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Weiye Loh

Science, Strong Inference -- Proper Scientific Method - 0 views

  • Scientists these days tend to keep up a polite fiction that all science is equal. Except for the work of the misguided opponent whose arguments we happen to be refuting at the time, we speak as though every scientist's field and methods of study are as good as every other scientist's and perhaps a little better. This keeps us all cordial when it comes to recommending each other for government grants.
  • Why should there be such rapid advances in some fields and not in others? I think the usual explanations that we tend to think of - such as the tractability of the subject, or the quality or education of the men drawn into it, or the size of research contracts - are important but inadequate. I have begun to believe that the primary factor in scientific advance is an intellectual one. These rapidly moving fields are fields where a particular method of doing scientific research is systematically used and taught, an accumulative method of inductive inference that is so effective that I think it should be given the name of "strong inference." I believe it is important to examine this method, its use and history and rationale, and to see whether other groups and individuals might learn to adopt it profitably in their own scientific and intellectual work. In its separate elements, strong inference is just the simple and old-fashioned method of inductive inference that goes back to Francis Bacon. The steps are familiar to every college student and are practiced, off and on, by every scientist. The difference comes in their systematic application. Strong inference consists of applying the following steps to every problem in science, formally and explicitly and regularly: Devising alternative hypotheses; Devising a crucial experiment (or several of them), with alternative possible outcomes, each of which will, as nearly is possible, exclude one or more of the hypotheses; Carrying out the experiment so as to get a clean result; Recycling the procedure, making subhypotheses or sequential hypotheses to refine the possibilities that remain, and so on.
  • On any new problem, of course, inductive inference is not as simple and certain as deduction, because it involves reaching out into the unknown. Steps 1 and 2 require intellectual inventions, which must be cleverly chosen so that hypothesis, experiment, outcome, and exclusion will be related in a rigorous syllogism; and the question of how to generate such inventions is one which has been extensively discussed elsewhere (2, 3). What the formal schema reminds us to do is to try to make these inventions, to take the next step, to proceed to the next fork, without dawdling or getting tied up in irrelevancies.
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  • It is clear why this makes for rapid and powerful progress. For exploring the unknown, there is no faster method; this is the minimum sequence of steps. Any conclusion that is not an exclusion is insecure and must be rechecked. Any delay in recycling to the next set of hypotheses is only a delay. Strong inference, and the logical tree it generates, are to inductive reasoning what the syllogism is to deductive reasoning in that it offers a regular method for reaching firm inductive conclusions one after the other as rapidly as possible.
  • "But what is so novel about this?" someone will say. This is the method of science and always has been, why give it a special name? The reason is that many of us have almost forgotten it. Science is now an everyday business. Equipment, calculations, lectures become ends in themselves. How many of us write down our alternatives and crucial experiments every day, focusing on the exclusion of a hypothesis? We may write our scientific papers so that it looks as if we had steps 1, 2, and 3 in mind all along. But in between, we do busywork. We become "method- oriented" rather than "problem-oriented." We say we prefer to "feel our way" toward generalizations. We fail to teach our students how to sharpen up their inductive inferences. And we do not realize the added power that the regular and explicit use of alternative hypothesis and sharp exclusion could give us at every step of our research.
  • A distinguished cell biologist rose and said, "No two cells give the same properties. Biology is the science of heterogeneous systems." And he added privately. "You know there are scientists, and there are people in science who are just working with these over-simplified model systems - DNA chains and in vitro systems - who are not doing science at all. We need their auxiliary work: they build apparatus, they make minor studies, but they are not scientists." To which Cy Levinthal replied: "Well, there are two kinds of biologists, those who are looking to see if there is one thing that can be understood and those who keep saying it is very complicated and that nothing can be understood. . . . You must study the simplest system you think has the properties you are interested in."
  • At the 1958 Conference on Biophysics, at Boulder, there was a dramatic confrontation between the two points of view. Leo Szilard said: "The problems of how enzymes are induced, of how proteins are synthesized, of how antibodies are formed, are closer to solution than is generally believed. If you do stupid experiments, and finish one a year, it can take 50 years. But if you stop doing experiments for a little while and think how proteins can possibly be synthesized, there are only about 5 different ways, not 50! And it will take only a few experiments to distinguish these." One of the young men added: "It is essentially the old question: How small and elegant an experiment can you perform?" These comments upset a number of those present. An electron microscopist said. "Gentlemen, this is off the track. This is philosophy of science." Szilard retorted. "I was not quarreling with third-rate scientists: I was quarreling with first-rate scientists."
  • Any criticism or challenge to consider changing our methods strikes of course at all our ego-defenses. But in this case the analytical method offers the possibility of such great increases in effectiveness that it is unfortunate that it cannot be regarded more often as a challenge to learning rather than as challenge to combat. Many of the recent triumphs in molecular biology have in fact been achieved on just such "oversimplified model systems," very much along the analytical lines laid down in the 1958 discussion. They have not fallen to the kind of men who justify themselves by saying "No two cells are alike," regardless of how true that may ultimately be. The triumphs are in fact triumphs of a new way of thinking.
  • the emphasis on strong inference
  • is also partly due to the nature of the fields themselves. Biology, with its vast informational detail and complexity, is a "high-information" field, where years and decades can easily be wasted on the usual type of "low-information" observations or experiments if one does not think carefully in advance about what the most important and conclusive experiments would be. And in high-energy physics, both the "information flux" of particles from the new accelerators and the million-dollar costs of operation have forced a similar analytical approach. It pays to have a top-notch group debate every experiment ahead of time; and the habit spreads throughout the field.
  • Historically, I think, there have been two main contributions to the development of a satisfactory strong-inference method. The first is that of Francis Bacon (13). He wanted a "surer method" of "finding out nature" than either the logic-chopping or all-inclusive theories of the time or the laudable but crude attempts to make inductions "by simple enumeration." He did not merely urge experiments as some suppose, he showed the fruitfulness of interconnecting theory and experiment so that the one checked the other. Of the many inductive procedures he suggested, the most important, I think, was the conditional inductive tree, which proceeded from alternative hypothesis (possible "causes," as he calls them), through crucial experiments ("Instances of the Fingerpost"), to exclusion of some alternatives and adoption of what is left ("establishing axioms"). His Instances of the Fingerpost are explicitly at the forks in the logical tree, the term being borrowed "from the fingerposts which are set up where roads part, to indicate the several directions."
  • ere was a method that could separate off the empty theories! Bacon, said the inductive method could be learned by anybody, just like learning to "draw a straighter line or more perfect circle . . . with the help of a ruler or a pair of compasses." "My way of discovering sciences goes far to level men's wit and leaves but little to individual excellence, because it performs everything by the surest rules and demonstrations." Even occasional mistakes would not be fatal. "Truth will sooner come out from error than from confusion."
  • Nevertheless there is a difficulty with this method. As Bacon emphasizes, it is necessary to make "exclusions." He says, "The induction which is to be available for the discovery and demonstration of sciences and arts, must analyze nature by proper rejections and exclusions, and then, after a sufficient number of negatives come to a conclusion on the affirmative instances." "[To man] it is granted only to proceed at first by negatives, and at last to end in affirmatives after exclusion has been exhausted." Or, as the philosopher Karl Popper says today there is no such thing as proof in science - because some later alternative explanation may be as good or better - so that science advances only by disproofs. There is no point in making hypotheses that are not falsifiable because such hypotheses do not say anything, "it must be possible for all empirical scientific system to be refuted by experience" (14).
  • The difficulty is that disproof is a hard doctrine. If you have a hypothesis and I have another hypothesis, evidently one of them must be eliminated. The scientist seems to have no choice but to be either soft-headed or disputatious. Perhaps this is why so many tend to resist the strong analytical approach and why some great scientists are so disputatious.
  • Fortunately, it seems to me, this difficulty can be removed by the use of a second great intellectual invention, the "method of multiple hypotheses," which is what was needed to round out the Baconian scheme. This is a method that was put forward by T.C. Chamberlin (15), a geologist at Chicago at the turn of the century, who is best known for his contribution to the Chamberlain-Moulton hypothesis of the origin of the solar system.
  • Chamberlin says our trouble is that when we make a single hypothesis, we become attached to it. "The moment one has offered an original explanation for a phenomenon which seems satisfactory, that moment affection for his intellectual child springs into existence, and as the explanation grows into a definite theory his parental affections cluster about his offspring and it grows more and more dear to him. . . . There springs up also unwittingly a pressing of the theory to make it fit the facts and a pressing of the facts to make them fit the theory..." "To avoid this grave danger, the method of multiple working hypotheses is urged. It differs from the simple working hypothesis in that it distributes the effort and divides the affections. . . . Each hypothesis suggests its own criteria, its own method of proof, its own method of developing the truth, and if a group of hypotheses encompass the subject on all sides, the total outcome of means and of methods is full and rich."
  • The conflict and exclusion of alternatives that is necessary to sharp inductive inference has been all too often a conflict between men, each with his single Ruling Theory. But whenever each man begins to have multiple working hypotheses, it becomes purely a conflict between ideas. It becomes much easier then for each of us to aim every day at conclusive disproofs - at strong inference - without either reluctance or combativeness. In fact, when there are multiple hypotheses, which are not anyone's "personal property," and when there are crucial experiments to test them, the daily life in the laboratory takes on an interest and excitement it never had, and the students can hardly wait to get to work to see how the detective story will come out. It seems to me that this is the reason for the development of those distinctive habits of mind and the "complex thought" that Chamberlin described, the reason for the sharpness, the excitement, the zeal, the teamwork - yes, even international teamwork - in molecular biology and high- energy physics today. What else could be so effective?
  • Unfortunately, I think, there are other other areas of science today that are sick by comparison, because they have forgotten the necessity for alternative hypotheses and disproof. Each man has only one branch - or none - on the logical tree, and it twists at random without ever coming to the need for a crucial decision at any point. We can see from the external symptoms that there is something scientifically wrong. The Frozen Method, The Eternal Surveyor, The Never Finished, The Great Man With a Single Hypothcsis, The Little Club of Dependents, The Vendetta, The All-Encompassing Theory Which Can Never Be Falsified.
  • a "theory" of this sort is not a theory at all, because it does not exclude anything. It predicts everything, and therefore does not predict anything. It becomes simply a verbal formula which the graduate student repeats and believes because the professor has said it so often. This is not science, but faith; not theory, but theology. Whether it is hand-waving or number-waving, or equation-waving, a theory is not a theory unless it can be disproved. That is, unless it can be falsified by some possible experimental outcome.
  • the work methods of a number of scientists have been testimony to the power of strong inference. Is success not due in many cases to systematic use of Bacon's "surest rules and demonstrations" as much as to rare and unattainable intellectual power? Faraday's famous diary (16), or Fermi's notebooks (3, 17), show how these men believed in the effectiveness of daily steps in applying formal inductive methods to one problem after another.
  • Surveys, taxonomy, design of equipment, systematic measurements and tables, theoretical computations - all have their proper and honored place, provided they are parts of a chain of precise induction of how nature works. Unfortunately, all too often they become ends in themselves, mere time-serving from the point of view of real scientific advance, a hypertrophied methodology that justifies itself as a lore of respectability.
  • We speak piously of taking measurements and making small studies that will "add another brick to the temple of science." Most such bricks just lie around the brickyard (20). Tables of constraints have their place and value, but the study of one spectrum after another, if not frequently re-evaluated, may become a substitute for thinking, a sad waste of intelligence in a research laboratory, and a mistraining whose crippling effects may last a lifetime.
  • Beware of the man of one method or one instrument, either experimental or theoretical. He tends to become method-oriented rather than problem-oriented. The method-oriented man is shackled; the problem-oriented man is at least reaching freely toward that is most important. Strong inference redirects a man to problem-orientation, but it requires him to be willing repeatedly to put aside his last methods and teach himself new ones.
  • anyone who asks the question about scientific effectiveness will also conclude that much of the mathematizing in physics and chemistry today is irrelevant if not misleading. The great value of mathematical formulation is that when an experiment agrees with a calculation to five decimal places, a great many alternative hypotheses are pretty well excluded (though the Bohr theory and the Schrödinger theory both predict exactly the same Rydberg constant!). But when the fit is only to two decimal places, or one, it may be a trap for the unwary; it may be no better than any rule-of-thumb extrapolation, and some other kind of qualitative exclusion might be more rigorous for testing the assumptions and more important to scientific understanding than the quantitative fit.
  • Today we preach that science is not science unless it is quantitative. We substitute correlations for causal studies, and physical equations for organic reasoning. Measurements and equations are supposed to sharpen thinking, but, in my observation, they more often tend to make the thinking noncausal and fuzzy. They tend to become the object of scientific manipulation instead of auxiliary tests of crucial inferences.
  • Many - perhaps most - of the great issues of science are qualitative, not quantitative, even in physics and chemistry. Equations and measurements are useful when and only when they are related to proof; but proof or disproof comes first and is in fact strongest when it is absolutely convincing without any quantitative measurement.
  • you can catch phenomena in a logical box or in a mathematical box. The logical box is coarse but strong. The mathematical box is fine-grained but flimsy. The mathematical box is a beautiful way of wrapping up a problem, but it will not hold the phenomena unless they have been caught in a logical box to begin with.
  • Of course it is easy - and all too common - for one scientist to call the others unscientific. My point is not that my particular conclusions here are necessarily correct, but that we have long needed some absolute standard of possible scientific effectiveness by which to measure how well we are succeeding in various areas - a standard that many could agree on and one that would be undistorted by the scientific pressures and fashions of the times and the vested interests and busywork that they develop. It is not public evaluation I am interested in so much as a private measure by which to compare one's own scientific performance with what it might be. I believe that strong inference provides this kind of standard of what the maximum possible scientific effectiveness could be - as well as a recipe for reaching it.
  • The strong-inference point of view is so resolutely critical of methods of work and values in science that any attempt to compare specific cases is likely to sound but smug and destructive. Mainly one should try to teach it by example and by exhorting to self-analysis and self-improvement only in general terms
  • one severe but useful private test - a touchstone of strong inference - that removes the necessity for third-person criticism, because it is a test that anyone can learn to carry with him for use as needed. It is our old friend the Baconian "exclusion," but I call it "The Question." Obviously it should be applied as much to one's own thinking as to others'. It consists of asking in your own mind, on hearing any scientific explanation or theory put forward, "But sir, what experiment could disprove your hypothesis?"; or, on hearing a scientific experiment described, "But sir, what hypothesis does your experiment disprove?"
  • It is not true that all science is equal; or that we cannot justly compare the effectiveness of scientists by any method other than a mutual-recommendation system. The man to watch, the man to put your money on, is not the man who wants to make "a survey" or a "more detailed study" but the man with the notebook, the man with the alternative hypotheses and the crucial experiments, the man who knows how to answer your Question of disproof and is already working on it.
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    There is so much bad science and bad statistics information in media reports, publications, and shared between conversants that I think it is important to understand about facts and proofs and the associated pitfalls.
Weiye Loh

Skepticblog » Flaws in Creationist Logic - 0 views

  • making a false analogy here by confusing the origin of life with the later evolution of life. The watch analogy was specifically offered to say that something which is complex and displays design must have been created and designed by a creator. Therefore, since we see complexity and design in life it too must have had a creator. But all the life that we know – that life which is being pointed to as complex and designed – is the result of a process (evolution) that has worked over billions of years. Life can grow, reproduce, and evolve. Watches cannot – so it is not a valid analogy.
  • Life did emerge from non-living matter, but that is irrelevant to the point. There was likely a process of chemical evolution – but still the non-living precursors to life were just chemicals, they did not display the design or complexity apparent in a watch. Ankur’s attempt to rescue this false analogy fails. And before someone has a chance to point it out – yes, I said that life displays design. It displays bottom-up evolutionary design, not top-down intelligent design. This refers to another fallacy of creationists – the assumption that all design is top down. But nature demonstrates that this is a false assumption.
  • An increase in variation is an increase in information – it takes more information to describe the greater variety. By any actual definition of information – variation increases information. Also, as I argued, when you have gene duplication you are physically increasing the number of information carrying units – that is an increase in information. There is simply no way to avoid the mountain of genetic evidence that genetic information has increased over evolutionary time through evolutionary processes.
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    FLAWS IN CREATIONIST LOGIC
Weiye Loh

Why Evolution May Favor Irrationality - Newsweek - 0 views

  • The reason we succumb to confirmation bias, why we are blind to counterexamples, and why we fall short of CartesianCartesian logic in so many other ways is that these lapses have a purpose: they help us “devise and evaluate arguments that are intended to persuade other people,” says psychologist Hugo Mercier of the University of Pennsylvania. Failures of logic, he and cognitive scientist Dan Sperber of the Institut Jean Nicod in Paris propose, are in fact effective ploys to win arguments.
  • That puts poor reasoning in a completely different light. Arguing, after all, is less about seeking truth than about overcoming opposing views.
  • while confirmation bias, for instance, may mislead us about what’s true and real, by letting examples that support our view monopolize our memory and perception, it maximizes the artillery we wield when trying to convince someone that, say, he really is “late all the time.” Confirmation bias “has a straightforward explanation,” argues Mercier. “It contributes to effective argumentation.”
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  • finding counterexamples can, in general, weaken our confidence in our own arguments. Forms of reasoning that are good for solving logic puzzles but bad for winning arguments lost out, over the course of evolution, to those that help us be persuasive but cause us to struggle with abstract syllogisms. Interestingly, syllogisms are easier to evaluate in the form “No flying things are penguins; all penguins are birds; so some birds are not fliers.” That’s because we are more likely to argue about animals than A, B, and C.
  • The sort of faulty thinking called motivated reasoning also impedes our search for truth but advances arguments. For instance, we tend to look harder for flaws in a study when we don’t agree with its conclusions and are more critical of evidence that undermines our point of view.
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    The Limits of Reason Why evolution may favor irrationality.
Weiye Loh

Odds Are, It's Wrong - Science News - 0 views

  • science has long been married to mathematics. Generally it has been for the better. Especially since the days of Galileo and Newton, math has nurtured science. Rigorous mathematical methods have secured science’s fidelity to fact and conferred a timeless reliability to its findings.
  • a mutant form of math has deflected science’s heart from the modes of calculation that had long served so faithfully. Science was seduced by statistics, the math rooted in the same principles that guarantee profits for Las Vegas casinos. Supposedly, the proper use of statistics makes relying on scientific results a safe bet. But in practice, widespread misuse of statistical methods makes science more like a crapshoot.
  • science’s dirtiest secret: The “scientific method” of testing hypotheses by statistical analysis stands on a flimsy foundation. Statistical tests are supposed to guide scientists in judging whether an experimental result reflects some real effect or is merely a random fluke, but the standard methods mix mutually inconsistent philosophies and offer no meaningful basis for making such decisions. Even when performed correctly, statistical tests are widely misunderstood and frequently misinterpreted. As a result, countless conclusions in the scientific literature are erroneous, and tests of medical dangers or treatments are often contradictory and confusing.
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  • Experts in the math of probability and statistics are well aware of these problems and have for decades expressed concern about them in major journals. Over the years, hundreds of published papers have warned that science’s love affair with statistics has spawned countless illegitimate findings. In fact, if you believe what you read in the scientific literature, you shouldn’t believe what you read in the scientific literature.
  • “There are more false claims made in the medical literature than anybody appreciates,” he says. “There’s no question about that.”Nobody contends that all of science is wrong, or that it hasn’t compiled an impressive array of truths about the natural world. Still, any single scientific study alone is quite likely to be incorrect, thanks largely to the fact that the standard statistical system for drawing conclusions is, in essence, illogical. “A lot of scientists don’t understand statistics,” says Goodman. “And they don’t understand statistics because the statistics don’t make sense.”
  • In 2007, for instance, researchers combing the medical literature found numerous studies linking a total of 85 genetic variants in 70 different genes to acute coronary syndrome, a cluster of heart problems. When the researchers compared genetic tests of 811 patients that had the syndrome with a group of 650 (matched for sex and age) that didn’t, only one of the suspect gene variants turned up substantially more often in those with the syndrome — a number to be expected by chance.“Our null results provide no support for the hypothesis that any of the 85 genetic variants tested is a susceptibility factor” for the syndrome, the researchers reported in the Journal of the American Medical Association.How could so many studies be wrong? Because their conclusions relied on “statistical significance,” a concept at the heart of the mathematical analysis of modern scientific experiments.
  • Statistical significance is a phrase that every science graduate student learns, but few comprehend. While its origins stretch back at least to the 19th century, the modern notion was pioneered by the mathematician Ronald A. Fisher in the 1920s. His original interest was agriculture. He sought a test of whether variation in crop yields was due to some specific intervention (say, fertilizer) or merely reflected random factors beyond experimental control.Fisher first assumed that fertilizer caused no difference — the “no effect” or “null” hypothesis. He then calculated a number called the P value, the probability that an observed yield in a fertilized field would occur if fertilizer had no real effect. If P is less than .05 — meaning the chance of a fluke is less than 5 percent — the result should be declared “statistically significant,” Fisher arbitrarily declared, and the no effect hypothesis should be rejected, supposedly confirming that fertilizer works.Fisher’s P value eventually became the ultimate arbiter of credibility for science results of all sorts
  • But in fact, there’s no logical basis for using a P value from a single study to draw any conclusion. If the chance of a fluke is less than 5 percent, two possible conclusions remain: There is a real effect, or the result is an improbable fluke. Fisher’s method offers no way to know which is which. On the other hand, if a study finds no statistically significant effect, that doesn’t prove anything, either. Perhaps the effect doesn’t exist, or maybe the statistical test wasn’t powerful enough to detect a small but real effect.
  • Soon after Fisher established his system of statistical significance, it was attacked by other mathematicians, notably Egon Pearson and Jerzy Neyman. Rather than testing a null hypothesis, they argued, it made more sense to test competing hypotheses against one another. That approach also produces a P value, which is used to gauge the likelihood of a “false positive” — concluding an effect is real when it actually isn’t. What  eventually emerged was a hybrid mix of the mutually inconsistent Fisher and Neyman-Pearson approaches, which has rendered interpretations of standard statistics muddled at best and simply erroneous at worst. As a result, most scientists are confused about the meaning of a P value or how to interpret it. “It’s almost never, ever, ever stated correctly, what it means,” says Goodman.
  • experimental data yielding a P value of .05 means that there is only a 5 percent chance of obtaining the observed (or more extreme) result if no real effect exists (that is, if the no-difference hypothesis is correct). But many explanations mangle the subtleties in that definition. A recent popular book on issues involving science, for example, states a commonly held misperception about the meaning of statistical significance at the .05 level: “This means that it is 95 percent certain that the observed difference between groups, or sets of samples, is real and could not have arisen by chance.”
  • That interpretation commits an egregious logical error (technical term: “transposed conditional”): confusing the odds of getting a result (if a hypothesis is true) with the odds favoring the hypothesis if you observe that result. A well-fed dog may seldom bark, but observing the rare bark does not imply that the dog is hungry. A dog may bark 5 percent of the time even if it is well-fed all of the time. (See Box 2)
    • Weiye Loh
       
      Does the problem then, lie not in statistics, but the interpretation of statistics? Is the fallacy of appeal to probability is at work in such interpretation? 
  • Another common error equates statistical significance to “significance” in the ordinary use of the word. Because of the way statistical formulas work, a study with a very large sample can detect “statistical significance” for a small effect that is meaningless in practical terms. A new drug may be statistically better than an old drug, but for every thousand people you treat you might get just one or two additional cures — not clinically significant. Similarly, when studies claim that a chemical causes a “significantly increased risk of cancer,” they often mean that it is just statistically significant, possibly posing only a tiny absolute increase in risk.
  • Statisticians perpetually caution against mistaking statistical significance for practical importance, but scientific papers commit that error often. Ziliak studied journals from various fields — psychology, medicine and economics among others — and reported frequent disregard for the distinction.
  • “I found that eight or nine of every 10 articles published in the leading journals make the fatal substitution” of equating statistical significance to importance, he said in an interview. Ziliak’s data are documented in the 2008 book The Cult of Statistical Significance, coauthored with Deirdre McCloskey of the University of Illinois at Chicago.
  • Multiplicity of mistakesEven when “significance” is properly defined and P values are carefully calculated, statistical inference is plagued by many other problems. Chief among them is the “multiplicity” issue — the testing of many hypotheses simultaneously. When several drugs are tested at once, or a single drug is tested on several groups, chances of getting a statistically significant but false result rise rapidly.
  • Recognizing these problems, some researchers now calculate a “false discovery rate” to warn of flukes disguised as real effects. And genetics researchers have begun using “genome-wide association studies” that attempt to ameliorate the multiplicity issue (SN: 6/21/08, p. 20).
  • Many researchers now also commonly report results with confidence intervals, similar to the margins of error reported in opinion polls. Such intervals, usually given as a range that should include the actual value with 95 percent confidence, do convey a better sense of how precise a finding is. But the 95 percent confidence calculation is based on the same math as the .05 P value and so still shares some of its problems.
  • Statistical problems also afflict the “gold standard” for medical research, the randomized, controlled clinical trials that test drugs for their ability to cure or their power to harm. Such trials assign patients at random to receive either the substance being tested or a placebo, typically a sugar pill; random selection supposedly guarantees that patients’ personal characteristics won’t bias the choice of who gets the actual treatment. But in practice, selection biases may still occur, Vance Berger and Sherri Weinstein noted in 2004 in ControlledClinical Trials. “Some of the benefits ascribed to randomization, for example that it eliminates all selection bias, can better be described as fantasy than reality,” they wrote.
  • Randomization also should ensure that unknown differences among individuals are mixed in roughly the same proportions in the groups being tested. But statistics do not guarantee an equal distribution any more than they prohibit 10 heads in a row when flipping a penny. With thousands of clinical trials in progress, some will not be well randomized. And DNA differs at more than a million spots in the human genetic catalog, so even in a single trial differences may not be evenly mixed. In a sufficiently large trial, unrandomized factors may balance out, if some have positive effects and some are negative. (See Box 3) Still, trial results are reported as averages that may obscure individual differences, masking beneficial or harm­ful effects and possibly leading to approval of drugs that are deadly for some and denial of effective treatment to others.
  • nother concern is the common strategy of combining results from many trials into a single “meta-analysis,” a study of studies. In a single trial with relatively few participants, statistical tests may not detect small but real and possibly important effects. In principle, combining smaller studies to create a larger sample would allow the tests to detect such small effects. But statistical techniques for doing so are valid only if certain criteria are met. For one thing, all the studies conducted on the drug must be included — published and unpublished. And all the studies should have been performed in a similar way, using the same protocols, definitions, types of patients and doses. When combining studies with differences, it is necessary first to show that those differences would not affect the analysis, Goodman notes, but that seldom happens. “That’s not a formal part of most meta-analyses,” he says.
  • Meta-analyses have produced many controversial conclusions. Common claims that antidepressants work no better than placebos, for example, are based on meta-analyses that do not conform to the criteria that would confer validity. Similar problems afflicted a 2007 meta-analysis, published in the New England Journal of Medicine, that attributed increased heart attack risk to the diabetes drug Avandia. Raw data from the combined trials showed that only 55 people in 10,000 had heart attacks when using Avandia, compared with 59 people per 10,000 in comparison groups. But after a series of statistical manipulations, Avandia appeared to confer an increased risk.
  • combining small studies in a meta-analysis is not a good substitute for a single trial sufficiently large to test a given question. “Meta-analyses can reduce the role of chance in the interpretation but may introduce bias and confounding,” Hennekens and DeMets write in the Dec. 2 Journal of the American Medical Association. “Such results should be considered more as hypothesis formulating than as hypothesis testing.”
  • Some studies show dramatic effects that don’t require sophisticated statistics to interpret. If the P value is 0.0001 — a hundredth of a percent chance of a fluke — that is strong evidence, Goodman points out. Besides, most well-accepted science is based not on any single study, but on studies that have been confirmed by repetition. Any one result may be likely to be wrong, but confidence rises quickly if that result is independently replicated.“Replication is vital,” says statistician Juliet Shaffer, a lecturer emeritus at the University of California, Berkeley. And in medicine, she says, the need for replication is widely recognized. “But in the social sciences and behavioral sciences, replication is not common,” she noted in San Diego in February at the annual meeting of the American Association for the Advancement of Science. “This is a sad situation.”
  • Most critics of standard statistics advocate the Bayesian approach to statistical reasoning, a methodology that derives from a theorem credited to Bayes, an 18th century English clergyman. His approach uses similar math, but requires the added twist of a “prior probability” — in essence, an informed guess about the expected probability of something in advance of the study. Often this prior probability is more than a mere guess — it could be based, for instance, on previous studies.
  • it basically just reflects the need to include previous knowledge when drawing conclusions from new observations. To infer the odds that a barking dog is hungry, for instance, it is not enough to know how often the dog barks when well-fed. You also need to know how often it eats — in order to calculate the prior probability of being hungry. Bayesian math combines a prior probability with observed data to produce an estimate of the likelihood of the hunger hypothesis. “A scientific hypothesis cannot be properly assessed solely by reference to the observational data,” but only by viewing the data in light of prior belief in the hypothesis, wrote George Diamond and Sanjay Kaul of UCLA’s School of Medicine in 2004 in the Journal of the American College of Cardiology. “Bayes’ theorem is ... a logically consistent, mathematically valid, and intuitive way to draw inferences about the hypothesis.” (See Box 4)
  • In many real-life contexts, Bayesian methods do produce the best answers to important questions. In medical diagnoses, for instance, the likelihood that a test for a disease is correct depends on the prevalence of the disease in the population, a factor that Bayesian math would take into account.
  • But Bayesian methods introduce a confusion into the actual meaning of the mathematical concept of “probability” in the real world. Standard or “frequentist” statistics treat probabilities as objective realities; Bayesians treat probabilities as “degrees of belief” based in part on a personal assessment or subjective decision about what to include in the calculation. That’s a tough placebo to swallow for scientists wedded to the “objective” ideal of standard statistics. “Subjective prior beliefs are anathema to the frequentist, who relies instead on a series of ad hoc algorithms that maintain the facade of scientific objectivity,” Diamond and Kaul wrote.Conflict between frequentists and Bayesians has been ongoing for two centuries. So science’s marriage to mathematics seems to entail some irreconcilable differences. Whether the future holds a fruitful reconciliation or an ugly separation may depend on forging a shared understanding of probability.“What does probability mean in real life?” the statistician David Salsburg asked in his 2001 book The Lady Tasting Tea. “This problem is still unsolved, and ... if it remains un­solved, the whole of the statistical approach to science may come crashing down from the weight of its own inconsistencies.”
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    Odds Are, It's Wrong Science fails to face the shortcomings of statistics
Weiye Loh

Roger Pielke Jr.'s Blog: The Flip Side of Extreme Event Attribution - 0 views

  • It is just logical that one cannot make the claim that action on climate change will influence future extreme events without first being able to claim that greenhouse gas emissions have a discernible influence on those extremes. This probably helps to explain why there is such a push to classify the attribution issue as settled. But this is just piling on one bad argument on top of another.
  • Even if you believe that attribution has been achieved, these are bad arguments for the simple fact that detecting the effects on the global climate system of emissions reductions would take many, many (many!) decades.  For instance, for an aggressive climate policy that would stabilize carbon dioxide at 450 ppm, detecting a change in average global temperatures would necessarily occur in the second half of this century.  Detection of changes in extreme events would take even longer.
  • To suggest that action on greenhouse gas emissions is a mechanism for modulating the impacts of extreme events remains a highly misleading argument.  There are better justifications for action on carbon dioxide that do not depend on contorting the state of the science.
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    It is just logical that one cannot make the claim that action on climate change will influence future extreme events without first being able to claim that greenhouse gas emissions have a discernible influence on those extremes. This probably helps to explain why there is such a push to classify the attribution issue as settled. But this is just piling on one bad argument on top of another.
Weiye Loh

Open Letter to Richard Dawkins: Why Are You Still In Denial About Group Selection? : Ev... - 0 views

  • Dear Richard, I do not agree with the cynical adage "science progresses--funeral by funeral", but I fear that it might be true in your case for the subject of group selection.
  • Edward Wilson was misunderstanding kin selection as far back as Sociobiology, where he treated it as a subset of group selection ... Kin selection is not a subset of group selection, it is a logical consequence of gene selection. And gene selection is (everything that Nowak et al ought to mean by) 'standard natural selection' theory: has been ever since the neo-Darwinian synthesis of the 1930s.
  • I do not agree with the Nowak et al. article in every respect and will articulate some of my disagreements in subsequent posts. For the moment, I want to stress how alone you are in your statement about group selection. Your view is essentially pre-1975, a date that is notable not only for the publication of Sociobiology but also a paper by W.D. Hamilton, one of your heroes, who correctly saw the relationship between kin selection and group selection thanks to the work of George Price. Ever since, knowledgeable theoretical biologists have known that inclusive fitness theory includes the logic of multilevel selection, which means that altruism is selectively disadvantageous within kin groups and evolves only by virtue of groups with more altruists contributing more to the gene pool than groups with fewer altruists. The significance of relatedness is that it clusters the genes coding for altruistic and selfish behaviors into different groups.
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  • Even the contemporary theoretical biologists most critical of multilevel selection, such as Stuart West and Andy Gardner, acknowledge what you still deny. In an earlier feature on group selection published in Nature, Andy Gardner is quoted as saying "Everyone agrees that group selection occurs"--everyone except you, that is.
  • You correctly say that gene selection is standard natural selection theory. Essentially, it is a popularization of the concept of average effects in population genetics theory, which averages the fitness of alternative genes across all contexts to calculate what evolves in the total population. For that reason, it is an elementary mistake to regard gene selection as an alternative to group selection. Whenever a gene evolves in the total population on the strength of group selection, despite being selectively disadvantageous within groups, it has the highest average effect compared to the genes that it replaced. Please consult the installment of my "Truth and Reconciliation for Group Selection" series titled "Naïve Gene Selectionism" for a refresher course. While you're at it, check out the installment titled "Dawkins Protests--Too Much".
  • The Nowak et al. article includes several critiques of inclusive fitness theory that need to be distinguished from each other. One issue is whether inclusive fitness theory is truly equivalent to explicit models of evolution in multi-group populations, or whether it makes so many simplifying assumptions that it restricts itself to a small region of the parameter space. A second issue is whether benefiting collateral kin is required for the evolution of eusociality and other forms of prosociality. A third issue is whether inclusive fitness theory, as understood by the average evolutionary biologist and the general public, bears any resemblance to inclusive fitness theory as understood by the cognoscenti.
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    Open Letter to Richard Dawkins: Why Are You Still In Denial About Group Selection?
Weiye Loh

A Culture of Poverty - Ta-Nehisi Coates - Personal - The Atlantic - 0 views

  • When we talk "culture," as it relates to African-Americans, we assume a kind of exclusivity and suspension of logic. Stats are whipped out (70 percent of black babies born out of wedlock) and then claims are tossed around cavalierly, (black culture doesn't value marriage.) The problem isn't that "culture" doesn't exist, nor is it that elements of that "culture" might impair upward mobility.
  • It defies logic to think that any group, in a generationaly entrenched position, would not develop codes and mores for how to survive in that position. African-Americans, themselves, from poor to bourgeois, are the harshest critics of the street mentality. Of course, most white people only pay attention when Bill Cosby or Barack Obama are making that criticism. The problem is that rarely do such critiques ask  why anyone would embrace such values. Moreover, they tend to assume that there's something uniquely "black" about those values, and their the embrace.
  • If you are a young person living in an environment where violence is frequent and random, the willingness to meet any hint of violence with yet more violence is a shield.
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  • once I was acculturated to the notion that often the quickest way to forestall more fighting, is to fight, I was a believer. And maybe it's wrong to say this, but it made my the rest of my time in Baltimore a lot easier, because the willingness to fight isn't just about yourself, it's a signal to your peer group. 
  • To the young people in my neighborhood, friendship was defined by having each other's back. And in that way, the personal shields, the personal willingness to meet violence with violence, combined and became a collective, neighborhood shield--a neighborhood rep.
  • I think one can safely call that an element of a kind of street culture. It's also an element which--once one leaves the streets--is a great impediment.
  • I suspect that a large part of the problem, when we talk about culture, is an inability to code-switch, to understand that the language of Rohan is not the language of Mordor
  • how difficult it is to get people to discard practices which were essential to them in one world, but hinder their advancement into another. And then there's the fear of that other world, that sense that if you discard those practices, you have discarded some of yourself, and done it in pursuit of a world, that you may not master. 
  • The streets are like any other world--we all assume an armor, a garment to suit that world. And indeed, in every world, some people wear the armor better than others, and thus reap considerable social reward.
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    A Culture of Poverty
Weiye Loh

Fatalism (Stanford Encyclopedia of Philosophy) - 0 views

  • This view may be argued for in various ways: by appeal to logical laws and metaphysical necessities; by appeal to the existence and nature of God; by appeal to causal determinism. When argued for in the first way, it is commonly called “Logical fatalism” (or, in some cases, “Metaphysical fatalism”); when argued for in the second way, it is commonly called “Theological fatalism”. When argued for in the third way it is not now commonly referred to as “fatalism” at all, and such arguments will not be discussed here.
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    "fatalism" is commonly used to refer to an attitude of resignation in the face of some future event or events which are thought to be inevitable
Weiye Loh

Is Pure Altruism Possible? - NYTimes.com - 0 views

  • It’s undeniable that people sometimes act in a way that benefits others, but it may seem that they always get something in return — at the very least, the satisfaction of having their desire to help fulfilled.
  • Contemporary discussions of altruism quickly turn to evolutionary explanations. Reciprocal altruism and kin selection are the two main theories. According to reciprocal altruism, evolution favors organisms that sacrifice their good for others in order to gain a favor in return. Kin selection — the famous “selfish gene” theory popularized by Richard Dawkins — says that an individual who behaves altruistically towards others who share its genes will tend to reproduce those genes. Organisms may be altruistic; genes are selfish. The feeling that loving your children more than yourself is hard-wired lends plausibility to the theory of kin selection.
  • The defect of reciprocal altruism is clear. If a person acts to benefit another in the expectation that the favor will be returned, the natural response is: “That’s not altruism!”  Pure altruism, we think, requires a person to sacrifice for another without consideration of personal gain. Doing good for another person because something’s in it for the do-er is the very opposite of what we have in mind. Kin selection does better by allowing that organisms may genuinely sacrifice their interests for another, but it fails to explain why they sometimes do so for those with whom they share no genes
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  • When we ask whether human beings are altruistic, we want to know about their motives or intentions. Biological altruism explains how unselfish behavior might have evolved but, as Frans de Waal suggested in his column in The Stone on Sunday, it implies nothing about the motives or intentions of the agent: after all, birds and bats and bees can act altruistically. This fact helps to explain why, despite these evolutionary theories, the view that people never intentionally act to benefit others except to obtain some good for themselves still possesses a powerful lure over our thinking.
  • The lure of this view — egoism — has two sources, one psychological, the other logical. Consider first the psychological. One reason people deny that altruism exists is that, looking inward, they doubt the purity of their own motives. We know that even when we appear to act unselfishly, other reasons for our behavior often rear their heads: the prospect of a future favor, the boost to reputation, or simply the good feeling that comes from appearing to act unselfishly. As Kant and Freud observed, people’s true motives may be hidden, even (or perhaps especially) from themselves. Even if we think we’re acting solely to further another person’s good, that might not be the real reason. (There might be no single “real reason” — actions can have multiple motives.)
  • So the psychological lure of egoism as a theory of human action is partly explained by a certain humility or skepticism people have about their own or others’ motives
  • There’s also a less flattering reason: denying the possibility of pure altruism provides a convenient excuse for selfish behavior.
  • The logical lure of egoism is different: the view seems impossible to disprove. No matter how altruistic a person appears to be, it’s possible to conceive of her motive in egoistic terms.
  • The impossibility of disproving egoism may sound like a virtue of the theory, but, as philosophers of science know, it’s really a fatal drawback. A theory that purports to tell us something about the world, as egoism does, should be falsifiable. Not false, of course, but capable of being tested and thus proved false. If every state of affairs is compatible with egoism, then egoism doesn’t tell us anything distinctive about how things are.
  • s ambiguity in the concepts of desire and the satisfaction of desire. If people possess altruistic motives, then they sometimes act to benefit others without the prospect of gain to themselves. In other words, they desire the good of others for its own sake, not simply as a means to their own satisfaction.
  • Still, when our desires are satisfied we normally experience satisfaction; we feel good when we do good. But that doesn’t mean we do good only in order to get that “warm glow” — that our true incentives are self-interested (as economists tend to claim). Indeed, as de Waal argues, if we didn’t desire the good of others for its own sake, then attaining it wouldn’t produce the warm glow.
  • Common sense tells us that some people are more altruistic than others. Egoism’s claim that these differences are illusory — that deep down, everybody acts only to further their own interests — contradicts our observations and deep-seated human practices of moral evaluation.
  • At the same time, we may notice that generous people don’t necessarily suffer more or flourish less than those who are more self-interested.
  • The point is rather that the kind of altruism we ought to encourage, and probably the only kind with staying power, is satisfying to those who practice it. Studies of rescuers show that they don’t believe their behavior is extraordinary; they feel they must do what they do, because it’s just part of who they are. The same holds for more common, less newsworthy acts — working in soup kitchens, taking pets to people in nursing homes, helping strangers find their way, being neighborly. People who act in these ways believe that they ought to help others, but they also want to help, because doing so affirms who they are and want to be and the kind of world they want to exist. As Prof. Neera Badhwar has argued, their identity is tied up with their values, thus tying self-interest and altruism together. The correlation between doing good and feeling good is not inevitable— inevitability lands us again with that empty, unfalsifiable egoism — but it is more than incidental.
  • Altruists should not be confused with people who automatically sacrifice their own interests for others.
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    Is Pure Altruism Possible?
Weiye Loh

Rationally Speaking: Are Intuitions Good Evidence? - 0 views

  • Is it legitimate to cite one’s intuitions as evidence in a philosophical argument?
  • appeals to intuitions are ubiquitous in philosophy. What are intuitions? Well, that’s part of the controversy, but most philosophers view them as intellectual “seemings.” George Bealer, perhaps the most prominent defender of intuitions-as-evidence, writes, “For you to have an intuition that A is just for it to seem to you that A… Of course, this kind of seeming is intellectual, not sensory or introspective (or imaginative).”2 Other philosophers have characterized them as “noninferential belief due neither to perception nor introspection”3 or alternatively as “applications of our ordinary capacities for judgment.”4
  • Philosophers may not agree on what, exactly, intuition is, but that doesn’t stop them from using it. “Intuitions often play the role that observation does in science – they are data that must be explained, confirmers or the falsifiers of theories,” Brian Talbot says.5 Typically, the way this works is that a philosopher challenges a theory by applying it to a real or hypothetical case and showing that it yields a result which offends his intuitions (and, he presumes, his readers’ as well).
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  • For example, John Searle famously appealed to intuition to challenge the notion that a computer could ever understand language: “Imagine a native English speaker who knows no Chinese locked in a room full of boxes of Chinese symbols (a data base) together with a book of instructions for manipulating the symbols (the program). Imagine that people outside the room send in other Chinese symbols which, unknown to the person in the room, are questions in Chinese (the input). And imagine that by following the instructions in the program the man in the room is able to pass out Chinese symbols which are correct answers to the questions (the output)… If the man in the room does not understand Chinese on the basis of implementing the appropriate program for understanding Chinese then neither does any other digital computer solely on that basis because no computer, qua computer, has anything the man does not have.” Should we take Searle’s intuition that such a system would not constitute “understanding” as good evidence that it would not? Many critics of the Chinese Room argument argue that there is no reason to expect our intuitions about intelligence and understanding to be reliable.
  • Ethics leans especially heavily on appeals to intuition, with a whole school of ethicists (“intuitionists”) maintaining that a person can see the truth of general ethical principles not through reason, but because he “just sees without argument that they are and must be true.”6
  • Intuitions are also called upon to rebut ethical theories such as utilitarianism: maximizing overall utility would require you to kill one innocent person if, in so doing, you could harvest her organs and save five people in need of transplants. Such a conclusion is taken as a reductio ad absurdum, requiring utilitarianism to be either abandoned or radically revised – not because the conclusion is logically wrong, but because it strikes nearly everyone as intuitively wrong.
  • British philosopher G.E. Moore used intuition to argue that the existence of beauty is good irrespective of whether anyone ever gets to see and enjoy that beauty. Imagine two planets, he said, one full of stunning natural wonders – trees, sunsets, rivers, and so on – and the other full of filth. Now suppose that nobody will ever have the opportunity to glimpse either of those two worlds. Moore concluded, “Well, even so, supposing them quite apart from any possible contemplation by human beings; still, is it irrational to hold that it is better that the beautiful world should exist than the one which is ugly? Would it not be well, in any case, to do what we could to produce it rather than the other? Certainly I cannot help thinking that it would."7
  • Although similar appeals to intuition can be found throughout all the philosophical subfields, their validity as evidence has come under increasing scrutiny over the last two decades, from philosophers such as Hilary Kornblith, Robert Cummins, Stephen Stich, Jonathan Weinberg, and Jaakko Hintikka (links go to representative papers from each philosopher on this issue). The severity of their criticisms vary from Weinberg’s warning that “We simply do not know enough about how intuitions work,” to Cummins’ wholesale rejection of philosophical intuition as “epistemologically useless.”
  • One central concern for the critics is that a single question can inspire totally different, and mutually contradictory, intuitions in different people.
  • For example, I disagree with Moore’s intuition that it would be better for a beautiful planet to exist than an ugly one even if there were no one around to see it. I can’t understand what the words “better” and “worse,” let alone “beautiful” and “ugly,” could possibly mean outside the domain of the experiences of conscious beings
  • If we want to take philosophers’ intuitions as reason to believe a proposition, then the existence of opposing intuitions leaves us in the uncomfortable position of having reason to believe both a proposition and its opposite.
  • “I suspect there is overall less agreement than standard philosophical practice presupposes, because having the ‘right’ intuitions is the entry ticket to various subareas of philosophy,” Weinberg says.
  • But the problem that intuitions are often not universally shared is overshadowed by another problem: even if an intuition is universally shared, that doesn’t mean it’s accurate. For in fact there are many universal intuitions that are demonstrably false.
  • People who have not been taught otherwise typically assume that an object dropped out of a moving plane will fall straight down to earth, at exactly the same latitude and longitude from which it was dropped. What will actually happen is that, because the object begins its fall with the same forward momentum it had while it was on the plane, it will continue to travel forward, tracing out a curve as it falls and not a straight line. “Considering the inadequacies of ordinary physical intuitions, it is natural to wonder whether ordinary moral intuitions might be similarly inadequate,” Princeton’s Gilbert Harman has argued,9 and the same could be said for our intuitions about consciousness, metaphysics, and so on.
  • We can’t usually “check” the truth of our philosophical intuitions externally, with an experiment or a proof, the way we can in physics or math. But it’s not clear why we should expect intuitions to be true. If we have an innate tendency towards certain intuitive beliefs, it’s likely because they were useful to our ancestors.
  • But there’s no reason to expect that the intuitions which were true in the world of our ancestors would also be true in other, unfamiliar contexts
  • And for some useful intuitions, such as moral ones, “truth” may have been beside the point. It’s not hard to see how moral intuitions in favor of fairness and generosity would have been crucial to the survival of our ancestors’ tribes, as would the intuition to condemn tribe members who betrayed those reciprocal norms. If we can account for the presence of these moral intuitions by the fact that they were useful, is there any reason left to hypothesize that they are also “true”? The same question could be asked of the moral intuitions which Jonathan Haidt has classified as “purity-based” – an aversion to incest, for example, would clearly have been beneficial to our ancestors. Since that fact alone suffices to explain the (widespread) presence of the “incest is morally wrong” intuition, why should we take that intuition as evidence that “incest is morally wrong” is true?
  • The still-young debate over intuition will likely continue to rage, especially since it’s intertwined with a rapidly growing body of cognitive and social psychological research examining where our intuitions come from and how they vary across time and place.
  • its resolution bears on the work of literally every field of analytic philosophy, except perhaps logic. Can analytic philosophy survive without intuition? (If so, what would it look like?) And can the debate over the legitimacy of appeals to intuition be resolved with an appeal to intuition?
Weiye Loh

Rationally Speaking: Studying folk morality: philosophy, psychology, or what? - 0 views

  • in the magazine article Joshua mentions several studies of “folk morality,” i.e. of how ordinary people think about moral problems. The results are fascinating. It turns out that people’s views are correlated with personality traits, with subjects who score high on “openness to experience” being reliably more relativists than objectivists about morality (I am not using the latter term in the infamous Randyan meaning here, but as Knobe does, to indicate the idea that morality has objective bases).
  • Other studies show that people who are capable of considering multiple options in solving mathematical puzzles also tend to be moral relativists, and — in a study co-authored by Knobe himself — the very same situation (infanticide) was judged along a sliding scale from objectivism to relativism depending on whether the hypothetical scenario involved a fellow American (presumably sharing our same general moral values), the member of an imaginary Amazonian tribe (for which infanticide was acceptable), and an alien from the planet Pentar (belonging to a race whose only goal in life is to turn everything into equilateral pentagons, and killing individuals that might get in the way of that lofty objective is a duty). Oh, and related research also shows that young children tend to be objectivists, while young adults are usually relativists — but that later in life one’s primordial objectivism apparently experiences a comeback.
  • This is all very interesting social science, but is it philosophy? Granted, the differences between various disciplines are often not clear cut, and of course whenever people engage in truly inter-disciplinary work we should simply applaud the effort and encourage further work. But I do wonder in what sense, if any, the kinds of results that Joshua and his colleagues find have much to do with moral philosophy.
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  • there seems to me the potential danger of confusing various categories of moral discourse. For instance, are the “folks” studied in these cases actually relativist, or perhaps adherents to one of several versions of moral anti-realism? The two are definitely not the same, but I doubt that the subjects in question could tell the difference (and I wouldn’t expect them to, after all they are not philosophers).
  • why do we expect philosophers to learn from “folk morality” when we do not expect, say, physicists to learn from folk physics (which tends to be Aristotelian in nature), or statisticians from people’s understanding of probability theory (which is generally remarkably poor, as casino owners know very well)? Or even, while I’m at it, why not ask literary critics to discuss Shakespeare in light of what common folks think about the bard (making sure, perhaps, that they have at least read his works, and not just watched the movies)?
  • Hence, my other examples of stat (i.e., math) and literary criticism. I conceive of philosophy in general, and moral philosophy in particular, as more akin to a (science-informed, to be sure) mix between logic and criticism. Some moral philosophy consists in engaging an “if ... then” sort of scenario, akin to logical-mathematical thinking, where one begins with certain axioms and attempts to derive the consequences of such axioms. In other respects, moral philosophers exercise reflective criticism concerning those consequences as they might be relevant to practical problems.
  • For instance, we may write philosophically about abortion, and begin our discussion from a comparison of different conceptions of “person.” We might conclude that “if” one adopts conception X of what a person is, “then” abortion is justifiable under such and such conditions; while “if” one adopts conception Y of a person, “then” abortion is justifiable under a different set of conditions, or not justifiable at all. We could, of course, back up even further and engage in a discussion of what “personhood” is, thus moving from moral philosophy to metaphysics.
  • Nowhere in the above are we going to ask “folks” what they think a person is, or how they think their implicit conception of personhood informs their views on abortion. Of course people’s actual views on abortion are crucial — especially for public policy — and they are intrinsically interesting to social scientists. But they don’t seem to me to make much more contact with philosophy than the above mentioned popular opinions on Shakespeare make contact with serious literary criticism. And please, let’s not play the cheap card of “elitism,” unless we are willing to apply the label to just about any intellectual endeavor, in any discipline.
  • There is one area in which experimental philosophy can potentially contribute to philosophy proper (as opposed to social science). Once we have a more empirically grounded understanding of what people’s moral reasoning actually is, then we can analyze the likely consequences of that reasoning for a variety of societal issues. But now we would be doing something more akin to political than moral philosophy.
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    My colleague Joshua Knobe at Yale University recently published an intriguing article in The Philosopher's Magazine about the experimental philosophy of moral decision making. Joshua and I have had a nice chat during a recent Rationally Speaking podcast dedicated to experimental philosophy, but I'm still not convinced about the whole enterprise.
Weiye Loh

Roger Pielke Jr.'s Blog: Two View on Science and Politics - 0 views

  • My father is testifying before the House Energy & Committee today in what will inevitably be a show hearing using climate scientists as props
  • I did note a stark contrast in how Richard Somerville presented the role of science and policy and that presented by my father.  Here is what Somerville says (PDF): [T]he need to drastically reduce global greenhouse gas emissions is urgent, and the urgency is scientific, not political. Mother Nature herself thus imposes a timescale on when emissions need to peak and then begin to decline rapidly. This urgency is therefore not ideological at all, but rather is due to the physics and biogeochemistry of the climate system itself. Diplomats and legislators, as well as heads of state worldwide, are powerless to alter the laws of nature and must face scientific facts and the hard evidence of scientific findings.
  • Contrast that with what my father says (PDF): Decisions about government regulation are ultimately legal, administrative, legislative, and political decisions. As such they can be informed by scientific considerations, but they are not determined by them. In my testimony, I seek to share my perspectives on the science of climate based on my work in this field over the past four decades.
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  • Doug said... 1 If legal, administrative, legislative, and political decisions that are allegedly based on science are not determined by the science than they are not based in science. They are scientifically unsubstantiated. I find this a very poor way to govern, rejecting science when it doesn't meet your political agenda.
  • True science is apolitical and non-ideological. Only the use of science is politicized.
  • I totally agree with you about the distinction between science and policy. I'm also fascinated by the concept of urgency. In the case of a developing disaster, "urgent" is logically a fairly short space on the time line. Before that, it's not yet urgent. After that, it's too late. Any analysis that does not acknowledge this basic logic is likely to strain credibility. And any uncertainty about future climate (and impacts) implies uncertainty about where on the time line the "urgent" window is or will be located. The uncertainty has to be small, or there is no way to know we're inside that short time period. And "maybe it's urgent" or "maybe it's too late" are not very persuasive arguments.
Weiye Loh

Why You Can't Say "Twitter" Or "Facebook" On French TV - 0 views

  • The regulatory decree was issued on May 27. The rationale behind the decision? Apparently mentioning social networks like Twitter or Facebook by name goes against a 1992 decree prohibiting surreptitious advertising. Encouraging users to engage with the content creators or give their own feedback is “clandestine advertising” for the social networks themselves.
  • Christine Kelly, a spokesperson for the CSA, tried to explain the decision by saying it “would be a distortion of competition” to “give preference to Facebook, which is worth billions of dollars, when there are many other social networks that are struggling for recognition.”
  • Matthew Fraser, a Canadian-born journalist who lives and works in Paris, sees this ruling as an example of the “deeply rooted animosity in the French psyche toward Anglo-Saxon cultural domination.” Fraser writes that “sometimes this cultural resentment finds expression in French regulations and laws.”
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  • Mashable always give misleading news with misleading titles and ridiculous analysis. In France, you cannot do neither good nor bad ad for any brand or company in a TV program (unless you pay your ad slot of course). With the coming of social networks, people advertise their page and by the way facebook and twitter. That’s why the ban comes to say that facebook and twitter are also brands and companies like others. Actually, you can say “Facebook” and “twitter” and whatever you want… in any TV program in France, but you cannot advertise for them. So please be less simplistic and a little more percise in you articles.
  • By this logic no personal brand (i.e. Brad Pitt, Angelina Jolie, and so on) could be mentioned without them paying for it. And by this logic, public relations could not exist as a profession in France.
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    French broadcasters who want to encourage viewer interaction via Facebook or Twitter accounts can no longer do so. The "follow us on Twitter" or "Like us on Facebook" refrains - common parlance in American broadcasting - are no longer allowed on French channels. The networks can still say "find us on social networks," but services cannot be mentioned by name.
Weiye Loh

Does Anything Matter? by Peter Singer - Project Syndicate - 0 views

  • Although this view of ethics has often been challenged, many of the objections have come from religious thinkers who appealed to God’s commands. Such arguments have limited appeal in the largely secular world of Western philosophy. Other defenses of objective truth in ethics made no appeal to religion, but could make little headway against the prevailing philosophical mood.
  • Many people assume that rationality is always instrumental: reason can tell us only how to get what we want, but our basic wants and desires are beyond the scope of reasoning. Not so, Parfit argues. Just as we can grasp the truth that 1 + 1 = 2, so we can see that I have a reason to avoid suffering agony at some future time, regardless of whether I now care about, or have desires about, whether I will suffer agony at that time. We can also have reasons (though not always conclusive reasons) to prevent others from suffering agony. Such self-evident normative truths provide the basis for Parfit’s defense of objectivity in ethics.
  • One major argument against objectivism in ethics is that people disagree deeply about right and wrong, and this disagreement extends to philosophers who cannot be accused of being ignorant or confused. If great thinkers like Immanuel Kant and Jeremy Bentham disagree about what we ought to do, can there really be an objectively true answer to that question? Parfit’s response to this line of argument leads him to make a claim that is perhaps even bolder than his defense of objectivism in ethics. He considers three leading theories about what we ought to do – one deriving from Kant, one from the social-contract tradition of Hobbes, Locke, Rousseau, and the contemporary philosophers John Rawls and T.M. Scanlon, and one from Bentham’s utilitarianism – and argues that the Kantian and social-contract theories must be revised in order to be defensible.
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  • he argues that these revised theories coincide with a particular form of consequentialism, which is a theory in the same broad family as utilitarianism. If Parfit is right, there is much less disagreement between apparently conflicting moral theories than we all thought. The defenders of each of these theories are, in Parfit’s vivid phrase, “climbing the same mountain on different sides.”
  • Parfit’s real interest is in combating subjectivism and nihilism. Unless he can show that objectivism is true, he believes, nothing matters.
  • When Parfit does come to the question of “what matters,” his answer might seem surprisingly obvious. He tells us, for example, that what matters most now is that “we rich people give up some of our luxuries, ceasing to overheat the Earth’s atmosphere, and taking care of this planet in other ways, so that it continues to support intelligent life.” Many of us had already reached that conclusion. What we gain from Parfit’s work is the possibility of defending these and other moral claims as objective truths.
  •  
    Can moral judgments be true or false? Or is ethics, at bottom, a purely subjective matter, for individuals to choose, or perhaps relative to the culture of the society in which one lives? We might have just found out the answer. Among philosophers, the view that moral judgments state objective truths has been out of fashion since the 1930's, when logical positivists asserted that, because there seems to be no way of verifying the truth of moral judgments, they cannot be anything other than expressions of our feelings or attitudes. So, for example, when we say, "You ought not to hit that child," all we are really doing is expressing our disapproval of your hitting the child, or encouraging you to stop hitting the child. There is no truth to the matter of whether or not it is wrong for you to hit the child.
Weiye Loh

Roger Pielke Jr.'s Blog: Wanted: Less Spin, More Informed Debate - 0 views

  • , the rejection of proposals that suggest starting with a low carbon price is thus a pretty good guarantee against any carbon pricing at all.  It is rather remarkable to see advocates for climate action arguing against a policy that recommends implementing a carbon price, simply because it does not start high enough for their tastes.  For some, idealism trumps pragmatism, even if it means no action at all.
  • Ward writes: . . . climate change is the result of a number of market failures, the largest of which arises from the fact that the prices of products and services involving emissions of greenhouse gases do not reflect the true costs of the damage caused through impacts on the climate. . . All serious economic analyses of how to tackle climate change identify the need to correct this market failure through a carbon price, which can be implemented, for instance, through cap and trade schemes or carbon taxes. . . A carbon price can be usefully supplemented by improvements in innovation policies, but it needs to be at the core of action on climate change, as this paper by Carolyn Fischer and Richard Newell points out.
  • First, the criticism is off target. A low and rising carbon price is in fact a central element to the policy recommendations advanced by the Hartwell Group in Climate Pragmatism, the Hartwell Paper, and as well, in my book The Climate Fix.  In Climate Pragmatism, we approvingly cite Japan's low-but-rising fossil fuels tax and discuss a range of possible fees or taxes on fossil fuels, implemented, not to penalize energy use or price fossil fuels out of the market, but rather to ensure that as we benefit from today’s energy resources we are setting aside the funds necessary to accelerate energy innovation and secure the nation’s energy future.
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  • Here is another debating lesson -- before engaging in public not only should one read the materials that they are critiquing, they should also read the materials that they cite in support of their own arguments. This is not the first time that Bob Ward has put out misleading information related to my work.  Ever since we debated in public at the Royal Institution, Bob has adopted guerrilla tactics, lobbing nonsense into the public arena and then hiding when challenged to support or defend his views.  As readers here know, I am all for open and respectful debate over these important topics.  Why is that instead, all we get is poorly informed misdirection and spin? Despite the attempts at spin, I'd welcome Bob's informed engagement on this topic. Perhaps he might start by explaining which of the 10 statements that I put up on the mathematics and logic underlying climate pragmatism is incorrect.
  • In comments to another blog, I've identified Bob as a PR flack. I see no reason to change that assessment. In fact, his actions only confirm it. Where does he fit into a scientific debate?
  • Thanks for the comment, but I'll take the other side ;-)First, this is a policy debate that involves various scientific, economic, political analyses coupled with various values commitments including monied interests -- and as such, PR guys are as welcome as anyone else.That said, the problem here is not that Ward is a PR guy, but that he is trying to make his case via spin and misrepresentation. That gets noticed pretty quickly by anyone paying attention and is easily shot down.
Weiye Loh

Rationally Speaking: Ray Kurzweil and the Singularity: visionary genius or pseudoscient... - 0 views

  • I will focus on a single detailed essay he wrote entitled “Superintelligence and Singularity,” which was originally published as chapter 1 of his The Singularity is Near (Viking 2005), and has been reprinted in an otherwise insightful collection edited by Susan Schneider, Science Fiction and Philosophy.
  • Kurzweil begins by telling us that he gradually became aware of the coming Singularity, in a process that, somewhat peculiarly, he describes as a “progressive awakening” — a phrase with decidedly religious overtones. He defines the Singularity as “a future period during which the pace of technological change will be so rapid, its impact so deep, that human life will be irreversibly transformed.” Well, by that definition, we have been through several “singularities” already, as technology has often rapidly and irreversibly transformed our lives.
  • The major piece of evidence for Singularitarianism is what “I [Kurzweil] have called the law of accelerating returns (the inherent acceleration of the rate of evolution, with technological evolution as a continuation of biological evolution).”
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  • the first obvious serious objection is that technological “evolution” is in no logical way a continuation of biological evolution — the word “evolution” here being applied with completely different meanings. And besides, there is no scientifically sensible way in which biological evolution has been accelerating over the several billion years of its operation on our planet. So much for scientific accuracy and logical consistency.
  • here is a bit that will give you an idea of why some people think of Singularitarianism as a secular religion: “The Singularity will allow us to transcend [the] limitations of our biological bodies and brains. We will gain power over our fates. Our mortality will be in our own hands. We will be able to live as long as we want.”
  • Fig. 2 of that essay shows a progression through (again, entirely arbitrary) six “epochs,” with the next one (#5) occurring when there will be a merger between technological and human intelligence (somehow, a good thing), and the last one (#6) labeled as nothing less than “the universe wakes up” — a nonsensical outcome further described as “patterns of matter and energy in the universe becom[ing] saturated with intelligence processes and knowledge.” This isn’t just science fiction, it is bad science fiction.
  • “a serious assessment of the history of technology reveals that technological change is exponential. Exponential growth is a feature of any evolutionary process.” First, it is highly questionable that one can even measure “technological change” on a coherent uniform scale. Yes, we can plot the rate of, say, increase in microprocessor speed, but that is but one aspect of “technological change.” As for the idea that any evolutionary process features exponential growth, I don’t know where Kurzweil got it, but it is simply wrong, for one thing because biological evolution does not have any such feature — as any student of Biology 101 ought to know.
  • Kurzweil’s ignorance of evolution is manifested again a bit later, when he claims — without argument, as usual — that “Evolution is a process of creating patterns of increasing order. ... It’s the evolution of patterns that constitutes the ultimate story of the world. ... Each stage or epoch uses the information-processing methods of the previous epoch to create the next.” I swear, I was fully expecting a scholarly reference to Deepak Chopra at the end of that sentence. Again, “evolution” is a highly heterogeneous term that picks completely different concepts, such as cosmic “evolution” (actually just change over time), biological evolution (which does have to do with the creation of order, but not in Kurzweil’s blatantly teleological sense), and technological “evolution” (which is certainly yet another type of beast altogether, since it requires intelligent design). And what on earth does it mean that each epoch uses the “methods” of the previous one to “create” the next one?
  • As we have seen, the whole idea is that human beings will merge with machines during the ongoing process of ever accelerating evolution, an event that will eventually lead to the universe awakening to itself, or something like that. Now here is the crucial question: how come this has not happened already?
  • To appreciate the power of this argument you may want to refresh your memory about the Fermi Paradox, a serious (though in that case, not a knockdown) argument against the possibility of extraterrestrial intelligent life. The story goes that physicist Enrico Fermi (the inventor of the first nuclear reactor) was having lunch with some colleagues, back in 1950. His companions were waxing poetic about the possibility, indeed the high likelihood, that the galaxy is teeming with intelligent life forms. To which Fermi asked something along the lines of: “Well, where are they, then?”
  • The idea is that even under very pessimistic (i.e., very un-Kurzweil like) expectations about how quickly an intelligent civilization would spread across the galaxy (without even violating the speed of light limit!), and given the mind boggling length of time the galaxy has already existed, it becomes difficult (though, again, not impossible) to explain why we haven’t seen the darn aliens yet.
  • Now, translate that to Kurzweil’s much more optimistic predictions about the Singularity (which allegedly will occur around 2045, conveniently just a bit after Kurzweil’s expected demise, given that he is 63 at the time of this writing). Considering that there is no particular reason to think that planet earth, or the human species, has to be the one destined to trigger the big event, why is it that the universe hasn’t already “awakened” as a result of a Singularity occurring somewhere else at some other time?
Weiye Loh

More Than 1 Billion People Are Hungry in the World - By Abhijit Banerjee and Esther Duf... - 0 views

  • We were starting to feel very bad for him and his family, when we noticed the TV and other high-tech gadgets. Why had he bought all these things if he felt the family did not have enough to eat? He laughed, and said, "Oh, but television is more important than food!"
  • For many in the West, poverty is almost synonymous with hunger. Indeed, the announcement by the United Nations Food and Agriculture Organization in 2009 that more than 1 billion people are suffering from hunger grabbed headlines in a way that any number of World Bank estimates of how many poor people live on less than a dollar a day never did. COMMENTS (7) SHARE: Twitter   Reddit   Buzz   More... But is it really true? Are there really more than a billion people going to bed hungry each night?
  • unfortunately, this is not always the world as the experts view it. All too many of them still promote sweeping, ideological solutions to problems that defy one-size-fits-all answers, arguing over foreign aid, for example, while the facts on the ground bear little resemblance to the fierce policy battles they wage.
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  • Jeffrey Sachs, an advisor to the United Nations and director of Columbia University's Earth Institute, is one such expert. In books and countless speeches and television appearances, he has argued that poor countries are poor because they are hot, infertile, malaria-infested, and often landlocked; these factors, however, make it hard for them to be productive without an initial large investment to help them deal with such endemic problems. But they cannot pay for the investments precisely because they are poor -- they are in what economists call a "poverty trap." Until something is done about these problems, neither free markets nor democracy will do very much for them.
  • But then there are others, equally vocal, who believe that all of Sachs's answers are wrong. William Easterly, who battles Sachs from New York University at the other end of Manhattan, has become one of the most influential aid critics in his books, The Elusive Quest for Growth and The White Man's Burden. Dambisa Moyo, an economist who worked at Goldman Sachs and the World Bank, has joined her voice to Easterly's with her recent book, Dead Aid. Both argue that aid does more bad than good. It prevents people from searching for their own solutions, while corrupting and undermining local institutions and creating a self-perpetuating lobby of aid agencies.
  • The best bet for poor countries, they argue, is to rely on one simple idea: When markets are free and the incentives are right, people can find ways to solve their problems. They do not need handouts from foreigners or their own governments.
  • According to Easterly, there is no such thing as a poverty trap.
  • To find out whether there are in fact poverty traps, and, if so, where they are and how to help the poor get out of them, we need to better understand the concrete problems they face. Some aid programs help more than others, but which ones? Finding out required us to step out of the office and look more carefully at the world. In 2003, we founded what became the Abdul Latif Jameel Poverty Action Lab, or J-PAL. A key part of our mission is to research by using randomized control trials -- similar to experiments used in medicine to test the effectiveness of a drug -- to understand what works and what doesn't in the real-world fight against poverty. In practical terms, that meant we'd have to start understanding how the poor really live their lives.
  • Take, for example, Pak Solhin, who lives in a small village in West Java, Indonesia. He once explained to us exactly how a poverty trap worked. His parents used to have a bit of land, but they also had 13 children and had to build so many houses for each of them and their families that there was no land left for cultivation. Pak Solhin had been working as a casual agricultural worker, which paid up to 10,000 rupiah per day (about $2) for work in the fields. A recent hike in fertilizer and fuel prices, however, had forced farmers to economize. The local farmers decided not to cut wages, Pak Solhin told us, but to stop hiring workers instead. As a result, in the two months before we met him in 2008, he had not found a single day of agricultural labor. He was too weak for the most physical work, too inexperienced for more skilled labor, and, at 40, too old to be an apprentice. No one would hire him.
  • Pak Solhin, his wife, and their three children took drastic steps to survive. His wife left for Jakarta, some 80 miles away, where she found a job as a maid. But she did not earn enough to feed the children. The oldest son, a good student, dropped out of school at 12 and started as an apprentice on a construction site. The two younger children were sent to live with their grandparents. Pak Solhin himself survived on the roughly 9 pounds of subsidized rice he got every week from the government and on fish he caught at a nearby lake. His brother fed him once in a while. In the week before we last spoke with him, he had eaten two meals a day for four days, and just one for the other three.
  • Pak Solhin appeared to be out of options, and he clearly attributed his problem to a lack of food. As he saw it, farmers weren't interested in hiring him because they feared they couldn't pay him enough to avoid starvation; and if he was starving, he would be useless in the field. What he described was the classic nutrition-based poverty trap, as it is known in the academic world. The idea is simple: The human body needs a certain number of calories just to survive. So when someone is very poor, all the food he or she can afford is barely enough to allow for going through the motions of living and earning the meager income used to buy that food. But as people get richer, they can buy more food and that extra food goes into building strength, allowing people to produce much more than they need to eat merely to stay alive. This creates a link between income today and income tomorrow: The very poor earn less than they need to be able to do significant work, but those who have enough to eat can work even more. There's the poverty trap: The poor get poorer, and the rich get richer and eat even better, and get stronger and even richer, and the gap keeps increasing.
  • But though Pak Solhin's explanation of how someone might get trapped in starvation was perfectly logical, there was something vaguely troubling about his narrative. We met him not in war-infested Sudan or in a flooded area of Bangladesh, but in a village in prosperous Java, where, even after the increase in food prices in 2007 and 2008, there was clearly plenty of food available and a basic meal did not cost much. He was still eating enough to survive; why wouldn't someone be willing to offer him the extra bit of nutrition that would make him productive in return for a full day's work? More generally, although a hunger-based poverty trap is certainly a logical possibility, is it really relevant for most poor people today? What's the best way, if any, for the world to help?
Weiye Loh

The new SingaNews - 13 views

Hi Valerie, I fully agree with your reply. However, there are some issues I will like to raise. "It seems a Christian cannot do anything in the secular realm without drawing criticisms or at th...

SingaNews Christian Fundamentalism Family Objectivity

guanyou chen

Ethically confusing defamation problem - 4 views

Link: http://www.rednano.sg/sfe/pastnews.action?&querystring=online%20defamation&pubid=ST&sort=D Summary: A man who visited and then later robbed a prostitute was chastised a...

defamation online forum

started by guanyou chen on 19 Aug 09 no follow-up yet
Weiye Loh

Libertarianism Is Marxism of the Right - 4 views

http://www.commongroundcommonsense.org/forums/lofiversion/index.php/t21933.html "Because 95 percent of the libertarianism one encounters at cocktail parties, on editorial pages, and on Capitol Hil...

Libertarianism Marxism

started by Weiye Loh on 28 Aug 09 no follow-up yet
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