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Test prep for kindergartners seems like a pretty blatant example of class privilege. But, of course, the argument that advantaging your own kid necessarily involves disadvantaging someone else’s applies to all sorts of things, from tutoring, to a leisurely summer with which to study for the SAT, to financial support during their unpaid internships, to helping them buy a house and, thus, keeping home prices high. I think it’s worth re-evaluating. Is giving your kid every advantage the moral thing to do?

This is also the fallacy of the perfect solution – since science-based medicine is not perfect, there is no legitimate basis for criticism of any modality.

The MIT researchers’ paper, however, suggests that the danger of information cascades may not be as dire as it previously seemed.

a mathematical model that describes attempts by members of a social network to make binary decisions — such as which of two brands of cell phone to buy — on the basis of decisions made by their neighbors. The model assumes that for all members of the population, there is a single right decision: one of the cell phones is intrinsically better than the other. But some members of the network have bad information about which is which.

The MIT researchers analyzed the propagation of information under two different conditions. In one case, there’s a cap on how much any one person can know about the state of the world: even if one cell phone is intrinsically better than the other, no one can determine that with 100 percent certainty. In the other case, there’s no such cap. There’s debate among economists and information theorists about which of these two conditions better reflects reality, and Kleinberg suggests that the answer may vary depending on the type of information propagating through the network. But previous models had suggested that, if there is a cap, information cascades are almost inevitable.

if there’s no cap on certainty, an expanding social network will eventually converge on an accurate representation of the state of the world; that wasn’t a big surprise. But they also showed that in many common types of networks, even if there is a cap on certainty, convergence will still occur.

people in the past have looked at it using more myopic models,” says Acemoglu. “They would be averaging type of models: so my opinion is an average of the opinions of my neighbors’.” In such a model, Acemoglu says, the views of people who are “oversampled” — who are connected with a large enough number of other people — will end up distorting the conclusions of the group as a whole.

What we’re doing is looking at it in a much more game-theoretic manner, where individuals are realizing where the information comes from. So there will be some correction factor,” Acemoglu says. “If I’m seeing you, your action, and I’m seeing Munzer’s action, and I also know that there is some probability that you might have observed Munzer, then I discount his opinion appropriately, because I know that I don’t want to overweight it. And that’s the reason why, even though you have these influential agents — it might be that Munzer is everywhere, and everybody observes him — that still doesn’t create a herd on his opinion.”

the new paper leaves a few salient questions unanswered, such as how quickly the network will converge on the correct answer, and what happens when the model of agents’ knowledge becomes more complex.

the MIT researchers begin to address both questions. One paper examines rate of convergence, although Dahleh and Acemoglu note that that its results are “somewhat weaker” than those about the conditions for convergence. Another paper examines cases in which different agents make different decisions given the same information: some people might prefer one type of cell phone, others another. In such cases, “if you know the percentage of people that are of one type, it’s enough — at least in certain networks — to guarantee learning,” Dahleh says. “I don’t need to know, for every individual, whether they’re for it or against it; I just need to know that one-third of the people are for it, and two-thirds are against it.” For instance, he says, if you notice that a Chinese restaurant in your neighborhood is always half-empty, and a nearby Indian restaurant is always crowded, then information about what percentages of people prefer Chinese or Indian food will tell you which restaurant, if either, is of above-average or below-average quality.

This is why, for example, large numbers of Americans oppose the idea of an estate tax even though the current form of the tax, slated to return in 2011, is very unlikely to affect them or their estates. In narrowly self-interested terms, that view may be irrational, but most Americans are unwilling to frame national issues in terms of rich versus poor. There’s a great deal of hostility toward various government bailouts, but the idea of “undeserving” recipients is the key factor in those feelings. Resentment against Wall Street gamesters hasn’t spilled over much into resentment against the wealthy more generally. The bailout for General Motors’ labor unions wasn’t so popular either—again, obviously not because of any bias against the wealthy but because a basic sense of fairness was violated. As of November 2010, congressional Democrats are of a mixed mind as to whether the Bush tax cuts should expire for those whose annual income exceeds $250,000; that is in large part because their constituents bear no animus toward rich people, only toward undeservedly rich people.

envy is usually local. At least in the United States, most economic resentment is not directed toward billionaires or high-roller financiers—not even corrupt ones. It’s directed at the guy down the hall who got a bigger raise. It’s directed at the husband of your wife’s sister, because the brand of beer he stocks costs $3 a case more than yours, and so on. That’s another reason why a lot of people aren’t so bothered by income or wealth inequality at the macro level. Most of us don’t compare ourselves to billionaires. Gore Vidal put it honestly: “Whenever a friend succeeds, a little something in me dies.”

Occasionally the cynic in me wonders why so many relatively well-off intellectuals lead the egalitarian charge against the privileges of the wealthy. One group has the status currency of money and the other has the status currency of intellect, so might they be competing for overall social regard? The high status of the wealthy in America, or for that matter the high status of celebrities, seems to bother our intellectual class most. That class composes a very small group, however, so the upshot is that growing income inequality won’t necessarily have major political implications at the macro level.

All that said, income inequality does matter—for both politics and the economy.

The numbers are clear: Income inequality has been rising in the United States, especially at the very top. The data show a big difference between two quite separate issues, namely income growth at the very top of the distribution and greater inequality throughout the distribution. The first trend is much more pronounced than the second, although the two are often confused.

When it comes to the first trend, the share of pre-tax income earned by the richest 1 percent of earners has increased from about 8 percent in 1974 to more than 18 percent in 2007. Furthermore, the richest 0.01 percent (the 15,000 or so richest families) had a share of less than 1 percent in 1974 but more than 6 percent of national income in 2007. As noted, those figures are from pre-tax income, so don’t look to the George W. Bush tax cuts to explain the pattern. Furthermore, these gains have been sustained and have evolved over many years, rather than coming in one or two small bursts between 1974 and today.1

At the same time, wage growth for the median earner has slowed since 1973. But that slower wage growth has afflicted large numbers of Americans, and it is conceptually distinct from the higher relative share of top income earners. For instance, if you take the 1979–2005 period, the average incomes of the bottom fifth of households increased only 6 percent while the incomes of the middle quintile rose by 21 percent. That’s a widening of the spread of incomes, but it’s not so drastic compared to the explosive gains at the very top.

The broader change in income distribution, the one occurring beneath the very top earners, can be deconstructed in a manner that makes nearly all of it look harmless. For instance, there is usually greater inequality of income among both older people and the more highly educated, if only because there is more time and more room for fortunes to vary. Since America is becoming both older and more highly educated, our measured income inequality will increase pretty much by demographic fiat. Economist Thomas Lemieux at the University of British Columbia estimates that these demographic effects explain three-quarters of the observed rise in income inequality for men, and even more for women.2

Attacking the problem from a different angle, other economists are challenging whether there is much growth in inequality at all below the super-rich. For instance, real incomes are measured using a common price index, yet poorer people are more likely to shop at discount outlets like Wal-Mart, which have seen big price drops over the past twenty years.3 Once we take this behavior into account, it is unclear whether the real income gaps between the poor and middle class have been widening much at all. Robert J. Gordon, an economist from Northwestern University who is hardly known as a right-wing apologist, wrote in a recent paper that “there was no increase of inequality after 1993 in the bottom 99 percent of the population”, and that whatever overall change there was “can be entirely explained by the behavior of income in the top 1 percent.”4

And so we come again to the gains of the top earners, clearly the big story told by the data. It’s worth noting that over this same period of time, inequality of work hours increased too. The top earners worked a lot more and most other Americans worked somewhat less. That’s another reason why high earners don’t occasion more resentment: Many people understand how hard they have to work to get there. It also seems that most of the income gains of the top earners were related to performance pay—bonuses, in other words—and not wildly out-of-whack yearly salaries.5

It is also the case that any society with a lot of “threshold earners” is likely to experience growing income inequality. A threshold earner is someone who seeks to earn a certain amount of money and no more. If wages go up, that person will respond by seeking less work or by working less hard or less often. That person simply wants to “get by” in terms of absolute earning power in order to experience other gains in the form of leisure—whether spending time with friends and family, walking in the woods and so on. Luck aside, that person’s income will never rise much above the threshold.

The funny thing is this: For years, many cultural critics in and of the United States have been telling us that Americans should behave more like threshold earners. We should be less harried, more interested in nurturing friendships, and more interested in the non-commercial sphere of life. That may well be good advice. Many studies suggest that above a certain level more money brings only marginal increments of happiness. What isn’t so widely advertised is that those same critics have basically been telling us, without realizing it, that we should be acting in such a manner as to increase measured income inequality. Not only is high inequality an inevitable concomitant of human diversity, but growing income inequality may be, too, if lots of us take the kind of advice that will make us happier.

Why is the top 1 percent doing so well?

Steven N. Kaplan and Joshua Rauh have recently provided a detailed estimation of particular American incomes.6 Their data do not comprise the entire U.S. population, but from partial financial records they find a very strong role for the financial sector in driving the trend toward income concentration at the top. For instance, for 2004, nonfinancial executives of publicly traded companies accounted for less than 6 percent of the top 0.01 percent income bracket. In that same year, the top 25 hedge fund managers combined appear to have earned more than all of the CEOs from the entire S&P 500. The number of Wall Street investors earning more than $100 million a year was nine times higher than the public company executives earning that amount. The authors also relate that they shared their estimates with a former U.S. Secretary of the Treasury, one who also has a Wall Street background. He thought their estimates of earnings in the financial sector were, if anything, understated.

Many of the other high earners are also connected to finance. After Wall Street, Kaplan and Rauh identify the legal sector as a contributor to the growing spread in earnings at the top. Yet many high-earning lawyers are doing financial deals, so a lot of the income generated through legal activity is rooted in finance. Other lawyers are defending corporations against lawsuits, filing lawsuits or helping corporations deal with complex regulations. The returns to these activities are an artifact of the growing complexity of the law and government growth rather than a tale of markets per se. Finance aside, there isn’t much of a story of market failure here, even if we don’t find the results aesthetically appealing.

When it comes to professional athletes and celebrities, there isn’t much of a mystery as to what has happened. Tiger Woods earns much more, even adjusting for inflation, than Arnold Palmer ever did. J.K. Rowling, the first billionaire author, earns much more than did Charles Dickens. These high incomes come, on balance, from the greater reach of modern communications and marketing. Kids all over the world read about Harry Potter. There is more purchasing power to spend on children’s books and, indeed, on culture and celebrities more generally. For high-earning celebrities, hardly anyone finds these earnings so morally objectionable as to suggest that they be politically actionable. Cultural critics can complain that good schoolteachers earn too little, and they may be right, but that does not make celebrities into political targets. They’re too popular. It’s also pretty clear that most of them work hard to earn their money, by persuading fans to buy or otherwise support their product. Most of these individuals do not come from elite or extremely privileged backgrounds, either. They worked their way to the top, and even if Rowling is not an author for the ages, her books tapped into the spirit of their time in a special way. We may or may not wish to tax the wealthy, including wealthy celebrities, at higher rates, but there is no need to “cure” the structural causes of higher celebrity incomes.

to be sure, the high incomes in finance should give us all pause.

The first factor driving high returns is sometimes called by practitioners “going short on volatility.” Sometimes it is called “negative skewness.” In plain English, this means that some investors opt for a strategy of betting against big, unexpected moves in market prices. Most of the time investors will do well by this strategy, since big, unexpected moves are outliers by definition. Traders will earn above-average returns in good times. In bad times they won’t suffer fully when catastrophic returns come in, as sooner or later is bound to happen, because the downside of these bets is partly socialized onto the Treasury, the Federal Reserve and, of course, the taxpayers and the unemployed.

if you bet against unlikely events, most of the time you will look smart and have the money to validate the appearance. Periodically, however, you will look very bad. Does that kind of pattern sound familiar? It happens in finance, too. Betting against a big decline in home prices is analogous to betting against the Wizards. Every now and then such a bet will blow up in your face, though in most years that trading activity will generate above-average profits and big bonuses for the traders and CEOs.

To this mix we can add the fact that many money managers are investing other people’s money. If you plan to stay with an investment bank for ten years or less, most of the people playing this investing strategy will make out very well most of the time. Everyone’s time horizon is a bit limited and you will bring in some nice years of extra returns and reap nice bonuses. And let’s say the whole thing does blow up in your face? What’s the worst that can happen? Your bosses fire you, but you will still have millions in the bank and that MBA from Harvard or Wharton. For the people actually investing the money, there’s barely any downside risk other than having to quit the party early. Furthermore, if everyone else made more or less the same mistake (very surprising major events, such as a busted housing market, affect virtually everybody), you’re hardly disgraced. You might even get rehired at another investment bank, or maybe a hedge fund, within months or even weeks.

Moreover, smart shareholders will acquiesce to or even encourage these gambles. They gain on the upside, while the downside, past the point of bankruptcy, is borne by the firm’s creditors. And will the bondholders object? Well, they might have a difficult time monitoring the internal trading operations of financial institutions. Of course, the firm’s trading book cannot be open to competitors, and that means it cannot be open to bondholders (or even most shareholders) either. So what, exactly, will they have in hand to object to?

Perhaps more important, government bailouts minimize the damage to creditors on the downside. Neither the Treasury nor the Fed allowed creditors to take any losses from the collapse of the major banks during the financial crisis. The U.S. government guaranteed these loans, either explicitly or implicitly. Guaranteeing the debt also encourages equity holders to take more risk. While current bailouts have not in general maintained equity values, and while share prices have often fallen to near zero following the bust of a major bank, the bailouts still give the bank a lifeline. Instead of the bank being destroyed, sometimes those equity prices do climb back out of the hole. This is true of the major surviving banks in the United States, and even AIG is paying back its bailout. For better or worse, we’re handing out free options on recovery, and that encourages banks to take more risk in the first place.

there is an unholy dynamic of short-term trading and investing, backed up by bailouts and risk reduction from the government and the Federal Reserve. This is not good. “Going short on volatility” is a dangerous strategy from a social point of view. For one thing, in so-called normal times, the finance sector attracts a big chunk of the smartest, most hard-working and most talented individuals. That represents a huge human capital opportunity cost to society and the economy at large. But more immediate and more important, it means that banks take far too many risks and go way out on a limb, often in correlated fashion. When their bets turn sour, as they did in 2007–09, everyone else pays the price.

And it’s not just the taxpayer cost of the bailout that stings. The financial disruption ends up throwing a lot of people out of work down the economic food chain, often for long periods. Furthermore, the Federal Reserve System has recapitalized major U.S. banks by paying interest on bank reserves and by keeping an unusually high interest rate spread, which allows banks to borrow short from Treasury at near-zero rates and invest in other higher-yielding assets and earn back lots of money rather quickly. In essence, we’re allowing banks to earn their way back by arbitraging interest rate spreads against the U.S. government. This is rarely called a bailout and it doesn’t count as a normal budget item, but it is a bailout nonetheless. This type of implicit bailout brings high social costs by slowing down economic recovery (the interest rate spreads require tight monetary policy) and by redistributing income from the Treasury to the major banks.

the “going short on volatility” strategy increases income inequality. In normal years the financial sector is flush with cash and high earnings. In implosion years a lot of the losses are borne by other sectors of society. In other words, financial crisis begets income inequality. Despite being conceptually distinct phenomena, the political economy of income inequality is, in part, the political economy of finance. Simon Johnson tabulates the numbers nicely: From 1973 to 1985, the financial sector never earned more than 16 percent of domestic corporate profits. In 1986, that figure reached 19 percent. In the 1990s, it oscillated between 21 percent and 30 percent, higher than it had ever been in the postwar period. This decade, it reached 41 percent. Pay rose just as dramatically. From 1948 to 1982, average compensation in the financial sector ranged between 99 percent and 108 percent of the average for all domestic private industries. From 1983, it shot upward, reaching 181 percent in 2007.7

There’s a second reason why the financial sector abets income inequality: the “moving first” issue. Let’s say that some news hits the market and that traders interpret this news at different speeds. One trader figures out what the news means in a second, while the other traders require five seconds. Still other traders require an entire day or maybe even a month to figure things out. The early traders earn the extra money. They buy the proper assets early, at the lower prices, and reap most of the gains when the other, later traders pile on. Similarly, if you buy into a successful tech company in the early stages, you are “moving first” in a very effective manner, and you will capture most of the gains if that company hits it big.

The moving-first phenomenon sums to a “winner-take-all” market. Only some relatively small number of traders, sometimes just one trader, can be first. Those who are first will make far more than those who are fourth or fifth. This difference will persist, even if those who are fourth come pretty close to competing with those who are first. In this context, first is first and it doesn’t matter much whether those who come in fourth pile on a month, a minute or a fraction of a second later. Those who bought (or sold, as the case may be) first have captured and locked in most of the available gains. Since gains are concentrated among the early winners, and the closeness of the runner-ups doesn’t so much matter for income distribution, asset-market trading thus encourages the ongoing concentration of wealth. Many investors make lots of mistakes and lose their money, but each year brings a new bunch of projects that can turn the early investors and traders into very wealthy individuals.

These two features of the problem—“going short on volatility” and “getting there first”—are related. Let’s say that Goldman Sachs regularly secures a lot of the best and quickest trades, whether because of its quality analysis, inside connections or high-frequency trading apparatus (it has all three). It builds up a treasure chest of profits and continues to hire very sharp traders and to receive valuable information. Those profits allow it to make “short on volatility” bets faster than anyone else, because if it messes up, it still has a large enough buffer to pad losses. This increases the odds that Goldman will repeatedly pull in spectacular profits.

Still, every now and then Goldman will go bust, or would go bust if not for government bailouts. But the odds are in any given year that it won’t because of the advantages it and other big banks have. It’s as if the major banks have tapped a hole in the social till and they are drinking from it with a straw. In any given year, this practice may seem tolerable—didn’t the bank earn the money fair and square by a series of fairly normal looking trades? Yet over time this situation will corrode productivity, because what the banks do bears almost no resemblance to a process of getting capital into the hands of those who can make most efficient use of it. And it leads to periodic financial explosions. That, in short, is the real problem of income inequality we face today. It’s what causes the inequality at the very top of the earning pyramid that has dangerous implications for the economy as a whole.

What about controlling bank risk-taking directly with tight government oversight? That is not practical. There are more ways for banks to take risks than even knowledgeable regulators can possibly control; it just isn’t that easy to oversee a balance sheet with hundreds of billions of dollars on it, especially when short-term positions are wound down before quarterly inspections. It’s also not clear how well regulators can identify risky assets. Some of the worst excesses of the financial crisis were grounded in mortgage-backed assets—a very traditional function of banks—not exotic derivatives trading strategies. Virtually any asset position can be used to bet long odds, one way or another. It is naive to think that underpaid, undertrained regulators can keep up with financial traders, especially when the latter stand to earn billions by circumventing the intent of regulations while remaining within the letter of the law.

For the time being, we need to accept the possibility that the financial sector has learned how to game the American (and UK-based) system of state capitalism. It’s no longer obvious that the system is stable at a macro level, and extreme income inequality at the top has been one result of that imbalance. Income inequality is a symptom, however, rather than a cause of the real problem. The root cause of income inequality, viewed in the most general terms, is extreme human ingenuity, albeit of a perverse kind. That is why it is so hard to control.

Another root cause of growing inequality is that the modern world, by so limiting our downside risk, makes extreme risk-taking all too comfortable and easy. More risk-taking will mean more inequality, sooner or later, because winners always emerge from risk-taking. Yet bankers who take bad risks (provided those risks are legal) simply do not end up with bad outcomes in any absolute sense. They still have millions in the bank, lots of human capital and plenty of social status. We’re not going to bring back torture, trial by ordeal or debtors’ prisons, nor should we. Yet the threat of impoverishment and disgrace no longer looms the way it once did, so we no longer can constrain excess financial risk-taking. It’s too soft and cushy a world.

Why don’t we simply eliminate the safety net for clueless or unlucky risk-takers so that losses equal gains overall? That’s a good idea in principle, but it is hard to put into practice. Once a financial crisis arrives, politicians will seek to limit the damage, and that means they will bail out major financial institutions. Had we not passed TARP and related policies, the United States probably would have faced unemployment rates of 25 percent of higher, as in the Great Depression. The political consequences would not have been pretty. Bank bailouts may sound quite interventionist, and indeed they are, but in relative terms they probably were the most libertarian policy we had on tap. It meant big one-time expenses, but, for the most part, it kept government out of the real economy (the General Motors bailout aside).

We probably don’t have any solution to the hazards created by our financial sector, not because plutocrats are preventing our political system from adopting appropriate remedies, but because we don’t know what those remedies are. Yet neither is another crisis immediately upon us. The underlying dynamic favors excess risk-taking, but banks at the current moment fear the scrutiny of regulators and the public and so are playing it fairly safe. They are sitting on money rather than lending it out. The biggest risk today is how few parties will take risks, and, in part, the caution of banks is driving our current protracted economic slowdown. According to this view, the long run will bring another financial crisis once moods pick up and external scrutiny weakens, but that day of reckoning is still some ways off.

Is the overall picture a shame? Yes. Is it distorting resource distribution and productivity in the meantime? Yes. Will it again bring our economy to its knees? Probably. Maybe that’s simply the price of modern society. Income inequality will likely continue to rise and we will search in vain for the appropriate political remedies for our underlying problems.

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

Despite the cowboy outlaw connotations, black-hat services are not illegal, but trafficking in them risks the wrath of Google. The company draws a pretty thick line between techniques it considers deceptive and “white hat” approaches, which are offered by hundreds of consulting firms and are legitimate ways to increase a site’s visibility. Penney’s results were derived from methods on the wrong side of that line, says Mr. Pierce. He described the optimization as the most ambitious attempt to game Google’s search results that he has ever seen.

TO understand the strategy that kept J. C. Penney in the pole position for so many searches, you need to know how Web sites rise to the top of Google’s results. We’re talking, to be clear, about the “organic” results — in other words, the ones that are not paid advertisements. In deriving organic results, Google’s algorithm takes into account dozens of criteria, many of which the company will not discuss.

But it has described one crucial factor in detail: links from one site to another. If you own a Web site, for instance, about Chinese cooking, your site’s Google ranking will improve as other sites link to it. The more links to your site, especially those from other Chinese cooking-related sites, the higher your ranking. In a way, what Google is measuring is your site’s popularity by polling the best-informed online fans of Chinese cooking and counting their links to your site as votes of approval.

But even links that have nothing to do with Chinese cooking can bolster your profile if your site is barnacled with enough of them. And here’s where the strategy that aided Penney comes in. Someone paid to have thousands of links placed on hundreds of sites scattered around the Web, all of which lead directly to JCPenney.com.

Who is that someone? A spokeswoman for J. C. Penney, Darcie Brossart, says it was not Penney.

“J. C. Penney did not authorize, and we were not involved with or aware of, the posting of the links that you sent to us, as it is against our natural search policies,” Ms. Brossart wrote in an e-mail. She added, “We are working to have the links taken down.”

Using an online tool called Open Site Explorer, Mr. Pierce found 2,015 pages with phrases like “casual dresses,” “evening dresses,” “little black dress” or “cocktail dress.” Click on any of these phrases on any of these 2,015 pages, and you are bounced directly to the main page for dresses on JCPenney.com.

Some of the 2,015 pages are on sites related, at least nominally, to clothing. But most are not. The phrase “black dresses” and a Penney link were tacked to the bottom of a site called nuclear.engineeringaddict.com. “Evening dresses” appeared on a site called casino-focus.com. “Cocktail dresses” showed up on bulgariapropertyportal.com. ”Casual dresses” was on a site called elistofbanks.com. “Semi-formal dresses” was pasted, rather incongruously, on usclettermen.org.

Mr. Stevens said that Web site owners, or publishers, as he calls them, get a small fee for each link, and the transaction is handled entirely over the Web. Publishers can reject certain keywords and links — Mr. Stevens said some balked at a lingerie link — but for the most part the system is on a kind of autopilot. A client pays Mr. Stevens and his colleagues for links, which are then farmed out to Web sites. Payment to publishers is handled via PayPal.

You might expect Mr. Stevens to have a certain amount of contempt for Google, given that he spends his professional life finding ways to subvert it. But through the evening he mentioned a few times that he’s in awe of the company, and the quality of its search engine.

“I think we need to make a distinction between two different kinds of searches — informational and commercial,” he said. “If you search ‘cancer,’ that’s an informational search and on those, Google is amazing. But in commercial searches, Google’s results are really polluted. My own personal experience says that the guy with the biggest S.E.O. budget always ranks the highest.”

To Mr. Stevens, S.E.O. is a game, and if you’re not paying black hats, you are losing to rivals with fewer compunctions.

WHY did Google fail to catch a campaign that had been under way for months? One, no less, that benefited a company that Google had already taken action against three times? And one that relied on a collection of Web sites that were not exactly hiding their spamminess? Mr. Cutts emphasized that there are 200 million domain names and a mere 24,000 employees at Google.

The kind of questions asked also marked the occasion as an academic one. Not “Won’t the economy implode if we do this?” or “Wouldn’t free expression rights be eroded if we went down that path?”, but “Would you be willing to follow your argument to its logical conclusion?” or “Doesn’t that amount to just making up the law as you go along?” These questions were continuations of a philosophical conversation that stretches back at least to the beginning of the republic; and while they were illustrated by real-world topics (the pardon power, habeas corpus, the electoral college), the focus was always on the theoretical puzzles of which those topics were disposable examples; they were never the main show.

That's not to say we're helpless. There is at least one climate lesson that we can draw from the recent weather: Whatever happens, prosperity and preparedness help. North Texas's ice storm wreaked havoc and left hundreds of football fans stranded, cold, and angry. But thanks to modern infrastructure, 21st century health care, and stockpiles of magnesium chloride and snow plows, the storm caused no reported deaths and Dallas managed to host the big game on Sunday.

What seems obvious is sometime just wrong.  This of course is why we actually do research.  So why is it that we shouldn't make what seems to be an obvious connection between these papers and recent disasters, as so many have already done?

First, the Min et al. paper seeks to identify a GHG signal in global precipitation over the period 1950-1999.  They focus on one-day and five-day measures of precipitation.  They do not discuss streamflow or damage.  For many years, an upwards trend in precipitation has been documented, and attributed to GHGs, even back to the 1990s (I co-authored a paper on precipitation and floods in 1999 that assumed a human influence on precipitation, PDF), so I am unsure what is actually new in this paper's conclusions.

However, accepting that precipitation has increased and can be attributed in some part to GHG emissions, there have not been shown corresponding increases in streamflow (floods)  or damage. How can this be?  Think of it like this -- Precipitation is to flood damage as wind is to windstorm damage.  It is not enough to say that it has become windier to make a connection to increased windstorm damage -- you need to show a specific increase in those specific wind events that actually cause damage. There are a lot of days that could be windier with no increase in damage; the same goes for precipitation.

My understanding of the literature on streamflow is that there have not been shown increasing peak streamflow commensurate with increases in precipitation, and this is a robust finding across the literature.  For instance, one recent review concludes: Floods are of great concern in many areas of the world, with the last decade seeing major fluvial events in, for example, Asia, Europe and North America. This has focused attention on whether or not these are a result of a changing climate. Rive flows calculated from outputs from global models often suggest that high river flows will increase in a warmer, future climate. However, the future projections are not necessarily in tune with the records collected so far – the observational evidence is more ambiguous. A recent study of trends in long time series of annual maximum river flows at 195 gauging stations worldwide suggests that the majority of these flow records (70%) do not exhibit any statistically significant trends. Trends in the remaining records are almost evenly split between having a positive and a negative direction.

Absent an increase in peak streamflows, it is impossible to connect the dots between increasing precipitation and increasing floods.  There are of course good reasons why a linkage between increasing precipitation and peak streamflow would be difficult to make, such as the seasonality of the increase in rain or snow, the large variability of flooding and the human influence on river systems.  Those difficulties of course translate directly to a difficulty in connecting the effects of increasing GHGs to flood disasters.

Second, the Pall et al. paper seeks to quantify the increased risk of a specific flood event in the UK in 2000 due to greenhouse gas emissions.  It applies a methodology that was previously used with respect to the 2003 European heatwave. Taking the paper at face value, it clearly states that in England and Wales, there has not been an increasing trend in precipitation or floods.  Thus, floods in this region are not a contributor to the global increase in disaster costs.  Further, there has been no increase in Europe in normalized flood losses (PDF).  Thus, Pall et al. paper is focused attribution in the context of on a single event, and not trend detection in the region that it focuses on, much less any broader context.

More generally, the paper utilizes a seasonal forecast model to assess risk probabilities.  Given the performance of seasonal forecast models in actual prediction mode, I would expect many scientists to remain skeptical of this approach to attribution. Of course, if this group can show an improvement in the skill of actual seasonal forecasts by using greenhouse gas emissions as a predictor, they will have a very convincing case.  That is a high hurdle.

In short, the new studies are interesting and add to our knowledge.  But they do not change the state of knowledge related to trends in global disasters and how they might be related to greenhouse gases.  But even so, I expect that many will still want to connect the dots between greenhouse gas emissions and recent floods.  Connecting the dots is fun, but it is not science.

Jessica Weinkle said...

The thing about the nature articles is that Nature itself made the leap from the science findings to damages in the News piece by Q. Schiermeier through the decision to bring up the topic of insurance. (Not to mention that which is symbolically represented merely by the journal’s cover this week). With what I (maybe, naively) believe to be a particularly ballsy move, the article quoted Muir-Wood, an industry scientists. However, what he is quoted as saying is admirably clever. Initially it is stated that Dr. Muir-Wood backs the notion that one cannot put the blame of increased losses on climate change. Then, the article ends with a quote from him, “If there’s evidence that risk is changing, then this is something we need to incorporate in our models.”

This is a very slippery slope and a brilliant double-dog dare. Without doing anything but sitting back and watching the headlines, one can form the argument that “science” supports the remodeling of the hazard risk above the climatological average and is more important then the risks stemming from socioeconomic factors. The reinsurance industry itself has published that socioeconomic factors far outweigh changes in the hazard in concern of losses. The point is (and that which has particularly gotten my knickers in a knot) is that Nature, et al. may wish to consider what it is that they want to accomplish. Is it greater involvement of federal governments in the insurance/reinsurance industry on the premise that climate change is too great a loss risk for private industry alone regardless of the financial burden it imposes? The move of insurance mechanisms into all corners of the earth under the auspices of climate change adaptation? Or simply a move to bolster prominence, regardless of whose back it breaks- including their own, if any of them are proud owners of a home mortgage? How much faith does one have in their own model when they are told that hundreds of millions of dollars in the global economy is being bet against the odds that their models produce?

What Nature says matters to the world; what scientists say matters to the world- whether they care for the responsibility or not. That is after all, the game of fame and fortune (aka prestige).

Unlike the drum language, which was based on spoken language, the optical telegraph was based on written French. Chappe invented an elaborate coding system to translate written messages into optical signals. Chappe had the opposite problem from the drummers. The drummers had a fast transmission system with ambiguous messages. They needed to slow down the transmission to make the messages unambiguous. Chappe had a painfully slow transmission system with redundant messages. The French language, like most alphabetic languages, is highly redundant, using many more letters than are needed to convey the meaning of a message. Chappe’s coding system allowed messages to be transmitted faster. Many common phrases and proper names were encoded by only two optical symbols, with a substantial gain in speed of transmission. The composer and the reader of the message had code books listing the message codes for eight thousand phrases and names. For Napoleon it was an advantage to have a code that was effectively cryptographic, keeping the content of the messages secret from citizens along the route.

After these two historical examples of rapid communication in Africa and France, the rest of Gleick’s book is about the modern development of information technolog

The modern history is dominated by two Americans, Samuel Morse and Claude Shannon. Samuel Morse was the inventor of Morse Code. He was also one of the pioneers who built a telegraph system using electricity conducted through wires instead of optical pointers deployed on towers. Morse launched his electric telegraph in 1838 and perfected the code in 1844. His code used short and long pulses of electric current to represent letters of the alphabet.

Morse was ideologically at the opposite pole from Chappe. He was not interested in secrecy or in creating an instrument of government power. The Morse system was designed to be a profit-making enterprise, fast and cheap and available to everybody. At the beginning the price of a message was a quarter of a cent per letter. The most important users of the system were newspaper correspondents spreading news of local events to readers all over the world. Morse Code was simple enough that anyone could learn it. The system provided no secrecy to the users. If users wanted secrecy, they could invent their own secret codes and encipher their messages themselves. The price of a message in cipher was higher than the price of a message in plain text, because the telegraph operators could transcribe plain text faster. It was much easier to correct errors in plain text than in cipher.

Claude Shannon was the founding father of information theory. For a hundred years after the electric telegraph, other communication systems such as the telephone, radio, and television were invented and developed by engineers without any need for higher mathematics. Then Shannon supplied the theory to understand all of these systems together, defining information as an abstract quantity inherent in a telephone message or a television picture. Shannon brought higher mathematics into the game.

When Shannon was a boy growing up on a farm in Michigan, he built a homemade telegraph system using Morse Code. Messages were transmitted to friends on neighboring farms, using the barbed wire of their fences to conduct electric signals. When World War II began, Shannon became one of the pioneers of scientific cryptography, working on the high-level cryptographic telephone system that allowed Roosevelt and Churchill to talk to each other over a secure channel. Shannon’s friend Alan Turing was also working as a cryptographer at the same time, in the famous British Enigma project that successfully deciphered German military codes. The two pioneers met frequently when Turing visited New York in 1943, but they belonged to separate secret worlds and could not exchange ideas about cryptography.

In 1945 Shannon wrote a paper, “A Mathematical Theory of Cryptography,” which was stamped SECRET and never saw the light of day. He published in 1948 an expurgated version of the 1945 paper with the title “A Mathematical Theory of Communication.” The 1948 version appeared in the Bell System Technical Journal, the house journal of the Bell Telephone Laboratories, and became an instant classic. It is the founding document for the modern science of information. After Shannon, the technology of information raced ahead, with electronic computers, digital cameras, the Internet, and the World Wide Web.

According to Gleick, the impact of information on human affairs came in three installments: first the history, the thousands of years during which people created and exchanged information without the concept of measuring it; second the theory, first formulated by Shannon; third the flood, in which we now live

The event that made the flood plainly visible occurred in 1965, when Gordon Moore stated Moore’s Law. Moore was an electrical engineer, founder of the Intel Corporation, a company that manufactured components for computers and other electronic gadgets. His law said that the price of electronic components would decrease and their numbers would increase by a factor of two every eighteen months. This implied that the price would decrease and the numbers would increase by a factor of a hundred every decade. Moore’s prediction of continued growth has turned out to be astonishingly accurate during the forty-five years since he announced it. In these four and a half decades, the price has decreased and the numbers have increased by a factor of a billion, nine powers of ten. Nine powers of ten are enough to turn a trickle into a flood.

Gordon Moore was in the hardware business, making hardware components for electronic machines, and he stated his law as a law of growth for hardware. But the law applies also to the information that the hardware is designed to embody. The purpose of the hardware is to store and process information. The storage of information is called memory, and the processing of information is called computing. The consequence of Moore’s Law for information is that the price of memory and computing decreases and the available amount of memory and computing increases by a factor of a hundred every decade. The flood of hardware becomes a flood of information.

In 1949, one year after Shannon published the rules of information theory, he drew up a table of the various stores of memory that then existed. The biggest memory in his table was the US Library of Congress, which he estimated to contain one hundred trillion bits of information. That was at the time a fair guess at the sum total of recorded human knowledge. Today a memory disc drive storing that amount of information weighs a few pounds and can be bought for about a thousand dollars. Information, otherwise known as data, pours into memories of that size or larger, in government and business offices and scientific laboratories all over the world. Gleick quotes the computer scientist Jaron Lanier describing the effect of the flood: “It’s as if you kneel to plant the seed of a tree and it grows so fast that it swallows your whole town before you can even rise to your feet.”

On December 8, 2010, Gleick published on the The New York Review’s blog an illuminating essay, “The Information Palace.” It was written too late to be included in his book. It describes the historical changes of meaning of the word “information,” as recorded in the latest quarterly online revision of the Oxford English Dictionary. The word first appears in 1386 a parliamentary report with the meaning “denunciation.” The history ends with the modern usage, “information fatigue,” defined as “apathy, indifference or mental exhaustion arising from exposure to too much information.”

The consequences of the information flood are not all bad. One of the creative enterprises made possible by the flood is Wikipedia, started ten years ago by Jimmy Wales. Among my friends and acquaintances, everybody distrusts Wikipedia and everybody uses it. Distrust and productive use are not incompatible. Wikipedia is the ultimate open source repository of information. Everyone is free to read it and everyone is free to write it. It contains articles in 262 languages written by several million authors. The information that it contains is totally unreliable and surprisingly accurate. It is often unreliable because many of the authors are ignorant or careless. It is often accurate because the articles are edited and corrected by readers who are better informed than the authors

Jimmy Wales hoped when he started Wikipedia that the combination of enthusiastic volunteer writers with open source information technology would cause a revolution in human access to knowledge. The rate of growth of Wikipedia exceeded his wildest dreams. Within ten years it has become the biggest storehouse of information on the planet and the noisiest battleground of conflicting opinions. It illustrates Shannon’s law of reliable communication. Shannon’s law says that accurate transmission of information is possible in a communication system with a high level of noise. Even in the noisiest system, errors can be reliably corrected and accurate information transmitted, provided that the transmission is sufficiently redundant. That is, in a nutshell, how Wikipedia works.

The information flood has also brought enormous benefits to science. The public has a distorted view of science, because children are taught in school that science is a collection of firmly established truths. In fact, science is not a collection of truths. It is a continuing exploration of mysteries. Wherever we go exploring in the world around us, we find mysteries. Our planet is covered by continents and oceans whose origin we cannot explain. Our atmosphere is constantly stirred by poorly understood disturbances that we call weather and climate. The visible matter in the universe is outweighed by a much larger quantity of dark invisible matter that we do not understand at all. The origin of life is a total mystery, and so is the existence of human consciousness. We have no clear idea how the electrical discharges occurring in nerve cells in our brains are connected with our feelings and desires and actions.

Even physics, the most exact and most firmly established branch of science, is still full of mysteries. We do not know how much of Shannon’s theory of information will remain valid when quantum devices replace classical electric circuits as the carriers of information. Quantum devices may be made of single atoms or microscopic magnetic circuits. All that we know for sure is that they can theoretically do certain jobs that are beyond the reach of classical devices. Quantum computing is still an unexplored mystery on the frontier of information theory. Science is the sum total of a great multitude of mysteries. It is an unending argument between a great multitude of voices. It resembles Wikipedia much more than it resembles the Encyclopaedia Britannica.

The rapid growth of the flood of information in the last ten years made Wikipedia possible, and the same flood made twenty-first-century science possible. Twenty-first-century science is dominated by huge stores of information that we call databases. The information flood has made it easy and cheap to build databases. One example of a twenty-first-century database is the collection of genome sequences of living creatures belonging to various species from microbes to humans. Each genome contains the complete genetic information that shaped the creature to which it belongs. The genome data-base is rapidly growing and is available for scientists all over the world to explore. Its origin can be traced to the year 1939, when Shannon wrote his Ph.D. thesis with the title “An Algebra for Theoretical Genetics.

Shannon was then a graduate student in the mathematics department at MIT. He was only dimly aware of the possible physical embodiment of genetic information. The true physical embodiment of the genome is the double helix structure of DNA molecules, discovered by Francis Crick and James Watson fourteen years later. In 1939 Shannon understood that the basis of genetics must be information, and that the information must be coded in some abstract algebra independent of its physical embodiment. Without any knowledge of the double helix, he could not hope to guess the detailed structure of the genetic code. He could only imagine that in some distant future the genetic information would be decoded and collected in a giant database that would define the total diversity of living creatures. It took only sixty years for his dream to come true.

In the twentieth century, genomes of humans and other species were laboriously decoded and translated into sequences of letters in computer memories. The decoding and translation became cheaper and faster as time went on, the price decreasing and the speed increasing according to Moore’s Law. The first human genome took fifteen years to decode and cost about a billion dollars. Now a human genome can be decoded in a few weeks and costs a few thousand dollars. Around the year 2000, a turning point was reached, when it became cheaper to produce genetic information than to understand it. Now we can pass a piece of human DNA through a machine and rapidly read out the genetic information, but we cannot read out the meaning of the information. We shall not fully understand the information until we understand in detail the processes of embryonic development that the DNA orchestrated to make us what we are.

The explosive growth of information in our human society is a part of the slower growth of ordered structures in the evolution of life as a whole. Life has for billions of years been evolving with organisms and ecosystems embodying increasing amounts of information. The evolution of life is a part of the evolution of the universe, which also evolves with increasing amounts of information embodied in ordered structures, galaxies and stars and planetary systems. In the living and in the nonliving world, we see a growth of order, starting from the featureless and uniform gas of the early universe and producing the magnificent diversity of weird objects that we see in the sky and in the rain forest. Everywhere around us, wherever we look, we see evidence of increasing order and increasing information. The technology arising from Shannon’s discoveries is only a local acceleration of the natural growth of information.

. Lord Kelvin, one of the leading physicists of that time, promoted the heat death dogma, predicting that the flow of heat from warmer to cooler objects will result in a decrease of temperature differences everywhere, until all temperatures ultimately become equal. Life needs temperature differences, to avoid being stifled by its waste heat. So life will disappear

Thanks to the discoveries of astronomers in the twentieth century, we now know that the heat death is a myth. The heat death can never happen, and there is no paradox. The best popular account of the disappearance of the paradox is a chapter, “How Order Was Born of Chaos,” in the book Creation of the Universe, by Fang Lizhi and his wife Li Shuxian.2 Fang Lizhi is doubly famous as a leading Chinese astronomer and a leading political dissident. He is now pursuing his double career at the University of Arizona.

The belief in a heat death was based on an idea that I call the cooking rule. The cooking rule says that a piece of steak gets warmer when we put it on a hot grill. More generally, the rule says that any object gets warmer when it gains energy, and gets cooler when it loses energy. Humans have been cooking steaks for thousands of years, and nobody ever saw a steak get colder while cooking on a fire. The cooking rule is true for objects small enough for us to handle. If the cooking rule is always true, then Lord Kelvin’s argument for the heat death is correct.

the cooking rule is not true for objects of astronomical size, for which gravitation is the dominant form of energy. The sun is a familiar example. As the sun loses energy by radiation, it becomes hotter and not cooler. Since the sun is made of compressible gas squeezed by its own gravitation, loss of energy causes it to become smaller and denser, and the compression causes it to become hotter. For almost all astronomical objects, gravitation dominates, and they have the same unexpected behavior. Gravitation reverses the usual relation between energy and temperature. In the domain of astronomy, when heat flows from hotter to cooler objects, the hot objects get hotter and the cool objects get cooler. As a result, temperature differences in the astronomical universe tend to increase rather than decrease as time goes on. There is no final state of uniform temperature, and there is no heat death. Gravitation gives us a universe hospitable to life. Information and order can continue to grow for billions of years in the future, as they have evidently grown in the past.

The vision of the future as an infinite playground, with an unending sequence of mysteries to be understood by an unending sequence of players exploring an unending supply of information, is a glorious vision for scientists. Scientists find the vision attractive, since it gives them a purpose for their existence and an unending supply of jobs. The vision is less attractive to artists and writers and ordinary people. Ordinary people are more interested in friends and family than in science. Ordinary people may not welcome a future spent swimming in an unending flood of information.

A darker view of the information-dominated universe was described in a famous story, “The Library of Babel,” by Jorge Luis Borges in 1941.3 Borges imagined his library, with an infinite array of books and shelves and mirrors, as a metaphor for the universe.

Gleick’s book has an epilogue entitled “The Return of Meaning,” expressing the concerns of people who feel alienated from the prevailing scientific culture. The enormous success of information theory came from Shannon’s decision to separate information from meaning. His central dogma, “Meaning is irrelevant,” declared that information could be handled with greater freedom if it was treated as a mathematical abstraction independent of meaning. The consequence of this freedom is the flood of information in which we are drowning. The immense size of modern databases gives us a feeling of meaninglessness. Information in such quantities reminds us of Borges’s library extending infinitely in all directions. It is our task as humans to bring meaning back into this wasteland. As finite creatures who think and feel, we can create islands of meaning in the sea of information. Gleick ends his book with Borges’s image of the human condition:We walk the corridors, searching the shelves and rearranging them, looking for lines of meaning amid leagues of cacophony and incoherence, reading the history of the past and of the future, collecting our thoughts and collecting the thoughts of others, and every so often glimpsing mirrors, in which we may recognize creatures of the information.

Universities are also being used as flag carriers for national economic ambitions - driving forward modernisation plans. For some it's been a spectacularly fast rise. According to the OECD, in the 1960s South Korea had a similar national wealth to Afghanistan. Now it tops international education league tables and has some of the highest-rated universities in the world. The Pohang University of Science and Technology in South Korea was only founded in 1986 - and is now in the top 30 of the Times Higher's global league table, elbowing past many ancient and venerable institutions. It also wants to compete on an international stage so the university has decided that all its graduate programmes should be taught in English rather than Korean.

governments want to use universities to upgrade their workforce and develop hi-tech industries.

"Universities are being seen as a key to the new economies, they're trying to grow the knowledge economy by building a base in universities," says Professor Altbach. Families, from rural China to eastern Europe, are also seeing university as a way of helping their children to get higher-paid jobs. A growing middle-class in India is pushing an expansion in places. Universities also stand to gain from recruiting overseas. "Universities in the rich countries are making big bucks," he says. This international trade is worth at least $50 billion a year, he estimates, the lion's share currently being claimed by the US.

Technology, much of it hatched on university campuses, is also changing higher education and blurring national boundaries.

It raises many questions too. What are the expectations of this Facebook generation? They might have degrees and be able to see what is happening on the other side of the world, but will there be enough jobs to match their ambitions? Who is going to pay for such an expanded university system? And what about those who will struggle to afford a place?

The success of the US system is not just about funding, says Professor Altbach. It's also because it's well run and research is effectively organised. "Of course there are lots of lousy institutions in the US, but overall the system works well." Continue reading the main story “Start Quote Developed economies are already highly dependent on universities and if anything that reliance will increase” End Quote David Willetts UK universities minister The status of the US system has been bolstered by the link between its university research and developing hi-tech industries. Icons of the internet-age such Google and Facebook grew out of US campuses.

all of this is for the purposes of infiltration, data mining, and (here's the one that really worries me) ganging up on bloggers, commenters  and otherwise "real" people to smear enemies and distort the truth.

CEO of HB Gary's Federal subsidiary, to several of his colleagues to present to clients: To build this capability we will create a set of personas on twitter,‭ ‬blogs,‭ ‬forums,‭ ‬buzz,‭ ‬and myspace under created names that fit the profile‭ (‬satellitejockey,‭ ‬hack3rman,‭ ‬etc‭)‬.‭  ‬These accounts are maintained and updated automatically through RSS feeds,‭ ‬retweets,‭ ‬and linking together social media commenting between platforms.‭  ‬With a pool of these accounts to choose from,‭ ‬once you have a real name persona you create a Facebook and LinkedIn account using the given name,‭ ‬lock those accounts down and link these accounts to a selected‭ ‬#‭ ‬of previously created social media accounts,‭ ‬automatically pre-aging the real accounts.

one of the team spells out how automation can work so one person can be many personas: Using the assigned social media accounts we can automate the posting of content that is relevant to the persona.  In this case there are specific social media strategy website RSS feeds we can subscribe to and then repost content on twitter with the appropriate hashtags.  In fact using hashtags and gaming some location based check-in services we can make it appear as if a persona was actually at a conference and introduce himself/herself to key individuals as part of the exercise, as one example.  There are a variety of social media tricks we can use to add a level of realness to all fictitious personas

It goes far beyond the mere ability for a government stooge, corporation or PR firm to hire people to post on sites like this one. They are talking about creating  the illusion of consensus. And consensus is a powerful persuader. What has more effect, one guy saying BP is not at fault? Or 20 people saying it? For the weak minded, the number can make all the difference.

UPDATE: From another email, I found a  government solicitation for this "Persona Management Software". This confirms that in fact, the US Gov. is attempting to use this kind of technology. But it appears from the solicitation it is contracted for use in foreign theaters like Afghanistan and Iraq. I can't imagine why this is posted on an open site. And whenthis was discovered by a couple of HB Gary staffers, they weren't too happy about it either:

Morris also makes heavy use of the “taking a quote out of context” strategy favored by creationists. His quotes are often from secondary sources and are incomplete.

A more scholarly (i.e. intellectually honest) approach would be to cite actual evidence to support a point. If you are going to cite an authority, then make sure the quote is relevant, in context, and complete.

And even better, cite a number of sources to show that the opinion is representative. Rather we get single, partial, and often outdated quotes without context.

(nature is not, it turns out, cleanly divided into “kinds”, which have no operational definition). He also repeats this canard: Such variation is often called microevolution, and these minor horizontal (or downward) changes occur fairly often, but such changes are not true “vertical” evolution. This is the microevolution/macroevolution false dichotomy. It is only “often called” this by creationists – not by actual evolutionary scientists. There is no theoretical or empirical division between macro and micro evolution. There is just evolution, which can result in the full spectrum of change from minor tweaks to major changes.

Morris wonders why there are no “dats” – dog-cat transitional species. He misses the hierarchical nature of evolution. As evolution proceeds, and creatures develop a greater and greater evolutionary history behind them, they increasingly are committed to their body plan. This results in a nestled hierarchy of groups – which is reflected in taxonomy (the naming scheme of living things).

once our distant ancestors developed the basic body plan of chordates, they were committed to that body plan. Subsequent evolution resulted in variations on that plan, each of which then developed further variations, etc. But evolution cannot go backward, undo evolutionary changes and then proceed down a different path. Once an evolutionary line has developed into a dog, evolution can produce variations on the dog, but it cannot go backwards and produce a cat.

Stephen J. Gould described this distinction as the difference between disparity and diversity. Disparity (the degree of morphological difference) actually decreases over evolutionary time, as lineages go extinct and the surviving lineages are committed to fewer and fewer basic body plans. Meanwhile, diversity (the number of variations on a body plan) within groups tends to increase over time.

the kind of evolutionary changes that were happening in the past, when species were relatively undifferentiated (compared to contemporary species) is indeed not happening today. Modern multi-cellular life has 600 million years of evolutionary history constraining their future evolution – which was not true of species at the base of the evolutionary tree. But modern species are indeed still evolving.

Here is a list of research documenting observed instances of speciation. The list is from 1995, and there are more recent examples to add to the list. Here are some more. And here is a good list with references of more recent cases.

Next Morris tries to convince the reader that there is no evidence for evolution in the past, focusing on the fossil record. He repeats the false claim (again, which I already dealt with) that there are no transitional fossils: Even those who believe in rapid evolution recognize that a considerable number of generations would be required for one distinct “kind” to evolve into another more complex kind. There ought, therefore, to be a considerable number of true transitional structures preserved in the fossils — after all, there are billions of non-transitional structures there! But (with the exception of a few very doubtful creatures such as the controversial feathered dinosaurs and the alleged walking whales), they are not there.

I deal with this question at length here, pointing out that there are numerous transitional fossils for the evolution of terrestrial vertebrates, mammals, whales, birds, turtles, and yes – humans from ape ancestors. There are many more examples, these are just some of my favorites.

Much of what follows (as you can see it takes far more space to correct the lies and distortions of Morris than it did to create them) is classic denialism – misinterpreting the state of the science, and confusing lack of information about the details of evolution with lack of confidence in the fact of evolution. Here are some examples – he quotes Niles Eldridge: “It is a simple ineluctable truth that virtually all members of a biota remain basically stable, with minor fluctuations, throughout their durations. . . .“ So how do evolutionists arrive at their evolutionary trees from fossils of organisms which didn’t change during their durations? Beware the “….” – that means that meaningful parts of the quote are being omitted. I happen to have the book (The Pattern of Evolution) from which Morris mined that particular quote. Here’s the rest of it: (Remember, by “biota” we mean the commonly preserved plants and animals of a particular geological interval, which occupy regions often as large as Roger Tory Peterson’s “eastern” region of North American birds.) And when these systems change – when the older species disappear, and new ones take their place – the change happens relatively abruptly and in lockstep fashion.”

Eldridge was one of the authors (with Gould) of punctuated equilibrium theory. This states that, if you look at the fossil record, what we see are species emerging, persisting with little change for a while, and then disappearing from the fossil record. They theorize that most species most of the time are at equilibrium with their environment, and so do not change much. But these periods of equilibrium are punctuated by disequilibrium – periods of change when species will have to migrate, evolve, or go extinct.

This does not mean that speciation does not take place. And if you look at the fossil record we see a pattern of descendant species emerging from ancestor species over time – in a nice evolutionary pattern. Morris gives a complete misrepresentation of Eldridge’s point – once again we see intellectual dishonesty in his methods of an astounding degree.

Regarding the atheism = religion comment, it reminds me of a great analogy that I first heard on twitter from Evil Eye. (paraphrase) “those that say atheism is a religion, is like saying ‘not collecting stamps’ is a hobby too.”

Morris next tackles the genetic evidence, writing: More often is the argument used that similar DNA structures in two different organisms proves common evolutionary ancestry. Neither argument is valid. There is no reason whatever why the Creator could not or would not use the same type of genetic code based on DNA for all His created life forms. This is evidence for intelligent design and creation, not evolution.

Here is an excellent summary of the multiple lines of molecular evidence for evolution. Basically, if we look at the sequence of DNA, the variations in trinucleotide codes for amino acids, and amino acids for proteins, and transposons within DNA we see a pattern that can only be explained by evolution (or a mischievous god who chose, for some reason, to make life look exactly as if it had evolved – a non-falsifiable notion).

The genetic code is essentially comprised of four letters (ACGT for DNA), and every triplet of three letters equates to a specific amino acid. There are 64 (4^3) possible three letter combinations, and 20 amino acids. A few combinations are used for housekeeping, like a code to indicate where a gene stops, but the rest code for amino acids. There are more combinations than amino acids, so most amino acids are coded for by multiple combinations. This means that a mutation that results in a one-letter change might alter from one code for a particular amino acid to another code for the same amino acid. This is called a silent mutation because it does not result in any change in the resulting protein.

It also means that there are very many possible codes for any individual protein. The question is – which codes out of the gazillions of possible codes do we find for each type of protein in different species. If each “kind” were created separately there would not need to be any relationship. Each kind could have it’s own variation, or they could all be identical if they were essentially copied (plus any mutations accruing since creation, which would be minimal). But if life evolved then we would expect that the exact sequence of DNA code would be similar in related species, but progressively different (through silent mutations) over evolutionary time.

This is precisely what we find – in every protein we have examined. This pattern is necessary if evolution were true. It cannot be explained by random chance (the probability is absurdly tiny – essentially zero). And it makes no sense from a creationist perspective. This same pattern (a branching hierarchy) emerges when we look at amino acid substitutions in proteins and other aspects of the genetic code.

Morris goes for the second law of thermodynamics again – in the exact way that I already addressed. He responds to scientists correctly pointing out that the Earth is an open system, by writing: This naive response to the entropy law is typical of evolutionary dissimulation. While it is true that local order can increase in an open system if certain conditions are met, the fact is that evolution does not meet those conditions. Simply saying that the earth is open to the energy from the sun says nothing about how that raw solar heat is converted into increased complexity in any system, open or closed. The fact is that the best known and most fundamental equation of thermodynamics says that the influx of heat into an open system will increase the entropy of that system, not decrease it. All known cases of decreased entropy (or increased organization) in open systems involve a guiding program of some sort and one or more energy conversion mechanisms.

Energy has to be transformed into a usable form in order to do the work necessary to decrease entropy. That’s right. That work is done by life. Plants take solar energy (again – I’m not sure what “raw solar heat” means) and convert it into food. That food fuels the processes of life, which include development and reproduction. Evolution emerges from those processes- therefore the conditions that Morris speaks of are met.

But Morris next makes a very confused argument: Evolution has neither of these. Mutations are not “organizing” mechanisms, but disorganizing (in accord with the second law). They are commonly harmful, sometimes neutral, but never beneficial (at least as far as observed mutations are concerned). Natural selection cannot generate order, but can only “sieve out” the disorganizing mutations presented to it, thereby conserving the existing order, but never generating new order.

The notion that evolution (as if it’s a thing) needs to use energy is hopelessly confused. Evolution is a process that emerges from the system of life – and life certainly can use solar energy to decrease its entropy, and by extension the entropy of the biosphere. Morris slips into what is often presented as an information argument.  (Yet again – already dealt with. The pattern here is that we are seeing a shuffling around of the same tired creationists arguments.) It is first not true that most mutations are harmful. Many are silent, and many of those that are not silent are not harmful. They may be neutral, they may be a mixed blessing, and their relative benefit vs harm is likely to be situational. They may be fatal. And they also may be simply beneficial.

Morris finishes with a long rambling argument that evolution is religion. Evolution is promoted by its practitioners as more than mere science. Evolution is promulgated as an ideology, a secular religion — a full-fledged alternative to Christianity, with meaning and morality . . . . Evolution is a religion. This was true of evolution in the beginning, and it is true of evolution still today. Morris ties evolution to atheism, which, he argues, makes it a religion. This assumes, of course, that atheism is a religion. That depends on how you define atheism and how you define religion – but it is mostly wrong. Atheism is a lack of belief in one particular supernatural claim – that does not qualify it as a religion.

But mutations are not “disorganizing” – that does not even make sense. It seems to be based on a purely creationist notion that species are in some privileged perfect state, and any mutation can only take them farther from that perfection. For those who actually understand biology, life is a kluge of compromises and variation. Mutations are mostly lateral moves from one chaotic state to another. They are not directional. But they do provide raw material, variation, for natural selection. Natural selection cannot generate variation, but it can select among that variation to provide differential survival. This is an old game played by creationists – mutations are not selective, and natural selection is not creative (does not increase variation). These are true but irrelevant, because mutations increase variation and information, and selection is a creative force that results in the differential survival of better adapted variation.

How can we assess the competence of a scientist? Past performance is, realistically, the only way to judge future performance. Past performance can only be assessed by looking at their publications. Were they in a similar area? Are they considered significant? Are they numerous? Curiously, though, the second question is also answered by looking at publications—if a topic is considered significant, then there will be lots of publications in that area, and those publications will be of more general interest, and so end up in higher ranking journals.

So we end up in the situation that the editors of major journals are in the position to influence the direction of scientific funding, meaning that there is a huge incentive for everyone to make damn sure that their work ends up in Science or Nature. But why are Science, Nature, and PNAS considered the place to put significant work? Why isn't a new optical phenomena, published in Optics Express, as important as a new optical phenomena published in Science?

The big three try to be general; they will, in principle, publish reports from any discipline, and they anticipate readership from a range of disciplines. This explicit generality means that the scientific results must not only be of general interest, but also highly significant. The remaining journals become more specialized, covering perhaps only physics, or optics, or even just optical networking. However, they all claim to only publish work that is highly original in nature.

Are standards really so different? Naturally, the more specialized a journal is, the fewer people it appeals to. However, the major difference in determining originality is one of degree and referee. A more specialized journal has more detailed articles, so the differences between experiments stand out more obviously, while appealing to general interest changes the emphasis of the article away from details toward broad conclusions.

as the audience becomes broader, more technical details get left by the wayside. Note that none of the gene sequences published in Science have the actual experimental and analysis details. What ends up published is really a broad-brush description of the work, with the important details either languishing as supplemental information, or even published elsewhere, in a more suitable journal. Yet, the high profile paper will get all the citations, while the more detailed—the unkind would say accurate—description of the work gets no attention.

And that is how journals are ranked. Count the number of citations for each journal per volume, run it through a magic number generator, and the impact factor jumps out (make your checks out to ISI Thomson please). That leaves us with the following formula: grants require high impact publications, high impact publications need citations, and that means putting research in a journal that gets lots of citations. Grants follow the concepts that appear to be currently significant, and that's decided by work that is published in high impact journals.

This system would be fine if it did not ignore the fact that performing science and reporting scientific results are two very different skills, and not everyone has both in equal quantity. The difference between a Nature-worthy finding and a not-Nature-worthy finding is often in the quality of the writing. How skillfully can I relate this bit of research back to general or topical interests? It really is this simple. Over the years, I have seen quite a few physics papers with exaggerated claims of significance (or even results) make it into top flight journals, and the only differences I can see between those works and similar works published elsewhere is that the presentation and level of detail are different.

articles from the big three are much easier to cover on Nobel Intent than articles from, say Physical Review D. Nevertheless, when we do cover them, sometimes the researchers suddenly realize that they could have gotten a lot more mileage out of their work. It changes their approach to reporting their results, which I see as evidence that writing skill counts for as much as scientific quality.

If that observation is generally true, then it raises questions about the whole process of evaluating a researcher's competence and a field's significance, because good writers corrupt the process by publishing less significant work in journals that only publish significant findings. In fact, I think it goes further than that, because Science, Nature, and PNAS actively promote themselves as scientific compasses. Want to find the most interesting and significant research? Read PNAS.

The publishers do this by extensively publicizing science that appears in their own journals. Their news sections primarily summarize work published in the same issue of the same magazine. This lets them create a double-whammy of scientific significance—not only was the work published in Nature, they also summarized it in their News and Views section.

Very few of the other journals do this. I don't get early access to the Physical Review series, even though I love reporting from them. In fact, until this year, they didn't even highlight interesting papers for their own readers. This makes it incredibly hard for a science reporter to cover science outside of the major journals. The knock-on effect is that Applied Physics Letters never appears in the news, which means you can't evaluate recent news coverage to figure out what's of general interest, leaving you with... well, the big three journals again, which mostly report on themselves. On the other hand, if a particular scientific topic does start to receive some press attention, it is much more likely that similar work will suddenly be acceptable in the big three journals.

That said, I should point out that judging the significance of scientific work is a process fraught with difficulty. Why do you think it takes around 10 years from the publication of first results through to obtaining a Nobel Prize? Because it can take that long for the implications of the results to sink in—or, more commonly, sink without trace.

I don't think that we can reasonably expect journal editors and peer reviewers to accurately assess the significance (general or otherwise) of a new piece of research. There are, of course, exceptions: the first genome sequences, the first observation that the rate of the expansion of the universe is changing. But the point is that these are exceptions, and most work's significance is far more ambiguous, and even goes unrecognized (or over-celebrated) by scientists in the field.

The conclusion is that the top three journals are significantly gamed by scientists who are trying to get ahead in their careers—citations always lag a few years behind, so a PNAS paper with less than ten citations can look good for quite a few years, even compared to an Optics Letters with 50 citations. The top three journals overtly encourage this, because it is to their advantage if everyone agrees that they are the source of the most interesting science. Consequently, scientists who are more honest in self-assessing their work, or who simply aren't word-smiths, end up losing out.

scientific competence should not be judged by how many citations the author's work has received or where it was published. Instead, we should consider using a mathematical graph analysis to look at the networks of publications and citations, which should help us judge how central to a field a particular researcher is. This would have the positive influence of a publication mattering less than who thought it was important.

Science and Nature should either eliminate their News and Views section, or implement a policy of not reporting on their own articles. This would open up one of the major sources of "science news for scientists" to stories originating in other journals.