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Some European leaders, including Angela Merkel, may be backtracking fast on their commitment to nuclear power, but despite yesterday's escalation of the ongoing crisis in Fukushima, Japan, there appear to be no signs that India, China and other emerging economies will succumb to a similar backlash. For the emerging economies, overcoming poverty and insecurity of supply remain the overriding priorities of energy policy.

there is a tendency to conclude that govts with the best expert advice have made this decision because there is a real danger of something sinister happening. But remember govts are also under pressure to act because they are made up of politicians - also they may be making precautionary moves because they have little to lose and have to be seen as being pro-active. How real is the danger of harmful radiation reaching Tokyo and should you leave if you're in Tokyo? There were many people doing a "wait and see" before Wednesday but once the US & UK govt called for a pull-out, the fear factor rose several notches and if you're a Japanese in Tokyo watching all the foreigners "abandoning" your city, you start to feel some anxiety and later panic. One EU official used the word "apocalypse"[Link] to describe the situation in Japan and the fear index hit the roof....then a whole herd of experts came out to paint more dire scenarios saying the Japanese have lost all control of the nuclear plants. All this lead the public to think that calamity is the most likely outcome of the unfolding saga and if make a decision from all this, you will just run for the exits if you're in Tokyo. All this is happening while the Japanese govt is trying to calm the people and prevent a pandemonium after the triple disaster hit the country. In China, people have emptied the supermarket shelves of iodized salt because of media reports that the consumption of iodine can block radioactive iodine from being absorbed by thyroid glands causing thyroid cancer. There are also reports of people getting ill after ingesting iodine pills out of fear of radiation.

Much of this flow of cash was the product of the Three Power Source Development Laws, a sophisticated system of government subsidies created in 1974 by Kakuei Tanaka, the powerful prime minister who shaped Japan’s nuclear power landscape and used big public works projects to build postwar Japan’s most formidable political machine. The law required all Japanese power consumers to pay, as part of their utility bills, a tax that was funneled to communities with nuclear plants. Officials at the Ministry of Economy, Trade and Industry, which regulates the nuclear industry, and oversees the subsidies, refused to specify how much communities have come to rely on those subsidies. “This is money to promote the locality’s acceptance of a nuclear plant,” said Tatsumi Nakano of the ministry’s Agency for Natural Resources and Energy.

In the entire news bulletin, almost nothing was mentioned about the areas where the earthquake was most severe and the tsunami most devastating (i.e. the Sendai area). There was hardly any footage, no on-the-spot reporting, no casualty figures, nothing about how victims are putting up. OK, to be fair there were a few seconds showing people queuing up to get food and drinking water at one shop. Not a word about 10,000 people missing from Minamisanriku. Not even about rescue teams struggling to get to the worst areas. Amazingly, not a word too was said about the nuclear plants with overheating cores, or the hurried evacuations (that I learnt about online), at first 3 km radius, then 10 km, and now 20 km. . .  suggesting that the situation is probably out of control and may be becoming critical. To CNA, it is apparently not news. What was news was how horrid it was that middle-class Singaporeans were stuck at the airport unable to go on holiday.

in complex systems, "no matter how effective conventional safety devices are, there is a form of accident that is inevitable" - hence the term "normal accidents".

system accidents occur with many technologies: Take the example of a highway blow-out leading to a pile-up. This may have disastrous consequences for those involved but cannot be described as a disaster. The latter only happens when the technologies involved have the potential to affect many innocent bystanders. This "dread factor" is why the nuclear aspect of Japan's ordeal has come to dominate headlines, even though the tsunami has had much greater immediate impact on lives.

It is simply too early to say what precisely went wrong at Fukushima, and it has been surprising to see commentators speak with such speed and certainty. Most people accept that they will only ever have a rough understanding of the facts. But they instinctively ask if they can trust those in charge and wonder why governments support particular technologies so strongly.

Industry and governments need to be more straightforward with the public. The pretence of knowledge is deeply unscientific; a more humble approach where officials are frank about the unknowns would paradoxically engender greater trust.

Likewise, nuclear's opponents need to adopt a measured approach. We need a fuller democratic debate about the choices we are making. Catastrophic potential needs to be a central criterion in decisions about technology. Advice from experts is useful but the most significant questions are ethical in character.

If technologies can potentially have disastrous effects on large numbers of innocent bystanders, someone needs to represent their interests. We might expect this to be the role of governments, yet they have generally become advocates of nuclear power because it is a relatively low-carbon technology that reduces reliance on fossil fuels. Unfortunately, this commitment seems to have reduced their ability to be seen to act as honest brokers, something acutely felt at times like these, especially since there have been repeated scandals in Japan over the covering-up of information relating to accidents at reactors.

Post Fukushima, governments in Germany, Switzerland and Austria already appear to be shifting their policies. Rational voices, such as the Britain's chief scientific adviser John Beddington, are saying quite logically that we should not compare the events in Japan with the situation in Britain, which does not have the same earthquake risk. Unfortunately, such arguments are unlikely to prevail in the politics of risky technologies.

firms and investors involved in nuclear power have often failed to take regulatory and political risk into account; history shows that nuclear accidents can lead to tighter regulations, which in turn can increase nuclear costs. Further ahead, the proponents of hazardous technologies need to bear the full costs of their products, including insurance liabilities and the cost of independent monitoring of environmental and health effects. As it currently stands, taxpayers would pay for any future nuclear incident.

Critics of technology are often dubbed in policy circles as anti-science. Yet critical thinking is central to any rational decision-making process - it is less scientific to support a technology uncritically. Accidents happen with all technologies, and are regrettable but not disastrous so long as the technology does not have catastrophic potential; this raises significant questions about whether we want to adopt technologies that do have such potential.

"I demand slow motion footage of this atrocity," it's not just gruesome curiosity, or an unempathetic OMG factor, at work here. There is something profoundly humbling about seeing how fragile we truly are, how swiftly and easily everything can be wiped out. The footage from Japan is indeed spectacular. It's also a wrenching memento mori, a reminder of our mortality. Because with each breath we take, all of us are just little boats in the whirlpool, hoping to hang on through the storm. 

The Japan Shogi Association, incidentally, seems to have a deep fear of computers beating humans. In 2005, it introduced a ban on professional members playing computers without permission, and Shimizu's defeat was the first since a simpler computer system was beaten by a (male) champion, Akira Watanabe, in 2007.

Perhaps the association doesn't mind so much if a woman is beaten: NHK reports that the JSA will conduct an in-depth analysis of the match before it decides whether to allow the software to challenge a higher-ranking male professional player.

But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology. In the field of medicine, the phenomenon seems extremely widespread, affecting not only antipsychotics but also therapies ranging from cardiac stents to Vitamin E and antidepressants: Davis has a forthcoming analysis demonstrating that the efficacy of antidepressants has gone down as much as threefold in recent decades.

In private, Schooler began referring to the problem as “cosmic habituation,” by analogy to the decrease in response that occurs when individuals habituate to particular stimuli. “Habituation is why you don’t notice the stuff that’s always there,” Schooler says. “It’s an inevitable process of adjustment, a ratcheting down of excitement. I started joking that it was like the cosmos was habituating to my ideas. I took it very personally.”

At first, he assumed that he’d made an error in experimental design or a statistical miscalculation. But he couldn’t find anything wrong with his research. He then concluded that his initial batch of research subjects must have been unusually susceptible to verbal overshadowing. (John Davis, similarly, has speculated that part of the drop-off in the effectiveness of antipsychotics can be attributed to using subjects who suffer from milder forms of psychosis which are less likely to show dramatic improvement.) “It wasn’t a very satisfying explanation,” Schooler says. “One of my mentors told me that my real mistake was trying to replicate my work. He told me doing that was just setting myself up for disappointment.”

the effect is especially troubling because of what it exposes about the scientific process. 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? Francis Bacon, the early-modern philosopher and pioneer of the scientific method, once declared that experiments were essential, because they allowed us to “put nature to the question.” But it appears that nature often gives us different answers.

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. And 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. “Whenever I start talking about this, scientists get very nervous,” he says. “But I still want to know what happened to my results. Like most scientists, I assumed that it would get easier to document my effect over time. I’d get better at doing the experiments, at zeroing in on the conditions that produce verbal overshadowing. So why did the opposite happen? I’m convinced that we can use the tools of science to figure this out. First, though, we have to admit that we’ve got a problem.”

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. In fact, even when numerous variables were controlled for—Jennions knew, for instance, that the same author might publish several critical papers, which could distort his analysis—there was still a significant decrease in the validity of the hypothesis, often within a year of publication. 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.”

the worst part was that when I submitted these null results I had difficulty getting them published. The journals only wanted confirming data. It was too exciting an idea to disprove, at least back then.

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.

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. A “significant” result is defined as any data point that would be produced by chance less than five per cent of the time. This ubiquitous test was invented in 1922 by the English mathematician Ronald Fisher, who picked five per cent as the boundary line, somewhat arbitrarily, because it made pencil and slide-rule calculations easier. 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. In recent years, publication bias has mostly been seen as a problem for clinical trials, since pharmaceutical companies are less interested in publishing results that aren’t favorable. But it’s becoming increasingly clear that publication bias also produces major distortions in fields without large corporate incentives, such as psychology and ecology.

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

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.

The funnel graph visually captures the distortions of selective reporting. For instance, 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.” In a recent review article, 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 “shoehorning” 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.”

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. Between 1966 and 1995, there were forty-seven studies of acupuncture in China, Taiwan, and Japan, and every single trial concluded that acupuncture was an effective treatment. During the same period, there were ninety-four clinical trials of acupuncture in the United States, Sweden, and the U.K., and only fifty-six per cent of these studies found any therapeutic benefits. As Palmer notes, this wide discrepancy suggests that scientists find ways to confirm their preferred hypothesis, disregarding what they don’t want to see. Our beliefs are a form of blindness.

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. Forty-five of these studies reported positive results, suggesting that the intervention being tested was effective. Because most of these studies were randomized controlled trials—the “gold standard” of medical evidence—they tended to have a significant impact on clinical practice, and led to the spread of treatments such as hormone replacement therapy for menopausal women and daily low-dose aspirin to prevent heart attacks and strokes. Nevertheless, 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 situation is even worse when a subject is fashionable. In recent years, for instance, there have been hundreds of studies on the various genes that control the differences in disease risk between men and women. These findings have included everything from the mutations responsible for the increased risk of schizophrenia to the genes underlying hypertension. Ioannidis and his colleagues looked at four hundred and thirty-two of these claims. They quickly discovered that the vast majority had serious flaws. But 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.”

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. “The scientists are so eager to pass this magical test that they start playing around with the numbers, trying to find anything that seems worthy,” Ioannidis says. In recent years, Ioannidis has become increasingly blunt about the pervasiveness of the problem. One of his most cited papers has a deliberately provocative title: “Why Most Published Research Findings Are False.”

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 show a strong effect. They really want to believe that it’s true.”

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,” he says. The current “obsession” with replicability distracts from the real problem, which is faulty design. He notes that nobody even tries to replicate most science papers—there are simply too many. (According to Nature, a third of all studies never even get cited, let alone repeated.)

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,” Schooler says. “It would help us finally deal with all these issues that the decline effect is exposing.”

Although such reforms would mitigate the dangers of publication bias and selective reporting, they still wouldn’t erase the decline effect. This is largely because 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

John Crabbe, a neuroscientist at the Oregon Health and Science University, conducted an experiment that showed how unknowable chance events can skew tests of replicability. He performed a series of experiments on mouse behavior in three different science labs: in Albany, New York; Edmonton, Alberta; and Portland, Oregon. Before he conducted the experiments, he tried to standardize every variable he could think of. The same strains of mice were used in each lab, shipped on the same day from the same supplier. The animals were raised in the same kind of enclosure, with the same brand of sawdust bedding. They had been exposed to the same amount of incandescent light, were living with the same number of littermates, and were fed the exact same type of chow pellets. When the mice were handled, it was with the same kind of surgical glove, and when they were tested it was on the same equipment, at the same time in the morning.

The premise of this test of replicability, of course, is that each of the labs should have generated the same pattern of results. “If any set of experiments should have passed the test, it should have been ours,” Crabbe says. “But that’s not the way it turned out.” In one experiment, Crabbe injected a particular strain of mouse with cocaine. In Portland the mice given the drug moved, on average, six hundred centimetres more than they normally did; in Albany they moved seven hundred and one additional centimetres. But in the Edmonton lab they moved more than five thousand additional centimetres. Similar deviations were observed in a test of anxiety. Furthermore, these inconsistencies didn’t follow any detectable pattern. In Portland one strain of mouse proved most anxious, while in Albany another strain won that distinction.

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. Grants get written, follow-up studies are conducted. The end result is a scientific accident that can take years to unravel.

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. Verbal overshadowing might exhibit the decline effect, but it remains extensively relied upon within the field. The same holds for any number of phenomena, from the disappearing benefits of second-generation antipsychotics to the weak coupling ratio exhibited by decaying neutrons, which appears to have fallen by more than ten standard deviations between 1969 and 2001. 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.) Despite these findings, second-generation antipsychotics are still widely prescribed, and our model of the neutron hasn’t changed. The law of gravity remains the same.

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.

The moratorium could cause a spike in CO2 emissions as Germany turns to its other, more carbon-intensive sources to supply its energy demand. Already, the country has been engaged in a "dash for coal", building dozens of new coal plants in response to the perverse incentives and intense lobbying from the coal industries made possible by the European Emissions Trading Scheme. (As previously reported by Breakthrough Europe).

if lost generation were made up for entirely by coal-fired plants, carbon emissions would increase annually by as much as 33 million tons. This would represent an overall 4% annual increase in carbon emissions for the country and an 8% increase in carbon emissions for the power sector alone.

Alternatively, should the country try to replace lost generation entirely with power from renewables, it would need to more than double generation of renewable energy, from where it currently stands at 97 billion kWh to about 237 billion kWh. As part of the country's low-carbon strategy, Germany has planned to deploy at least 20% renewable energy sources by 2020. If the nation now chooses to meet this goal by displacing nuclear plants, 2020 emissions levels would be higher than had the country otherwise phased out its carbon-intensive coal or natural gas plants.

*Carbon emissions factors used are those estimated by the World Bank in 2009 for new coal-fired power plants (0.795 t C02/MWh) and new gas-fired power plants (0.398 t C02/MWh) **Data from Carbon Monitoring For Action, European Nuclear Society Data, and US Energy Information Administration

This wasn’t the case everywhere. Germany’s standards agency, established in 1887, was busy setting rules for everything from the content of dyes to the process for making porcelain; other European countries soon followed suit. Higher-quality products, in turn, helped the growth in Germany’s trade exceed that of the United States in the 1890s. America finally got its act together in 1894, when Congress standardized the meaning of what are today common scientific measures, including the ohm, the volt, the watt and the henry, in line with international metrics. And, in 1901, the United States became the last major economic power to establish an agency to set technological standards. The result was a boom in product innovation in all aspects of life during the 20th century. Today we can go to our hardware store and choose from hundreds of light bulbs that all conform to government-mandated quality and performance standards.

Technological standards not only promote innovation — they also can help protect one country’s industries from falling behind those of other countries. Today China, India and other rapidly growing nations are adopting standards that speed the deployment of new technologies. Without similar requirements to manufacture more technologically advanced products, American companies risk seeing the overseas markets for their products shrink while innovative goods from other countries flood the domestic market. To prevent that from happening, America needs not only to continue developing standards, but also to devise a strategy to apply them consistently and quickly.

The best approach would be to borrow from Japan, whose Top Runner program sets energy-efficiency standards by identifying technological leaders in a particular industry — say, washing machines — and mandating that the rest of the industry keep up. As technologies improve, the standards change as well, enabling a virtuous cycle of improvement. At the same time, the government should work with businesses to devise multidimensional standards, so that consumers don’t balk at products because they sacrifice, say, brightness and cost for energy efficiency.

This is not to say that innovation doesn’t bring disruption, and American policymakers can’t ignore the jobs that are lost when government standards sweep older technologies into the dustbin of history. An effective way forward on light bulbs, then, would be to apply standards only to those manufacturers that produce or import in large volume. Meanwhile, smaller, legacy light-bulb producers could remain, cushioning the blow to workers and meeting consumer demand.

Technologies and the standards that guide their deployment have revolutionized American society. They’ve been so successful, in fact, that the role of government has become invisible — so much so that even members of Congress should be excused for believing the government has no business mandating your choice of light bulbs.

In this New York Times’ article, “Teachers Wonder, Why the scorn?“, the writer notes the often scathing comments from counter-demonstrators – “Oh you pathetic teachers, read the online comments and placards of counterdemonstrators. You are glorified baby sitters who leave work at 3 p.m. You deserve minimum wage.” What had begun as an ostensibly ‘economic reform’ targeted at teachers’ unions has gradually transmogrified into a kind of “character attack” to this section of American society – teachers are people who wage violent protests (thanks to borrowed footage from the West Coast) and they are undeserving of their economic benefits, and indeed treat these privileges as ‘rights’. The ‘war’ is waged on multiple fronts, economic, political, social, psychological even — or at least one gets this sort of picture from reading these articles.

as Singaporeans with a uniquely Singaporean work ethic, we may perceive functioning ‘trade unions’ as those institutions in the so-called “West” where they amass lots of membership, then hold the government ‘hostage’ in order to negotiate higher wages and benefits. Think of trade unions in the Singaporean context, and I think of SIA pilots. And of LKY’s various firm and stern comments on those issues. Think of trade unions and I think of strikes in France, in South Korea, when I was younger, and of my mum saying, “How irresponsible!” before flipping the TV channel.

The reason why I think the teachers’ protests should not be seen solely as an issue about trade-unions, and evaluated myopically and naively in terms of whether trade unions are ‘good’ or ‘bad’ is because the protests feature in a larger political context with the billionaire Koch brothers at the helm, financing and directing much of what has transpired in recent weeks. Or at least according to certain articles which I present here.

In this NYT article entitled “Billionaire Brothers’ Money Plays Role in Wisconsin Dispute“, the writer noted that Koch Industries had been “one of the biggest contributors to the election campaign of Gov. Scott Walker of Wisconsin, a Republican who has championed the proposed cuts.” Further, the president of Americans for Prosperity, a nonprofit group financed by the Koch brothers, had reportedly addressed counter-demonstrators last Saturday saying that “the cuts were not only necessary, but they also represented the start of a much-needed nationwide move to slash public-sector union benefits.” and in his own words -“ ‘We are going to bring fiscal sanity back to this great nation’ ”. All this rhetoric would be more convincing to me if they weren’t funded by the same two billionaires who financially enabled Walker’s governorship.

I now refer you to a long piece by Jane Mayer for The New Yorker titled, “Covert Operations: The billionaire brothers who are waging a war against Obama“. According to her, “The Kochs are longtime libertarians who believe in drastically lower personal and corporate taxes, minimal social services for the needy, and much less oversight of industry—especially environmental regulation. These views dovetail with the brothers’ corporate interests.”

Their libertarian modus operandi involves great expenses in lobbying, in political contributions and in setting up think tanks. From 2006-2010, Koch Industries have led energy companies in political contributions; “[i]n the second quarter of 2010, David Koch was the biggest individual contributor to the Republican Governors Association, with a million-dollar donation.” More statistics, or at least those of the non-anonymous donation records, can be found on page 5 of Mayer’s piece.

Naturally, the Democrats also have their billionaire donors, most notably in the form of George Soros. Mayer writes that he has made ‘generous private contributions to various Democratic campaigns, including Obama’s.” Yet what distinguishes him from the Koch brothers here is, as Michael Vachon, his spokesman, argued, ‘that Soros’s giving is transparent, and that “none of his contributions are in the service of his own economic interests.” ‘ Of course, this must be taken with a healthy dose of salt, but I will note here that in Charles Ferguson’s documentary Inside Job, which was about the 2008 financial crisis, George Soros was one of those interviewed who was not portrayed negatively. (My review of it is here.)

Of the Koch brothers’ political investments, what interested me more was the US’ “first libertarian thinktank”, the Cato Institute. Mayer writes, ‘When President Obama, in a 2008 speech, described the science on global warming as “beyond dispute,” the Cato Institute took out a full-page ad in the Times to contradict him. Cato’s resident scholars have relentlessly criticized political attempts to stop global warming as expensive, ineffective, and unnecessary. Ed Crane, the Cato Institute’s founder and president, told [Mayer] that “global-warming theories give the government more control of the economy.” ‘

K Street refers to a major street in Washington, D.C. where major think tanks, lobbyists and advocacy groups are located.

with recent developments as the Citizens United case where corporations are now ‘persons’ and have no caps in political contributions, the Koch brothers are ever better-positioned to take down their perceived big, bad government and carry out their ideological agenda as sketched in Mayer’s piece

with much important news around the world jostling for our attention – earthquake in Japan, Middle East revolutions – the passing of an anti-union bill (which finally happened today, for better or for worse) in an American state is unlikely to make a headline able to compete with natural disasters and revolutions. Then, to quote Wisconsin Governor Scott Walker during that prank call conversation, “Sooner or later the media stops finding it [the teacher protests] interesting.”

What remains more puzzling for me is why the American public seems to buy into the Koch-funded libertarian rhetoric. Mayer writes, ‘ “Income inequality in America is greater than it has been since the nineteen-twenties, and since the seventies the tax rates of the wealthiest have fallen more than those of the middle class. Yet the brothers’ message has evidently resonated with voters: a recent poll found that fifty-five per cent of Americans agreed that Obama is a socialist.” I suppose that not knowing who is funding the political rhetoric makes it easier for the public to imbibe it.

Even though he believes in his method, he ignores the huge body of evidence that shows radon gas is no more reliable than any other “predictor”.

If the victims insist on suing someone, they should leave the seismologists alone and look into the construction of some of those buildings. The stories out of L’Aquila suggest that the death toll was much higher because of official corruption and shoddy construction, as happens in many countries both before and after big quakes.

much of the construction is apparently Mafia-controlled in that area—good luck suing them! Sadly, the ancient medieval buildings that crumbled were the most vulnerable because they were made of unreinforced masonry, the worst possible construction material in earthquake country

what does this imply for scientists who are working in a field that might have predictive power? In a litigious society like Italy or the U.S., this is a serious question. If a reputable seismologist does make a prediction and fails, he’s liable, because people will panic and make foolish decisions and then blame the seismologist for their losses. Now the Italian courts are saying that (despite world scientific consensus) seismologists are liable if they don’t predict quakes. They’re damned if they do, and damned if they don’t. In some societies where seismologists work hard at prediction and preparation (such as China and Japan), there is no precedent for suing scientists for doing their jobs properly, and the society and court system does not encourage people to file frivolous suits. But in litigious societies, the system is counterproductive, and stifles research that we would like to see developed. What seismologist would want to work on earthquake prediction if they can be sued? I know of many earth scientists with brilliant ideas not only about earthquake prediction but even ways to defuse earthquakes, slow down global warming, or many other incredible but risky brainstorms—but they dare not propose the idea seriously or begin to implement it for fear of being sued.

Export dependency is another correlate with English. Countries that export more are better at English (though it’s not clear which factor causes which).  Malaysia, the best English-performer in Asia, is also the sixth-most export-dependent country in the world.  (Singapore was too small to make the list, or it probably would have ranked similarly.) This is perhaps surprising, given a recent trend towards anti-colonial and anti-Western sentiment in Malaysia’s politics. The study’s authors surmise that English has become seen as a mere tool, divorced in many minds from its associations with Britain and America.

Teaching plays a role, too. Starting young, while it seems a good idea, may not pay off: children between eight and 12 learn foreign languages faster than younger ones, so each class hour on English is better spent on a 10-year-old than on a six-year-old.

Between 1984 and 2000, the study's authors say, the Netherlands and Denmark began English-teaching between 10 and 12, while Spain and Italy began between eight and 11, with considerably worse results. Mr Hult reckons that poor methods, particularly the rote learning he sees in Japan, can be responsible for poor results despite strenuous efforts.

one surprising result is that China and India are next to each other (29th and 30th of 44) in the rankings, despite India’s reputation as more Anglophone. Mr Hult says that the Chinese have made a broad push for English (they're "practically obsessed with it”). But efforts like this take time to marinade through entire economies, and so may have avoided notice by outsiders. India, by contrast, has long had well-known Anglophone elites, but this is a narrow slice of the population in a country considerably poorer and less educated than China. English has helped India out-compete China in services, while China has excelled in manufacturing. But if China keeps up the push for English, the subcontinental neighbour's advantage may not last.