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A language isolated in its own branch within a family, such as Armenian within Indo-European, is often also called an isolate, but the meaning of isolate in such cases is usually clarified. For instance, Armenian may be referred to as an "Indo-European isolate". By contrast, so far as is known, the Basque language is an absolute isolate: it has not been shown to be related to any other language despite numerous attempts.

The common ancestor of a language family is seldom known directly since most languages have a relatively short recorded history. However, it is possible to recover many features of a proto-language by applying the comparative method, a reconstructive procedure worked out by 19th century linguist August Schleicher.

The knowledge that video games possess this power, that they allow us to adopt new identities and grant us new ways of seeing ourselves, is as old as Mario’s quest for his princess.

One common strategy for thinking about this is to suggest that what we used to call the whole universe is just a small part of everything there is, and that we live in a kind of bubble universe, a small region of something much larger

Newton realized there had to be some force holding the moon in its orbit around the earth, to keep it from wandering off, and he knew also there was a force that was pulling the apple down to the earth. And so what suddenly struck him was that those could be one and the same thing, the same force

That was a physical discovery, a physical discovery of momentous importance, as important as anything you could ever imagine because it knit together the terrestrial realm and the celestial realm into one common physical picture. It was also a philosophical discovery in the sense that philosophy is interested in the fundamental natures of things.

There are other ideas, for instance that maybe there might be special sorts of laws, or special sorts of explanatory principles, that would apply uniquely to the initial state of the universe.

The basic philosophical question, going back to Plato, is "What is x?" What is virtue? What is justice? What is matter? What is time? You can ask that about dark energy - what is it? And it's a perfectly good question.

right now there are just way too many freely adjustable parameters in physics. Everybody agrees about that. There seem to be many things we call constants of nature that you could imagine setting at different values, and most physicists think there shouldn't be that many, that many of them are related to one another. Physicists think that at the end of the day there should be one complete equation to describe all physics, because any two physical systems interact and physics has to tell them what to do. And physicists generally like to have only a few constants, or parameters of nature. This is what Einstein meant when he famously said he wanted to understand what kind of choices God had --using his metaphor-- how free his choices were in creating the universe, which is just asking how many freely adjustable parameters there are. Physicists tend to prefer theories that reduce that number

You have others saying that time is just an illusion, that there isn't really a direction of time, and so forth. I myself think that all of the reasons that lead people to say things like that have very little merit, and that people have just been misled, largely by mistaking the mathematics they use to describe reality for reality itself. If you think that mathematical objects are not in time, and mathematical objects don't change -- which is perfectly true -- and then you're always using mathematical objects to describe the world, you could easily fall into the idea that the world itself doesn't change, because your representations of it don't.

physicists for almost a hundred years have been dissuaded from trying to think about fundamental questions. I think most physicists would quite rightly say "I don't have the tools to answer a question like 'what is time?' - I have the tools to solve a differential equation." The asking of fundamental physical questions is just not part of the training of a physicist anymore.

The question remains as to how often, after life evolves, you'll have intelligent life capable of making technology. What people haven't seemed to notice is that on earth, of all the billions of species that have evolved, only one has developed intelligence to the level of producing technology. Which means that kind of intelligence is really not very useful. It's not actually, in the general case, of much evolutionary value. We tend to think, because we love to think of ourselves, human beings, as the top of the evolutionary ladder, that the intelligence we have, that makes us human beings, is the thing that all of evolution is striving toward. But what we know is that that's not true. Obviously it doesn't matter that much if you're a beetle, that you be really smart. If it were, evolution would have produced much more intelligent beetles. We have no empirical data to suggest that there's a high probability that evolution on another planet would lead to technological intelligence.

If replication is what separates the rigor of science from the squishiness of pseudoscience, where do we put all these rigorously validated findings that can no longer be proved? Which results should we believe?

Schooler demonstrated that subjects shown a face and asked to describe it were much less likely to recognize the face when shown it later than those who had simply looked at it. Schooler called the phenomenon “verbal overshadowing.”

The most likely explanation for the decline is an obvious one: regression to the mean. As the experiment is repeated, that is, an early statistical fluke gets cancelled out. The extrasensory powers of Schooler’s subjects didn’t decline—they were simply an illusion that vanished over time.

yet Schooler has noticed that many of the data sets that end up declining seem statistically solid—that is, they contain enough data that any regression to the mean shouldn’t be dramatic. “These are the results that pass all the tests,” he says. “The odds of them being random are typically quite remote, like one in a million. This means that the decline effect should almost never happen. But it happens all the time!

this is why Schooler believes that the decline effect deserves more attention: its ubiquity seems to violate the laws of statistics

In 2001, Michael Jennions, a biologist at the Australian National University, set out to analyze “temporal trends” across a wide range of subjects in ecology and evolutionary biology. He looked at hundreds of papers and forty-four meta-analyses (that is, statistical syntheses of related studies), and discovered a consistent decline effect over time, as many of the theories seemed to fade into irrelevance.

Jennions admits that his findings are troubling, but expresses a reluctance to talk about them

publicly. “This is a very sensitive issue for scientists,” he says. “You know, we’re supposed to be dealing with hard facts, the stuff that’s supposed to stand the test of time. But when you see these trends you become a little more skeptical of things.”

While publication bias almost certainly plays a role in the decline effect, it remains an incomplete explanation. For one thing, it fails to account for the initial prevalence of positive results among studies that never even get submitted to journals. It also fails to explain the experience of people like Schooler, who have been unable to replicate their initial data despite their best efforts.

Jennions, similarly, argues that the decline effect is largely a product of publication bias, or the tendency of scientists and scientific journals to prefer positive data over null results, which is what happens when no effect is found. The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for

Sterling saw that if ninety-seven per cent of psychology studies were proving their hypotheses, either psychologists were extraordinarily lucky or they published only the outcomes of successful experiments.

One of his most cited papers has a deliberately provocative title: “Why Most Published Research Findings Are False.”

suspects that an equally significant issue is the selective reporting of results—the data that scientists choose to document in the first place. Palmer’s most convincing evidence relies on a statistical tool known as a funnel graph. When a large number of studies have been done on a single subject, the data should follow a pattern: studies with a large sample size should all cluster around a common value—the true result—whereas those with a smaller sample size should exhibit a random scattering, since they’re subject to greater sampling error. This pattern gives the graph its name, since the distribution resembles a funnel.

after Palmer plotted every study of fluctuating asymmetry, he noticed that the distribution of results with smaller sample sizes wasn’t random at all but instead skewed heavily toward positive results. Palmer has since documented a similar problem in several other contested subject areas. “Once I realized that selective reporting is everywhere in science, I got quite depressed,” Palmer told me. “As a researcher, you’re always aware that there might be some nonrandom patterns, but I had no idea how widespread it is.”

Palmer summarized the impact of selective reporting on his field: “We cannot escape the troubling conclusion that some—perhaps many—cherished generalities are at best exaggerated in their biological significance and at worst a collective illusion nurtured by strong a-priori beliefs often repeated.”

Palmer emphasizes that selective reporting is not the same as scientific fraud. Rather, the problem seems to be one of subtle omissions and unconscious misperceptions, as researchers struggle to make sense of their results. Stephen Jay Gould referred to this as the “sho

horning” process.

“A lot of scientific measurement is really hard,” Simmons told me. “If you’re talking about fluctuating asymmetry, then it’s a matter of minuscule differences between the right and left sides of an animal. It’s millimetres of a tail feather. And so maybe a researcher knows that he’s measuring a good male”—an animal that has successfully mated—“and he knows that it’s supposed to be symmetrical. Well, that act of measurement is going to be vulnerable to all sorts of perception biases. That’s not a cynical statement. That’s just the way human beings work.”

For Simmons, the steep rise and slow fall of fluctuating asymmetry is a clear example of a scientific paradigm, one of those intellectual fads that both guide and constrain research: after a new paradigm is proposed, the peer-review process is tilted toward positive results. But then, after a few years, the academic incentives shift—the paradigm has become entrenched—so that the most notable results are now those that disprove the theory.

John Ioannidis, an epidemiologist at Stanford University, argues that such distortions are a serious issue in biomedical research. “These exaggerations are why the decline has become so common,” he says. “It’d be really great if the initial studies gave us an accurate summary of things. But they don’t. And so what happens is we waste a lot of money treating millions of patients and doing lots of follow-up studies on other themes based on results that are misleading.”

In 2005, Ioannidis published an article in the Journal of the American Medical Association that looked at the forty-nine most cited clinical-research studies in three major medical journals.

the data Ioannidis found were disturbing: of the thirty-four claims that had been subject to replication, forty-one per cent had either been directly contradicted or had their effect sizes significantly downgraded.

the most troubling fact emerged when he looked at the test of replication: out of four hundred and thirty-two claims, only a single one was consistently replicable. “This doesn’t mean that none of these claims will turn out to be true,” he says. “But, given that most of them were done badly, I wouldn’t hold my breath.”

According to Ioannidis, the main problem is that too many researchers engage in what he calls “significance chasing,” or finding ways to interpret the data so that it passes the statistical test of significance—the ninety-five-per-cent boundary invented by Ronald Fisher.

One of the classic examples of selective reporting concerns the testing of acupuncture in different countries. While acupuncture is widely accepted as a medical treatment in various Asian countries, its use is much more contested in the West. These cultural differences have profoundly influenced the results of clinical trials.

The problem of selective reporting is rooted in a fundamental cognitive flaw, which is that we like proving ourselves right and hate being wrong.

“It feels good to validate a hypothesis,” Ioannidis said. “It feels even better when you’ve got a financial interest in the idea or your career depends upon it. And that’s why, even after a claim has been systematically disproven”—he cites, for instance, the early work on hormone replacement therapy, or claims involving various vitamins—“you still see some stubborn researchers citing the first few studies

That’s why Schooler argues that scientists need to become more rigorous about data collection before they publish. “We’re wasting too much time chasing after bad studies and underpowered experiments,”

The current “obsession” with replicability distracts from the real problem, which is faulty design.

“Every researcher should have to spell out, in advance, how many subjects they’re going to use, and what exactly they’re testing, and what constitutes a sufficient level of proof. We have the tools to be much more transparent about our experiments.”

Schooler recommends the establishment of an open-source database, in which researchers are required to outline their planned investigations and document all their results. “I think this would provide a huge increase in access to scientific work and give us a much better way to judge the quality of an experiment,”

scientific research will always be shadowed by a force that can’t be curbed, only contained: sheer randomness. Although little research has been done on the experimental dangers of chance and happenstance, the research that exists isn’t encouraging.

The disturbing implication of the Crabbe study is that a lot of extraordinary scientific data are nothing but noise. The hyperactivity of those coked-up Edmonton mice wasn’t an interesting new fact—it was a meaningless outlier, a by-product of invisible variables we don’t understand.

The problem, of course, is that such dramatic findings are also the most likely to get published in prestigious journals, since the data are both statistically significant and entirely unexpected

This suggests that the decline effect is actually a decline of illusion. While Karl Popper imagined falsification occurring with a single, definitive experiment—Galileo refuted Aristotelian mechanics in an afternoon—the process turns out to be much messier than that.

Many scientific theories continue to be considered true even after failing numerous experimental tests.

Even the law of gravity hasn’t always been perfect at predicting real-world phenomena. (In one test, physicists measuring gravity by means of deep boreholes in the Nevada desert found a two-and-a-half-per-cent discrepancy between the theoretical predictions and the actual data.)

Such anomalies demonstrate the slipperiness of empiricism. Although many scientific ideas generate conflicting results and suffer from falling effect sizes, they continue to get cited in the textbooks and drive standard medical practice. Why? Because these ideas seem true. Because they make sense. Because we can’t bear to let them go. And this is why the decline effect is so troubling. Not because it reveals the human fallibility of science, in which data are tweaked and beliefs shape perceptions. (Such shortcomings aren’t surprising, at least for scientists.) And not because it reveals that many of our most exciting theories are fleeting fads and will soon be rejected. (That idea has been around since Thomas Kuhn.)

The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that’s often not the case. Just because an idea is true doesn’t mean it can be proved. And just because an idea can be proved doesn’t mean it’s true. When the experiments are done, we still have to choose what to believe. ♦

If you are like most of our experimental participants, you will not give the same answer to the second question that you give to the first. Our participants said the “average” number was about four hours and the “normal” number was about three hours.

Again and again, our participants did not take the normal to be the same as the average. Instead, what people picked out as the “normal thing to do” or a “normal such-and-such” tended to be intermediate between what they thought was typical and what they thought was ideal.

These results point to something surprising about the way people’s minds work. You might imagine that people have two completely distinct modes of reasoning: On one hand, we can think about how things typically are; on the other, we can think about how things ought to be.

But our results suggest that people’s minds cannot be divided up so neatly in this way.

Likewise, people’s attitudes toward atypical behavior are frequently colored by this blended conception of normality.

However deeply ingrained this cognitive tendency may be, people are not condemned to think this way.

But this type of thinking, which takes some discipline, is no doubt more the exception than the rule. Most often, we do not stop to distinguish the typical from the acceptable, the infrequent from the deviant.

Starting in early adulthood, our number of friends starts to decrease steadily.

we lose an average of two friends when we gain a romantic partner.

We are constantly shedding our friends,”

“We grow in one direction, our friends grow in another, and there isn’t much in common anymore.”

But it gets harder to make friends as we get older. We have less time to pursue friendships. It is tougher to find people with similar interests and emotional styles when you no longer have a ready-made pool of classmates to choose from. School also provides a steady routine for people to develop intimacy slowly and naturally.

We also become more inhibited

If you want new friends, you need to look with intention. And, just as you would when looking for a mate, you need to look for someone who has something in common with you, and who is emotionally available.

the rest comes from his multiple real world examples illustrating exactly why even the most reluctant mathophobe is well advised to achieve a personal understanding of the statistical underpinnings of life, whether that individual is watching football on the couch, picking a school for the children or jiggling anxiously in a hospital admitting office.

And while we’re talking about bias, let’s not forget publication bias: studies that show a drug works get published, but those showing a drug does nothing tend to disappear.

The same trade-off applies to the interpretation of medical tests. Unproven disease screens are likely to do little but feed lots of costly, anxiety-producing garbage into your medical record.

The only people who still think we need the old-fashioned sort of “baseload power” that coal provides – power that is always running regardless of whether you need it – are those in the coal industry.

In the short term, that can be gas. But, in the longer term, to stop runaway climate change, that service will need to be supplied by renewable sources such as battery storage, hydro, solar thermal with storage or geothermal.

“As the world’s largest coal exporter, we have a vested interest in showing that we can provide both lower emissions and reliable baseload power with state-of-the-art, clean, coal-fired technology.”

materialism is not the greedy desire for material goods, but rather the belief that the fundamental reality of the world is material;

idealism is not the aspiration toward lofty and laudable goals, but rather the belief that the fundamental reality of the world is mental or idea-like. English-speaking philosophers today tend to speak of “physicalism” or “naturalism” rather than materialism (perhaps to avoid confusion with the Wall Street sense of the term). At the same time, Anglo-American historians of philosophy continue to find the distinction between materialism and idealism a useful one in our attempts at categorizing past schools of thought. Democritus and La Mettrie were materialists; Hobbes was pretty close. Berkeley and Kant were idealists; Leibniz may have been.

And it was these paradoxes that led the Irish philosopher to conclude that talk of matter was but a case of multiplying entities beyond necessity. For Berkeley, all we can know are ideas, and for this reason it made sense to suppose that the world itself consists in ideas.

Central to this performance was the concept of  “materialism.” The entire history of philosophy, in fact, was portrayed in Soviet historiography as a series of matches between the materialist home-team and its “idealist” opponents, beginning roughly with Democritus (good) and Plato (bad), and culminating in the opposition between official party philosophy and logical positivism, the latter of which was portrayed as a shrouded variety of idealism. Thus from the “Short Philosophical Dictionary,” published in Moscow in 1951, we learn that the school of logical empiricism represented by Rudolf Carnap, Otto Neurath and others, “is a form of subjective idealism, characteristic of degenerating bourgeois philosophy in the epoch of the decline of capitalism.”Now the Soviet usage of this pair of terms appears to fly in the face of our ordinary, non-philosophical understanding of them (that, for example,  Wall Street values are “materialist,” while the Occupy movement is “idealist”). One might have thought that the communists should be flinging the “materialist” label at their capitalist enemies, rather than claiming it for themselves. One might also have thought that the Bolshevik Revolution and the subsequent failed project of building a workers’ utopia was nothing if not idealistic.

one great problem with the concept of materialism is that it says very little in itself. What is required in addition is an elaboration of what a given thinker takes matter, or ideas, to be. It may not be just the Marxist aftertaste, but also the fact that the old common-sense idea about matter as brute, given stuff has turned out to have so little to do with the way the physical world actually is, that has led Anglo-American philosophers to prefer to associate themselves with the “physical” or the “natural” rather than with the material.  Reality, they want to say, is just what is natural, while everything else is in turn “supernatural” (this distinction has its clarity going for it, but it also seems uncomfortably close to tautology). Not every philosopher has a solid grasp of subatomic physics, but most know enough to grasp that, even if reality is eventually exhaustively accounted for through an enumeration of the kinds of particles and a few basic forces, this reality will still look nothing like what your average person-in-the-street takes reality to be.

The 18th-century idealist philosopher George Berkeley strongly believed that matter was only a fiction contrived by philosophers in the first place, for which the real people had no need. For Berkeley, there was never anything common-sensical about matter. We did not need to arrive at the era of atom-splitting and wave-particle duality, then, in order for the paradoxes inherent in matter to make themselves known (is it infinitely divisible or isn’t it?

Soviet and Western Marxists alike, by stark contrast, and before them the French “vulgar” (i.e., non-dialectical) materialists of the 18th century, saw and see the material world as the base and cause of all mental activity, as both bringing ideas into existence, and also determining the form and character of a society’s ideas in accordance with the state of its technology, its methods of resource extraction and its organization of labor. So here to focus on the material is not to become distracted from the true source of being, but rather to zero right in on it.

Consider money. Though it might sometimes be represented by bank notes or coins, money is an immaterial thing par excellence, and to seek to acquire it is to move on the plane of ideas. Of course, money can also be converted into material things, yet it seems simplistic to suppose that we want money only in order to convert it into the material things we really want, since even these material things aren’t just material either: they are symbolically dense artifacts, and they convey to others certain ideas about their owners. This, principally, is why their owners want them, which is to say that materialists (in the everyday sense) are trading in ideas just as much as anyone else.

In the end no one really cares about stuff itself. Material acquisitions — even, or perhaps especially, material acquisitions of things like Rolls Royces and Rolexes — are maneuvers within a universe of materially instantiated ideas. This is human reality, and it is within this reality that mystics, scientists, and philosophers alike are constrained to pursue their various ends, no matter what they might take the ultimate nature of the external world to be.

Reddit was about to become the preeminent place for "real 'expert'" AMAs that were extremely useful and enlightening.

AMAs among common folk focus on dishing on what sex, disease, or jobs are really like. The celebrity versions borrow the same idea, but they serve up inside information on celebrity itself (generally speaking) or politics itself. 

The AMA is supposed to expose the mechanism. The AMA is about exposing the "inside conversations." The AMA is like the crowdsourced version of those moments when Kevin Spacey turns to the camera in House of Cards and breaks things down. 

The more you see the world this way—full of malice and planning instead of circumstance and coincidence—the more likely you are to accept conspiracy theories of all kinds. Once you buy into the first theory, with its premises of coordination, efficacy, and secrecy, the next seems that much more plausible.

The common thread between distrust and cynicism, as defined in these experiments, is a perception of bad character. More broadly, it’s a tendency to focus on intention and agency, rather than randomness or causal complexity. In extreme form, it can become paranoia

In mild form, it’s a common weakness known as the fundamental attribution error—ascribing others’ behavior to personality traits and objectives, forgetting the importance of situational factors and chance

Clearly, susceptibility to conspiracy theories isn’t a matter of objectively evaluating evidence. It’s more about alienation. People who fall for such theories don’t trust the government or the media. They aim their scrutiny at the official narrative, not at the alternative explanations

Conspiracy believers are the ultimate motivated skeptics. Their curse is that they apply this selective scrutiny not to the left or right, but to the mainstream. They tell themselves that they’re the ones who see the lies, and the rest of us are sheep. But believing that everybody’s lying is just another kind of gullibility.

This is as good as it gets. There is “no evolution in our capacity for language.”

The answer given in the first lecture — “What is Language?” — is that we are creatures with language, and that language as a uniquely human biological capacity appeared suddenly and quite late in the evolutionary story, perhaps 75,000 years ago.

Chomsky gave three lectures under the general title “What Kind of Creatures are We?”

Language, then, does not arise from the social/cultural environment, although the environment provides the stuff or input it works on. That input is “impoverished”; it can’t account for the creativity of language performance, which has its source not in the empirical world, but in an innate ability that is more powerful than the stimuli it utilizes and plays with. It follows that if you want to understand language, you shouldn’t look to linguistic behavior but to the internal mechanism — the Universal Grammar — of which particular linguistic behaviors are a non-exhaustive expression. (The capacity exceeds the empirical resources it might deploy.)

In his second lecture (“What Can We Understand?”), Chomsky took up the question of what humans are capable of understanding and his answer, generally, was that we can understand what we can understand, and that means that we can’t understand what is beyond our innate mental capacities

This does not mean, he said, that what we can’t understand is not real: “What is mysterious to me is not an argument that it does not exist.” It’s just that while language is powerful and creative, its power and creativity have limits; and since language is thought rather than an addition to or clothing of thought, the limits of language are the limits of what we can fruitfully think about

(4) The academic views of a professor are independent of his or her real-world political views; academic disputes don’t track partisan disputes or vice versa; you can’t reason from an academic’s disciplinary views to the positions he or she would take in the public sphere; they are independent variables.

These assertions are offered as a counter to what Chomsky sees as the over-optimistic Enlightenment belief — common to many empiricist philosophies — that ours is a “limitless explanatory power” and that “we can do anything.”

In the third lecture (“What is the Common Good?”) Chomsky turned from the philosophy of mind and language to political philosophy and the question of what constitutes a truly democratic society

He likened dogmatic intellectual structures that interfere with free inquiry to coercive political structures that stifle the individual’s creative independence and fail to encourage humanity’s “richest diversity

He asserted that any institution marked by domination and hierarchy must rise to the challenge of justifying itself, and if it cannot meet the challenge, it should be dismantled.

He contrasted two accounts of democracy: one — associated by him with James Madison — distrusts the “unwashed” populace and puts its faith in representative government where those doing the representing (and the voting and the distributing of goods) constitute a moneyed and propertied elite

the other — associated by him with Adam Smith (in one of his moods), J. S. Mill, the 1960s and a tradition of anarchist writing — seeks to expand the franchise and multiply choices in the realms of thought, politics and economics. The impulse of this second, libertarian, strain of democracy, is “to free society from economic or theological guardianship,” and by “theological” Chomsky meant not formal religion as such but any assumed and frozen ideology that blocked inquiry and limited participation. There can’t, in short, be “too much democracy.”

It was thought of the highest order performed by a thinker, now 85 years old, who by and large eschewed rhetorical flourishes (he has called his own speaking style “boring” and says he likes it that way) and just did it, where ‘it” was the patient exploration of deep issues that had been explored before him by a succession of predecessors, fully acknowledged, in a conversation that is forever being continued and forever being replenished.

Yes, I said to myself, this is what we — those of us who bought a ticket on this particular train — do; we think about problems and puzzles and try to advance the understanding of them; and we do that kind of thinking because its pleasures are, in a strong sense, athletic and provide for us, at least on occasion, the experience of fully realizing whatever capabilities we might have. And we do it in order to have that experience, and to share it with colleagues and students of like mind, and not to make a moral or political point.

The term “master class” is a bit overused, but I feel no hesitation in using it here. It was a master class taught by a master, and if someone were to ask me what exactly is it that academics do, I would point to these lectures and say, simply, here it is, the thing itself.

The National Research Council framework for K-12 science education recommends that by the end of Grade 5, students should appreciate that rising average global temperatures will affect the lives of all humans and other organisms on the planet. By Grade 8, students should understand that the release of greenhouse gases from burning fossil fuels is a major factor in global warming. And by Grade 12, students should know that global climate models are very effective in modeling, predicting and managing the current and future impact of climate change.

Relying on a climate-change curriculum and teaching materials largely sourced from federal agencies—particularly those of the current ideologically driven administration—raises a number of issues. Along with the undue authoritative weight that such government-produced documents carry in the classroom, most of the work is one-sided and presented in categorical terms, leaving no room for a balanced discussion. Moreover, too much blind trust is placed in the predictive power of long-range computer simulations, despite the weak forecasting track record of most climate models to date.

Employing such a Socratic approach to teaching climate change would likely lead to a rational and thought-provoking classroom debate on the merits of the case. However, that is not the point of this academic exercise—which seems to be to indoctrinate young people by using K-12 educators to establish the same positive political feedback loop around global warming that has existed between the federal government and the nation’s colleges and universities for the past two decades.

The statin trials, which involved tens of thousands of people, found no more muscle aches, the most common complaint, in patients who took statins than in those who took placebos.

The widely held belief that statins affect memory also has not been borne out in clinical trials, said Dr. Jane Armitage of the University of Oxford. She and her colleagues studied memory problems in 20,000 patients randomly assigned to take a statin or a placebo. “There was absolutely no difference,” she said.

In a separate study, they looked at mood and sleep patterns and again found statins had no effect. Another study, in Scotland, detailed cognitive testing of older people taking statins or a placebo, and also found no effect.

Medieval science was guided by "logical consistency."

The logical empiricist's conception of scientific progress was thus a continuous one; more comprehensive theory replaced compatible, older theory

Hempel also believed that science evolved in a continuous manner. New theory did not contradict past theory: "theory does not simply refute the earlier empirical generalizations in its field; rather, it shows that within a certain limited range defined by qualifying conditions, the generalizations hold true in fairly close approximation." [21]

movement combined induction, based on empiricism, and deduction in the form of logic

e notion of scientific realism held by Newton led to the evolutionary view of the progress of science

he entities and processes of theory were believed to exist in nature, and science should discover those entities and processes

Particularly disturbing discoveries were made in the area of atomic physics. For instance, Heisenberg's indeterminacy (25)principle, according to historian of science Cecil Schneer, yielded the conclusion that "the world of nature is indeterminate.

"even the fundamental principle of causality fail[ed] ."

was not until the second half of the twentieth century that the preservers of the evolutionary idea of scientific progress, the logical empiricists, were seriously challenged

revolutionary model of scientific change and examined the role of the scientific community in preventing and then accepting change. Kuhn's conception of scientific change occurring through revolutions undermined the traditional scientific goal, finding "truth" in nature

Textbooks inform scientists-to-be about this common body of knowledge and understanding.

for the world is too huge and complex to be explored randomly.

a scientist knows what facts are relevant and can build on past research

Normal science, as defined by Kuhn, is cumulative. New knowledge fills a gap of ignorance

ne standard product of the scientific enterprise is missing. Normal science does not aim at novelties of fact or theory and, when successful, finds none."

ntain a mechanism that uncovers anomaly, inconsistencies within the paradigm.

eventually, details arise that are inconsistent with the current paradigm

hese inconsistencies are eventually resolved or are ignored.

y concern a topic of central importance, a crisis occurs and normal science comes to a hal

that the scientists re-examine the foundations of their science that they had been taking for granted

it resolves the crisis better than the others, it offers promise for future research, and it is more aesthetic than its competitors. The reasons for converting to a new paradigm are never completely rational.

Unlike evolutionary science, in which new knowledge fills a gap of ignorance, in Kuhn's model new knowledge replaces incompatible knowledge.

In a sense, we have circled back to the ancient and medieval practice of separating scientific theory from physical reality; both medieval scientists and Kuhn would agree that no theory corresponds to reality and therefore any number of theories might equally well explain a natural phenomenon. [36] Neither twentieth-century atomic theorists nor medieval astronomers are able to claim that their theories accurately describe physical phenomena. The inability to return to scientific realism suggests a tripartite division of the history of science, with a period of scientific realism fitting between two periods in which there is no insistence that theory correspond to reality. Although both scientific realism and the evolutionary idea of scientific progress appeal to common sense, both existed for only a few hundred years.

Most people successfully avoided reading until about 300 years ago. It was about then that Western European priests and princes decided that everyone should be taught to read. These literacy-loving types tried various schemes to make common folks literate; the most effective of these, however, was naked coercion. By the nineteenth century, churches and states all over Europe and North America were forcing parents to send their kids to school to learn to read

So it happened that by the early twentieth century most people in Western Europe and North America could read. They had no choice in the matter. They still don’t.

Why don’t most people like to read? The answer is surprisingly simple: humans weren’t evolved to read. Note that we have no reading organs: our eyes and brains were made for watching, not for decoding tiny symbols on mulch sheets. To prepare our eyes and brains for reading, we must rewire them. This process takes years of hard work to accomplish, and some people never accomplish it all. Moreover, even after you’ve learned to read, you probably won’t find reading to be very much fun. It consumes all of your attention, requires active thought, and makes your eyes hurt. For most people, then, reading is naturally hard and, therefore, something to be avoided if at all possible.

we have misidentified the “problem” facing us: it is not the much-bemoaned reading gap, but rather a seldom-mentioned knowledge gap. Though it is immodest to say, we readers genuinely know more than those who do not read. Thus we are usually able to make better-informed decisions than non-readers can.

Today any lecturer can produce and distribute high quality audio and video programs. Most scholars have the equipment on their desks (that is, a PC). The software is dead simple and inexpensive. And the shows themselves can be distributed the world over on the Internet for almost nothing.

If we in the Reading Class want to teach the the reading-averse public more effectively than we have in the past, we must rid ourselves of our reading fetish and admit that we’ve been falling down on the job. Once we take this painful step, then a number of interesting options for closing the knowledge gap become available. The most promising of these options is using audio and video to share what we know with the public at large.

We have to laboriously learn to read, but we are born with the ability to watch and listen. We don’t find reading terribly pleasant, but we do find watching and listening generally enjoyable.

The results of this “natural experiment” are in: people would much rather watch/listen than read. This is why Americans sit in front of the television for three hours a day, while they read for only a tiny fraction of that time.

Our task, then, is to give them something serious to watch and listen to, something that conveys the richness and complexity of our written work in pictures and sounds. The good news is that we can easily do this.

If we lived in an aristocracy of readers, this maldistribution of knowledge might be acceptable. But we don’t; rather, we live in a democracy (if we are lucky). In a democracy, the people – readers and non-readers alike – decide. Thus we would like all citizens to be knowledgeable so that they can make well-informed decisions about our common affairs. This has been a central goal of the Reading Class since the literacy-loving Enlightenment.

I’ve done it. Here are two examples. The first is New Books in History, an author-interview podcast featuring historians with new books. Aside from the computer, the total hardware and software start-up costs were roughly $300. It took me no time to learn the software thanks to some handy on-line tutorials available on Lynda.com. Today New Books in History has a large international audience.

The “new books” podcasts are not about serious books; they are about the ideas trapped in those serious, and seriously un-read, books. Books imprison ideas; the “new books” podcasts set them free.)

“Your results are not the least bit surprising,” he told me. “Anything short of sequencing is going to be short on accuracy — and even then, there’s almost no comprehensive data sets to compare to.”

“Even if they are accurately looking at 5 percent of the attributable risk, they’ve ignored the vast majority of the other risk factors — the dark matter for genetics — because we as a scientific community haven’t yet identified those risk factors,”

There are only 23 diseases that start in adulthood, can be treated, and for which highly predictive tests exist. All are rare, with hereditary breast cancer the most common. “A small percentage of people who get tested will get useful information,” Dr. Klitzman said. “But for most people, the results are not clinically useful, and they may be misleading or confusing.”

To be sure, my tests did provide some beneficial information. They all agreed that I lack markers associated with an increased risk of breast cancer and Alzheimer’s. That said, they were testing for only a small fraction of the genetic risks for these diseases, not for rare genetic variants that confer much of the risk. I could still develop those diseases, of course, but I don’t have reason to pursue aggressive screenings as I age.

He added: “If you want to spend money wisely to protect your health and you have a few hundred dollars, buy a scale, stand on it, and act accordingly.”