -0500, "Jim Wilkins"
You're engaging in a self-aggrandizing definition, Jim. First you decide what you do best, then you define that as the best thing there is to do...then you pat yourself on the back for being the best thing going.
As I said to Dan, the physical sciences are very good at dealing with dead things and things that never lived. Because the things they deal with are mechanistic and behave according to some relatively simple natural laws, the whole process of physical science behaves like a mechanism.
That makes it simpler to conduct an instrumentalist approach. But that does not justify co-opting the entire field of science, or of applying a self-congratulatory definition to the relative importance or the relative quality of the enterprise.
I don't know of any social scientist who is in a position to impose anything. Who are you thinking of?
Very good. Regression analysis today is an essential part of econometrics, and the methods of econometrics, as a couple of us stated early on in this thread, are being adoopted by several of the social sciences.
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