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the emergence of the blogosphere requires significantly more openness from scientists. However, providing the details necessary to validate large datasets can be difficult and time-consuming, and how FoI laws apply to research is still an evolving area. Meanwhile, the public needs to understand that science cannot and does not produce absolutely precise answers. Though the uncertainties may become smaller and better constrained over time, uncertainty in science is a fact of life which policymakers have to deal with. The chapter concludes: “the Review would urge all scientists to learn to communicate their work in ways that the public can access and understand”.

email is less formal than other forms of communication: “Extreme forms of language are frequently applied to quite normal situations by people who would never use it in other communication channels.” The CRU scientists assumed their emails to be private, so they used “slang, jargon and acronyms” which would have been more fully explained had they been talking to the public. And although some emails suggest CRU went out of their way to make life difficult for their critics, there are others which suggest they were bending over backwards to be honest. Therefore the Review found “the e-mails cannot always be relied upon as evidence of what actually occurred, nor indicative of actual behaviour that is extreme, exceptional or unprofessional.” [section 4.3]

when put into the proper context, what do these emails actually reveal about the behaviour of the CRU scientists? The report concluded (its emphasis):

we find that their rigour and honesty as scientists are not in doubt.

we did not find any evidence of behaviour that might undermine the conclusions of the IPCC assessments.

The argument that Climategate reveals an international climate science conspiracy is not really a very skeptical one. Sure, it is skeptical in the weak sense of questioning authority, but it stops there. Unlike true skepticism, it doesn’t go on to objectively examine all the evidence and draw a conclusion based on that evidence. Instead, it cherry-picks suggestive emails, seeing everything as incontrovertible evidence of a conspiracy, and concludes all of mainstream climate science is guilty by association. This is not skepticism; this is conspiracy theory.

The media dropped the ball There is a famous quotation attributed to Mark Twain: “A lie can travel halfway around the world while the truth is putting on its shoes.” This is more true in the internet age than it was when Mark Twain was alive. Unfortunately, it took months for the Climategate inquiries to put on their shoes, and by the time they reported, the damage had already been done. The media acted as an uncritical loudspeaker for the initial allegations, which will now continue to circulate around the world forever, then failed to give anywhere near the same amount of coverage to the inquiries clearing the scientists involved. For instance, Rupert Murdoch’s The Australian published no less than 85 stories about Climategate, but not one about the Muir Russell inquiry.

Even the Guardian, who have a relatively good track record on environmental reporting and were quick to criticize the worst excesses of climate conspiracy theorists, could not resist the lure of stolen emails. As George Monbiot writes, journalists see FoI requests and email hacking as a way of keeping people accountable, rather than the distraction from actual science which they are to scientists. In contrast, CRU director Phil Jones says: “I wish people would spend as much time reading my scientific papers as they do reading my e-mails.”

This is part of a broader problem with climate change reporting: the media holds scientists to far higher standards than it does contrarians. Climate scientists have to be right 100% of the time, but contrarians apparently can get away with being wrong nearly 100% of the time. The tiniest errors of climate scientists are nitpicked and blown out of all proportion, but contrarians get away with monstrous distortions and cherry-picking of evidence. Around the same time The Australian was bashing climate scientists, the same newspaper had no problem publishing Viscount Monckton’s blatant misrepresentations of IPCC projections (not to mention his demonstrably false conspiracy theory that the Copenhagen summit was a plot to establish a world government).

In the current model of environmental reporting, the contrarians do not lose anything by making baseless accusations. In fact, it is in their interests to throw as much mud at scientists as possible to increase the chance that some of it will stick in the public consciousness. But there is untold damage to the reputation of the scientists against whom the accusations are being made. We can only hope that in future the media will be less quick to jump to conclusions. If only editors and producers would stop and think for a moment about what they’re doing: they are playing with the future of the planet.

As a teacher at the City University of New York, I am constantly aware of the possibility that my students might cheat on their tests. I do take some elementary precautionary steps

Still, my job is not that of the policeman. My students are adults who theoretically are there to learn. If they don’t value that learning and prefer to pay someone else to fake it, so be it, ultimately it is they who lose in the most fundamental sense of the term. Just like drug addicts, to return to my earlier metaphor. And just as in that other case, it is enablers like Mr. Dante who simply can’t duck the moral blame.

n open letter to the president of SUNY-Albany, penned by molecular biologist Gregory Petsko. The SUNY-Albany president has recently announced the closing — for budgetary reasons — of the departments of French, Italian, Classics, Russian and Theater Arts at his university.

Petsko begins by taking on one of the alleged reasons why SUNY-Albany is slashing the humanities: low enrollment. He correctly points out that the problem can be solved overnight at the stroke of a pen: stop abdicating your responsibilities as educators and actually put constraints on what your students have to take in order to graduate. Make courses in English literature, foreign languages, philosophy and critical thinking, the arts and so on, mandatory or one of a small number of options that the students must consider in order to graduate.

But, you might say, that’s cheating the market! Students clearly don’t want to take those courses, and a business should cater to its customers. That type of reasoning is among the most pernicious and idiotic I’ve ever heard. Students are not clients (if anything, their parents, who usually pay the tuition, are), they are not shopping for a new bag or pair of shoes. They do not know what is best for them educationally, that’s why they go to college to begin with. If you are not convinced about how absurd the students-as-clients argument is, consider an analogy: does anyone with functioning brain cells argue that since patients in a hospital pay a bill, they should be dictating how the brain surgeon operates? I didn’t think so.

Petsko then tackles the second lame excuse given by the president of SUNY-Albany (and common among the upper administration of plenty of public universities): I can’t do otherwise because of the legislature’s draconian cuts. Except that university budgets are simply too complicated for there not to be any other option. I know this first hand, I’m on a special committee at my own college looking at how to creatively deal with budget cuts handed down to us from the very same (admittedly small minded and dysfunctional) New York state legislature that has prompted SUNY-Albany’s action. As Petsko points out, the president there didn’t even think of involving the faculty and staff in a broad discussion of how to deal with the crisis, he simply announced the cuts on a Friday afternoon and then ran for cover. An example of very poor leadership to say the least, and downright hypocrisy considering all the talk that the same administrator has been dishing out about the university “community.”

Finally, there is the argument that the humanities don’t pay for their own way, unlike (some of) the sciences (some of the time). That is indubitably true, but irrelevant. Universities are not businesses, they are places of higher learning. Yes, of course they need to deal with budgets, fund raising and all the rest. But the financial and administrative side has one goal and one goal only: to provide the best education to the students who attend that university.

That education simply must include the sciences, philosophy, literature, and the arts, as well as more technical or pragmatic offerings such as medicine, business and law. Why? Because that’s the kind of liberal education that makes for an informed and intelligent citizenry, without which our democracy is but empty talk, and our lives nothing but slavery to the marketplace.

Maybe this is not how education works in the US. I thought that general (or compulsory) education (ie. up to high school) is designed to make sure that citizens in a democratic country can perform their civil duties. A balanced and well-rounded education, which includes a healthy mixture of science and humanities, is indeed very important for this purpose. However, college-level education is for personal growth and therefore the person must have a large say about what kind of classes he or she chooses to take. I am disturbed by Massimo's hospital analogy. Students are not ill. They don't go to college to be cured, or to be good citizens. They go to college to learn things that *they* want to learn. Patients are passive. Students are not.I agree that students typically do not know what kind of education is good for them. But who does?

students do have a saying in their education. They pick their major, and there are electives. But I object to the idea that they can customize their major any way they want. That assumes they know what the best education for them is, they don't. That's the point of education.

The students are in your class to get a good grade, any learning that takes place is purely incidental. Those good grades will look good on their transcript and might convince a future employer that they are smart and thus are worth paying more.

Just how many of your students do you think will remember the extensive complex jargon of philosophy more than a couple of months after they leave your classroom?

and our lives nothing but slavery to the marketplace.We are there. Welcome. Where have you been all this time? In a capitalistic/plutocratic society money is power (and free speech too according to the supreme court). Money means a larger/better house/car/clothing/vacation than your neighbor and consequently better mating opportunities. You can mostly blame the women for that one I think just like the peacock's tail.

If a student of surgery fails to learn they might maim, kill or cripple someone. If an engineer of airplanes fails to learn they might design a faulty aircraft that fails and kills people. If a student of chemistry fails to learn they might design a faulty drug with unintended and unfortunate side effects, but what exactly would be the harm if a student of philosophy fails to learn Aristotle had to say about elements or Plato had to say about perfect forms? These things are so divorced from people's everyday activities as to be rendered all but meaningless.

human knowledge grows by leaps and bounds every day, but human brain capacity does not, so the portion of human knowledge you can personally hold gets smaller by the minute. Learn (and remember) as much as you can as fast as you can and you will still lose ground. You certainly have your work cut out for you emphasizing the importance of Thales in the Age of Twitter and whatever follows it next year.

He recently and rightly slated Ed Milliband, secretary of state for energy and climate change, for his ludicrous assertion that “opposition to wind farms should be as unacceptable as failing to wear a seatbelt,” describing this as political or environmental correctness veering towards fascism.

He has also retreated considerably from his extreme position of 2006, just as he earlier disassociated himself from some of the weirder extensions of the Gaia hypothesis, like the idea that the Earth as a whole is part of a universal consciousness.

Lovelock’s central point was that climate change models are not yet fit to make predictions even 40 years ahead. His position that continued release of carbon into the atmosphere constitutes a grave threat was unaltered, but he seemed to concede that the changes might not be as severe or rapid as he had earlier predicted.

It could be argued that Lovelock was over-hasty with his predictions of near extinction, but instead we should take heart that, almost half a century after developing his original hypothesis, he is still willing and capable of modifying his views on the basis of evidence. It is a good example not just for many younger scientists, but to everyone. On another level, it will perhaps raise hopes that some form of climate consensus can emerge out of the recent controversies. What we desperately need now is a more balanced and sustainable long-term energy strategy.

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)

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.”

A 2003 survey published in the journal Human Reproduction showed that few British adults would be concerned enough about their baby’s gender to use the technology, and most adults wanted the same number of sons as daughters

Bioethics specialist Edgar Dahl of the University of Geissen found that 68 per cent of Britons craved an equal number of boys and girls; 6 per cent wanted more boys; 4 per cent more girls; 3 per cent only boys; and 2 per cent only girls. Fascinatingly, even if a baby’s sex could be decided by simply taking a blue pill or a pink pill, 90 per cent of British respondents said they wouldn’t take it.

What about the danger of stigmatising the unwanted sex if gender selection was allowed? According to experts on so-called “gender disappointment,” the unwanted sex would actually be male.

I may think it is old-fashioned to want a son so that he can inherit the family business, or a daughter to have someone to go shopping with. But how different is that from the other preferences and expectations we have for our children, such as hoping they will be gifted at mathematics, music or sport? We all nurture secret expectations for our children: I hope that mine will be clever, beautiful, witty and wise. Perhaps it is not the end of the world if we allow some parents to add “female” or “male” to the list.

thanks to Wikileaks, the world has been enlightened to the fact that the Obama administration not only refused to prosecute these individuals itself, it also exerted pressure on the governments of Germany and Spain not to prosecute, or even indict, any of the torturers or war criminals from the Bush dictatorship.

we see many right-wing commentators demanding that Assange be hunted down, with some even calling for his murder, on the grounds that he may have endangered lives by releasing confidential government documents. Yet, for the right-wing, this apparently was not a concern when the late columnist Robert Novak "outed" CIA agent Valerie Plame after her husband Joseph Wilson authored an OP-ED piece in The New York Times criticizing the motivations for waging war against Iraq. Even though there was evidence of involvement within the highest echelons of the Bush dictatorship, only one person, Lewis "Scooter" Libby, was indicted and convicted of "outing" Plame to Novak. And, despite the fact that this "outing" potentially endangered the lives of Plame's overseas contacts, Bush commuted Libby's thirty-month prison sentence, calling it "excessive."

Why the disparity? The answer is simple: The Plame "outing" served the interests of the military-industrial complex and helped to conceal the Bush dictatorship's lies, tortures and war crimes, while Wikileaks not only exposed such evils, but also revealed how Obama's administration, and Obama himself, are little more than "snake oil" merchants pontificating about government accountability while undermining it at every turn.

When the United States Constitution was being created, a conflict emerged between delegates who wanted a strong federal government (the Federalists) and those who wanted a weak federal government (the anti-Federalists). Although the Federalists won the day, one of the most distinguished anti-Federalists, George Mason, refused to sign the new Constitution, sacrificing in the process, some historians say, a revered place amongst America's founding fathers. Two of Mason's concerns were that the Constitution did not contain a Bill of Rights, and that the presidential pardon powers would allow corrupt presidents to pardon people who had committed crimes on presidential orders.

Mason's concerns about the abuse of the pardon powers were eventually proven right when Gerald Ford pardoned Richard Nixon, when Ronald Reagan pardoned FBI agents convicted of authorizing illegal break-ins, and when George H.W. Bush pardoned six individuals involved in the Iran-Contra Affair.

Mason was also proven right after the Federalists realized that the States would not ratify the Constitution unless a Bill of Rights was added. But this was done begrudgingly, as demonstrated by America's second president, Federalist John Adams, who essentially destroyed the right to freedom of speech via the Alien and Sedition Acts, which made it a crime to say, write or publish anything critical of the United States government.

Most criminals break laws that others have created, and people who assist in exposing or apprehending them are usually lauded as heroes. But with the "espionage" acts, the criminals themselves have actually created laws to conceal their crimes, and exploit these laws to penalize people who expose them.

The problem with America's system of government is that it has become too easy, and too convenient, to simply stamp "classified" on documents that reveal acts of government corruption, cover-up, mendacity and malfeasance, or to withhold them "in the interest of national security." Given this web of secrecy, is it any wonder why so many Americans are still skeptical about the "official" versions of the John F. Kennedy or Martin Luther King Jr. assassinations, or the events surrounding the attacks of September 11, 2001?

I want to believe that the Wikileaks documents will change America for the better. But what undoubtedly will happen is a repetition of the past: those who expose government crimes and cover-ups will be prosecuted or branded as criminals; new laws will be passed to silence dissent; new Liebermans will arise to intimidate the corporate-controlled media; and new ways will be found to conceal the truth.

What Wikileaks has done is make people understand why so many Americans are politically apathetic and content to lose themselves in one or more of the addictions American culture offers, be it drugs, alcohol, the Internet, video games, celebrity gossip, text-messaging-in essence anything that serves to divert attention from the harshness of reality.

the evils committed by those in power can be suffocating, and the sense of powerlessness that erupts from being aware of these evils can be paralyzing, especially when accentuated by the knowledge that government evildoers almost always get away with their crimes

It’s true that the shooter in Arizona appears to have been mentally troubled. But that doesn’t mean that his act can or should be treated as an isolated event, having nothing to do with the national climate.

Last spring Politico.com reported on a surge in threats against members of Congress, which were already up by 300 percent. A number of the people making those threats had a history of mental illness — but something about the current state of America has been causing far more disturbed people than before to act out their illness by threatening, or actually engaging in, political violence.

As Clarence Dupnik, the sheriff responsible for dealing with the Arizona shootings, put it, it’s “the vitriolic rhetoric that we hear day in and day out from people in the radio business and some people in the TV business.” The vast majority of those who listen to that toxic rhetoric stop short of actual violence, but some, inevitably, cross that line.

It’s not a general lack of “civility,” the favorite term of pundits who want to wish away fundamental policy disagreements. Politeness may be a virtue, but there’s a big difference between bad manners and calls, explicit or implicit, for violence; insults aren’t the same as incitement.

there’s room in a democracy for people who ridicule and denounce those who disagree with them; there isn’t any place for eliminationist rhetoric, for suggestions that those on the other side of a debate must be removed from that debate by whatever means necessary.

And it’s the saturation of our political discourse — and especially our airwaves — with eliminationist rhetoric that lies behind the rising tide of violence.

Where’s that toxic rhetoric coming from? Let’s not make a false pretense of balance: it’s coming, overwhelmingly, from the right. It’s hard to imagine a Democratic member of Congress urging constituents to be “armed and dangerous” without being ostracized; but Representative Michele Bachmann, who did just that, is a rising star in the G.O.P.

And there’s a huge contrast in the media. Listen to Rachel Maddow or Keith Olbermann, and you’ll hear a lot of caustic remarks and mockery aimed at Republicans. But you won’t hear jokes about shooting government officials or beheading a journalist at The Washington Post. Listen to Glenn Beck or Bill O’Reilly, and you will.

Of course, the likes of Mr. Beck and Mr. O’Reilly are responding to popular demand.

But even if hate is what many want to hear, that doesn’t excuse those who pander to that desire. They should be shunned by all decent people.

Unfortunately, that hasn’t been happening: the purveyors of hate have been treated with respect, even deference, by the G.O.P. establishment. As David Frum, the former Bush speechwriter, has put it, “Republicans originally thought that Fox worked for us and now we’re discovering we work for Fox.”

You could argue that modern economics really began with David Hume’s Of the Balance of Trade, whose core is a gloriously clear thought experiment

More than 65% of the monsoon-influenced glaciers that we observed are retreating, but heavily debris-covered glaciers with stagnant low-gradient terminus regions typically have stable fronts. Debris-covered glaciers are common in the rugged central Himalaya, but they are almost absent in subdued landscapes on the Tibetan Plateau, where retreat rates are higher. In contrast, more than 50% of observed glaciers in the westerlies-influenced Karakoram region in the northwestern Himalaya are advancing or stable.

Our study shows that there is no uniform response of Himalayan glaciers to climate change and highlights the importance of debris cover for understanding glacier retreat, an effect that has so far been neglected in predictions of future water availability9, 10 or global sea level11.

Munich Re explains in the context of recent disasters (emphasis added): Overall, pressure on prices in most lines of business and regions is persisting. Munich Re therefore consistently withdrew from under-rated business. It nevertheless proved possible to expand accounts with individual major clients, so that the business volume grew slightly on balance, despite the difficult environment. Munich Re owes this profitable growth especially to its ability to swiftly offer complex, tailor-made reinsurance solutions to its clients. Besides this, the many large losses resulting from natural hazards and also from man-made events, had a stabilising influence on the lines of business and regions affected. Thus, prices increased markedly for natural catastrophe covers in Australia/New Zealand (Oceania) and in offshore energy business. There were no major changes in conditions in this renewal season. The overall outcome of the reinsurance treaty renewals at 1 January 2011 was again very satisfactory for Munich Re.

There is downward pressure on prices in the reinsurance industry because there have not been enough disasters to keep up demand and thus premium prices. The following observation was made just three months ago: Insurance and reinsurance prices have been falling across most business lines for two years, reflecting intense competition between well-capitalised insurers and a comparative dearth of major catastrophe-induced losses.

as Munch Re explains, they have been able to overcome the dearth of disasters because recent extreme events have allowed them to increase prices on coverage in a manner that not only counteracts recent losses to some degree, but even allows for "profitable growth."  As with most tall tales, the one about the financial plight of reinsurers dealing with a changed climate isn't going away any time soon. It is just another bit of  popular unreality that effective decision making will have to overcome.

Value-free science? Many scientists think that science is about objectivity and “just the facts, ma’am.” Not so fast, philosophers, historians and sociologists of science have argued now for a number of decades. While I certainly have no sympathy for the extreme postmodernist position exemplified by the so-called “strong programme” in sociology of science — that science is entirely the result of social construction — there are several interesting and delicate facets of the problem to explore.

there are values embedded in the practice of science itself: testability, accuracy, generality, simplicity, and the like. Needless to say, few if any of these can be justified within science itself — there is no experiment confirming Occam’s razor, for instance.

Then there are the many moral dimensions of science practice, both in terms of ethical issues internal to science (fraud) and of the much broader ones affecting society at large (societal consequences of research and technological advances).

There is also the issue of diversity in science. Until very recently, and in many fields still today, science has largely been an affair conducted by white males. And this has historically resulted in a large amount of nonsense — say about gender differences, or ethnic differences — put forth as objective knowledge and accepted by the public because it has the imprimatur of science. But, you might say, that was the past, now we have corrected the errors and moved on. Except that such an argument ignores the fact that there is little reason to think that only we have gotten it just right, that the current generation is somehow immune from an otherwise uninterrupted history of science-based blunders.

Regarding Occam's Razor, there is a justification for it based on probability theory, see:http://www.johndcook.com/blog/2011/01/12/occams-razor-bayes-theorem/http://telescoper.wordpress.com/2011/02/19/bayes-razor/http://www.stat.duke.edu/~berger/papers/ockham.html

another interesting dimension of the relationship between values and science concerns which scientific questions we should pursue (and, often, fund with public money). Scientists often act as they ought to be the only arbiters here, and talk as if some questions were “obviously” intrinsically important. But when your research is costly and paid for by the public, perhaps society deserves a bit more of an explanation concerning why millions of dollars ought to be spent on obscure problems that apparently interest only a handful of university professors concentrated in one or a few countries.

The missing ingredients are software packages, which are available at no cost but have to be made easy to use. “You would have a whole system with privacy and security built in for the civil world we are living in,” he said. “It stores everything you care about.” Put free software into the little plug server in the wall, and you would have a Freedom Box that would decentralize information and power, Mr. Moglen said. This month, he created the Freedom Box Foundation to organize the software.

In the first days of the personal computer era, many scoffed at the idea that free software could have an important place in the modern world. Today, it is the digital genome for millions of phones, printers, cameras, MP3 players, televisions, the Pentagon, the New York Stock Exchange and the computers that underpin Google’s empire.

Social networking has changed the balance of political power, he said, “but everything we know about technology tells us that the current forms of social network communication, despite their enormous current value for politics, are also intensely dangerous to use. They are too centralized; they are too vulnerable to state retaliation and control.”

investors were said to have put a value of about $50 billion on Facebook, the social network founded by Mark Zuckerberg. If revolutions for freedom rest on the shoulders of Facebook, Mr. Moglen said, the revolutionaries will have to count on individuals who have huge stakes in keeping the powerful happy.

“It is not hard, when everybody is just in one big database controlled by Mr. Zuckerberg, to decapitate a revolution by sending an order to Mr. Zuckerberg that he cannot afford to refuse,” Mr. Moglen said. By contrast, with tens of thousands of individual encrypted servers, there would be no one place where a repressive government could find out who was publishing or reading “subversive” material.

perhaps the difference in opinions on this subject expressed by Shindell and Caldeira is nothing more than an academic turf battle over what it means for policy makers to focus on "climate" -- with one wanting the term (and justifications for action invoking that term) to be reserved for long-term climate issues centered on carbon dioxide and the other focused on a broader definition of climate and its impacts.  If so, then it is important to realize that such turf battles have practical consequences. Shindell's breath of fresh air gets the last word with his explanation why it is that we must consider long- and short- term climate impacts at the same time, and how we balance them will reflect a host of non-scientific considerations: So rather than set one against the other, I’d view this as analogous to research on childhood leukemia versus Alzheimer’s. If you’re an advocate for child’s health, you may care more about the former, and if you’re a retiree you might care more about the latter. One could argue about which is most worthy based on number of cases, years of life lost, etc., but in the end it’s clear that both diseases are worth combating and any ranking of one over the other is a value judgement. Similarly, there is no scientific basis on which to decide which impacts of climate change are most important, and we can only conclude that both controls are worthwhile. The UNEP/WMO Assessment provides clear information on the benefits of short-lived forcer reductions so that decision-makers, and society at large, can decide how best to use limited resources.

If we eliminated emissions of methane and black carbon, but did nothing about carbon dioxide we would have delayedThis presupposes that CO2 emissions can be capped at current levels without economic devastation or that immediate economic devastation is warranted.

What's the answer for environmentalists? Change the message and frame the issue in a way that doesn't trigger unconscious opposition among so many Americans. That can be a simple as using the right labels: a recent study by researchers at the University of Michigan found that Republicans are less skeptical of "climate change" than "global warming," possibly because climate change sounds less specific. Possibly too because so broad a term includes the severe snowfalls of the past winter that can be a paradoxical result of a generally warmer world. Greens should also pin their message on subjects that are less controversial, like public health or national security. Instead of issuing dire warnings about an apocalyptic future — which seems to make many Americans stop listening — better to talk about the present generation's responsibility to the future, to bequeath their children and grandchildren a safer and healthy planet.

Group identification also plays a major role in how we make decisions — and that's another way facts can get filtered. Declining belief in climate science has been, for the most part in America, a conservative phenomenon. On the surface, that's curious: you could expect Republicans to be skeptical of economic solutions to climate change like a carbon tax, since higher taxes tend to be a Democratic policy, but scientific information ought to be non-partisan. Politicians never debate the physics of space travel after all, even if they argue fiercely over the costs and priorities associated with it. That, however, is the power of group thinking; for most conservative Americans, the very idea of climate science has been poisoned by ideologues who seek to advance their economic arguments by denying scientific fact. No additional data — new findings about CO2 feedback loops or better modeling of ice sheet loss — is likely to change their mind.

The bright side of all this irrationality is that it means human beings can act in ways that sometimes go against their immediate utility, sacrificing their own interests for the benefit of the group.

Our brains develop socially, not just selfishly, which means sustainable behavior — and salvation for the planet — may not be as difficult as it sometimes seem. We can motivate people to help stop climate change — it may just not be climate science that convinces them to act.

Jackson is a young bioscientist who, like many others, has discovered that the technologies used in genetics and molecular biology, once the preserve of only the most well-funded labs, are now cheap enough to allow experimental work to take place in their garages. For many, this means that they can conduct genetic experiments in a new way, adopting the so-called "hacker ethic" – the desire to tinker, deconstruct, rebuild.

The rise of this group is entertainingly documented in a new book by science writer Marcus Wohlsen, Biopunk (Current £18.99), which describes the parallels between today's generation of biological innovators and the rise of computer software pioneers of the 1980s and 1990s. Indeed, Bill Gates has said that if he were a teenager today, he would be working on biotechnology, not computer software.

open scientists suggest that it doesn't have to be that way. Their arguments are propelled by a number of different factors that are making transparency more viable than ever.The first and most powerful change has been the use of the web to connect people and collect information. The internet, now an indelible part of our lives, allows like-minded individuals to seek one another out and share vast amounts of raw data. Researchers can lay claim to an idea not by publishing first in a journal (a process that can take many months) but by sharing their work online in an instant.And while the rapidly decreasing cost of previously expensive technical procedures has opened up new directions for research, there is also increasing pressure for researchers to cut costs and deliver results. The economic crisis left many budgets in tatters and governments around the world are cutting back on investment in science as they try to balance the books. Open science can, sometimes, make the process faster and cheaper, showing what one advocate, Cameron Neylon, calls "an obligation and responsibility to the public purse".

"The litmus test of openness is whether you can have access to the data," says Dr Rufus Pollock, a co-founder of the Open Knowledge Foundation, a group that promotes broader access to information and data. "If you have access to the data, then anyone can get it, use it, reuse it and redistribute it… we've always built on the work of others, stood on the shoulders of giants and learned from those who have gone before."

moves are afoot to disrupt the closed world of academic journals and make high-level teaching materials available to the public. The Public Library of Science, based in San Francisco, is working to make journals more freely accessible

it's more than just politics at stake – it's also a fundamental right to share knowledge, rather than hide it. The best example of open science in action, he suggests, is the Human Genome Project, which successfully mapped our DNA and then made the data public. In doing so, it outflanked J Craig Venter's proprietary attempt to patent the human genome, opening up the very essence of human life for science, rather than handing our biological information over to corporate interests.

Open science proponents say that they do not want to make the current system a thing of the past, but that it shouldn't be seen as immutable either. In fact, they say, the way most people conceive of science – as a highly specialised academic discipline conducted by white-coated professionals in universities or commercial laboratories – is a very modern construction.It is only over the last century that scientific disciplines became industrialised and compartmentalised.

open scientists say they don't want to throw scientists to the wolves: they just want to help answer questions that, in many cases, are seen as insurmountable.

"Some people, very straightforwardly, said that they didn't like the idea because it undermined the concept of the romantic, lone genius." Even the most dedicated open scientists understand that appeal. "I do plan to keep going at them," he says of collaborative projects. "But I haven't given up on solitary thinking about problems entirely."

Zuckerberg's claim -- which he's already pointed out involved taking his words out of context -- was just that there could be socially useful reasons why younger people might be helped if they could have accounts, but over aggressive internet controls prevent that. Again, that seems to argue against control, not for it.

The internet does not exist as untouchable. Morality and the rule of law do apply to the actions people do there. The question is whether those laws are appropriate. In many cases, it appears they're not.

the fallacy is not that these laws are obsolete because they're difficult to enforce. It's that they're obsolete because many of them don't make any sense, such as these injunctions that seek to merely protect the rich and famous from having their own embarrassing actions discussed.

ome of these laws aren't "difficult" to enforce, they're impossible to enforce. And it's not because the internet is some "wild west," but because it's a very different platform of communication -- a many to many platform, which the world has not had before. We've had one-to-one and one-to-many forms of communication, but a many-to-many platform really does change some important fundamentals when it comes to speech. Far more important are the questions of internet access to unsuitable material, especially but not solely by children, as well as the danger to children from inadequately policed social media. Merely to write such a sentence is to invite outrage in some quarters, but these issues are all too easy for a society to ignore until they return to haunt us. And the proper response, if there is "unsuitable" (unsuitable to whom, by the way?) content is to go after those who produced and distributed it. Not to seek to block access and sweep it under the rug. That's denial. Let's live in reality.

Kettle talks about spam and pornography. Yet, I almost never see spam any more. Why? Because technologists came in and built filters. I never see pornography either. And not because of any laws or filters, but because the websites I surf don't display any, and contrary to the myth makers, it's pretty difficult to "accidentally" run into porn. I do a lot of surfing and can't recall ever accidentally coming across any.