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Suppose you want to say, "Bush read Chomsky's latest book." Let's focus on just the verb, "read." To say this sentence in English, we have to mark the verb for tense; in this case, we have to pronounce it like "red" and not like "reed." In Indonesian you need not (in fact, you can't) alter the verb to mark tense. In Russian you would have to alter the verb to indicate tense and gender. So if it was Laura Bush who did the reading, you'd use a different form of the verb than if it was George. In Russian you'd also have to include in the verb information about completion. If George read only part of the book, you'd use a different form of the verb than if he'd diligently plowed through the whole thing. In Turkish you'd have to include in the verb how you acquired this information: if you had witnessed this unlikely event with your own two eyes, you'd use one verb form, but if you had simply read or heard about it, or inferred it from something Bush said, you'd use a different verb form.

Clearly, languages require different things of their speakers. Does this mean that the speakers think differently about the world? Do English, Indonesian, Russian, and Turkish speakers end up attending to, partitioning, and remembering their experiences differently just because they speak different languages?

For some scholars, the answer to these questions has been an obvious yes. Just look at the way people talk, they might say. Certainly, speakers of different languages must attend to and encode strikingly different aspects of the world just so they can use their language properly. Scholars on the other side of the debate don't find the differences in how people talk convincing. All our linguistic utterances are sparse, encoding only a small part of the information we have available. Just because English speakers don't include the same information in their verbs that Russian and Turkish speakers do doesn't mean that English speakers aren't paying attention to the same things; all it means is that they're not talking about them. It's possible that everyone thinks the same way, notices the same things, but just talks differently.

Believers in cross-linguistic differences counter that everyone does not pay attention to the same things: if everyone did, one might think it would be easy to learn to speak other languages. Unfortunately, learning a new language (especially one not closely related to those you know) is never easy; it seems to require paying attention to a new set of distinctions. Whether it's distinguishing modes of being in Spanish, evidentiality in Turkish, or aspect in Russian, learning to speak these languages requires something more than just learning vocabulary: it requires paying attention to the right things in the world so that you have the correct information to include in what you say.

Follow me to Pormpuraaw, a small Aboriginal community on the western edge of Cape York, in northern Australia. I came here because of the way the locals, the Kuuk Thaayorre, talk about space. Instead of words like "right," "left," "forward," and "back," which, as commonly used in English, define space relative to an observer, the Kuuk Thaayorre, like many other Aboriginal groups, use cardinal-direction terms — north, south, east, and west — to define space.1 This is done at all scales, which means you have to say things like "There's an ant on your southeast leg" or "Move the cup to the north northwest a little bit." One obvious consequence of speaking such a language is that you have to stay oriented at all times, or else you cannot speak properly. The normal greeting in Kuuk Thaayorre is "Where are you going?" and the answer should be something like " Southsoutheast, in the middle distance." If you don't know which way you're facing, you can't even get past "Hello."

The result is a profound difference in navigational ability and spatial knowledge between speakers of languages that rely primarily on absolute reference frames (like Kuuk Thaayorre) and languages that rely on relative reference frames (like English).2 Simply put, speakers of languages like Kuuk Thaayorre are much better than English speakers at staying oriented and keeping track of where they are, even in unfamiliar landscapes or inside unfamiliar buildings. What enables them — in fact, forces them — to do this is their language. Having their attention trained in this way equips them to perform navigational feats once thought beyond human capabilities. Because space is such a fundamental domain of thought, differences in how people think about space don't end there. People rely on their spatial knowledge to build other, more complex, more abstract representations. Representations of such things as time, number, musical pitch, kinship relations, morality, and emotions have been shown to depend on how we think about space. So if the Kuuk Thaayorre think differently about space, do they also think differently about other things, like time? This is what my collaborator Alice Gaby and I came to Pormpuraaw to find out.

To test this idea, we gave people sets of pictures that showed some kind of temporal progression (e.g., pictures of a man aging, or a crocodile growing, or a banana being eaten). Their job was to arrange the shuffled photos on the ground to show the correct temporal order. We tested each person in two separate sittings, each time facing in a different cardinal direction. If you ask English speakers to do this, they'll arrange the cards so that time proceeds from left to right. Hebrew speakers will tend to lay out the cards from right to left, showing that writing direction in a language plays a role.3 So what about folks like the Kuuk Thaayorre, who don't use words like "left" and "right"? What will they do? The Kuuk Thaayorre did not arrange the cards more often from left to right than from right to left, nor more toward or away from the body. But their arrangements were not random: there was a pattern, just a different one from that of English speakers. Instead of arranging time from left to right, they arranged it from east to west. That is, when they were seated facing south, the cards went left to right. When they faced north, the cards went from right to left. When they faced east, the cards came toward the body and so on. This was true even though we never told any of our subjects which direction they faced. The Kuuk Thaayorre not only knew that already (usually much better than I did), but they also spontaneously used this spatial orientation to construct their representations of time.

I have described how languages shape the way we think about space, time, colors, and objects. Other studies have found effects of language on how people construe events, reason about causality, keep track of number, understand material substance, perceive and experience emotion, reason about other people's minds, choose to take risks, and even in the way they choose professions and spouses.8 Taken together, these results show that linguistic processes are pervasive in most fundamental domains of thought, unconsciously shaping us from the nuts and bolts of cognition and perception to our loftiest abstract notions and major life decisions. Language is central to our experience of being human, and the languages we speak profoundly shape the way we think, the way we see the world, the way we live our lives.

The fact that even quirks of grammar, such as grammatical gender, can affect our thinking is profound. Such quirks are pervasive in language; gender, for example, applies to all nouns, which means that it is affecting how people think about anything that can be designated by a noun.

How does an artist decide whether death, say, or time should be painted as a man or a woman? It turns out that in 85 percent of such personifications, whether a male or female figure is chosen is predicted by the grammatical gender of the word in the artist's native language. So, for example, German painters are more likely to paint death as a man, whereas Russian painters are more likely to paint death as a woman.

Does treating chairs as masculine and beds as feminine in the grammar make Russian speakers think of chairs as being more like men and beds as more like women in some way? It turns out that it does. In one study, we asked German and Spanish speakers to describe objects having opposite gender assignment in those two languages. The descriptions they gave differed in a way predicted by grammatical gender. For example, when asked to describe a "key" — a word that is masculine in German and feminine in Spanish — the German speakers were more likely to use words like "hard," "heavy," "jagged," "metal," "serrated," and "useful," whereas Spanish speakers were more likely to say "golden," "intricate," "little," "lovely," "shiny," and "tiny." To describe a "bridge," which is feminine in German and masculine in Spanish, the German speakers said "beautiful," "elegant," "fragile," "peaceful," "pretty," and "slender," and the Spanish speakers said "big," "dangerous," "long," "strong," "sturdy," and "towering." This was true even though all testing was done in English, a language without grammatical gender. The same pattern of results also emerged in entirely nonlinguistic tasks (e.g., rating similarity between pictures). And we can also show that it is aspects of language per se that shape how people think: teaching English speakers new grammatical gender systems influences mental representations of objects in the same way it does with German and Spanish speakers. Apparently even small flukes of grammar, like the seemingly arbitrary assignment of gender to a noun, can have an effect on people's ideas of concrete objects in the world.

Even basic aspects of time perception can be affected by language. For example, English speakers prefer to talk about duration in terms of length (e.g., "That was a short talk," "The meeting didn't take long"), while Spanish and Greek speakers prefer to talk about time in terms of amount, relying more on words like "much" "big", and "little" rather than "short" and "long" Our research into such basic cognitive abilities as estimating duration shows that speakers of different languages differ in ways predicted by the patterns of metaphors in their language. (For example, when asked to estimate duration, English speakers are more likely to be confused by distance information, estimating that a line of greater length remains on the test screen for a longer period of time, whereas Greek speakers are more likely to be confused by amount, estimating that a container that is fuller remains longer on the screen.)

An important question at this point is: Are these differences caused by language per se or by some other aspect of culture? Of course, the lives of English, Mandarin, Greek, Spanish, and Kuuk Thaayorre speakers differ in a myriad of ways. How do we know that it is language itself that creates these differences in thought and not some other aspect of their respective cultures? One way to answer this question is to teach people new ways of talking and see if that changes the way they think. In our lab, we've taught English speakers different ways of talking about time. In one such study, English speakers were taught to use size metaphors (as in Greek) to describe duration (e.g., a movie is larger than a sneeze), or vertical metaphors (as in Mandarin) to describe event order. Once the English speakers had learned to talk about time in these new ways, their cognitive performance began to resemble that of Greek or Mandarin speakers. This suggests that patterns in a language can indeed play a causal role in constructing how we think.6 In practical terms, it means that when you're learning a new language, you're not simply learning a new way of talking, you are also inadvertently learning a new way of thinking. Beyond abstract or complex domains of thought like space and time, languages also meddle in basic aspects of visual perception — our ability to distinguish colors, for example. Different languages divide up the color continuum differently: some make many more distinctions between colors than others, and the boundaries often don't line up across languages.

To test whether differences in color language lead to differences in color perception, we compared Russian and English speakers' ability to discriminate shades of blue. In Russian there is no single word that covers all the colors that English speakers call "blue." Russian makes an obligatory distinction between light blue (goluboy) and dark blue (siniy). Does this distinction mean that siniy blues look more different from goluboy blues to Russian speakers? Indeed, the data say yes. Russian speakers are quicker to distinguish two shades of blue that are called by the different names in Russian (i.e., one being siniy and the other being goluboy) than if the two fall into the same category. For English speakers, all these shades are still designated by the same word, "blue," and there are no comparable differences in reaction time. Further, the Russian advantage disappears when subjects are asked to perform a verbal interference task (reciting a string of digits) while making color judgments but not when they're asked to perform an equally difficult spatial interference task (keeping a novel visual pattern in memory). The disappearance of the advantage when performing a verbal task shows that language is normally involved in even surprisingly basic perceptual judgments — and that it is language per se that creates this difference in perception between Russian and English speakers.

What it means for a language to have grammatical gender is that words belonging to different genders get treated differently grammatically and words belonging to the same grammatical gender get treated the same grammatically. Languages can require speakers to change pronouns, adjective and verb endings, possessives, numerals, and so on, depending on the noun's gender. For example, to say something like "my chair was old" in Russian (moy stul bil' stariy), you'd need to make every word in the sentence agree in gender with "chair" (stul), which is masculine in Russian. So you'd use the masculine form of "my," "was," and "old." These are the same forms you'd use in speaking of a biological male, as in "my grandfather was old." If, instead of speaking of a chair, you were speaking of a bed (krovat'), which is feminine in Russian, or about your grandmother, you would use the feminine form of "my," "was," and "old."

Jeffrey Sachs, an advisor to the United Nations and director of Columbia University's Earth Institute, is one such expert. In books and countless speeches and television appearances, he has argued that poor countries are poor because they are hot, infertile, malaria-infested, and often landlocked; these factors, however, make it hard for them to be productive without an initial large investment to help them deal with such endemic problems. But they cannot pay for the investments precisely because they are poor -- they are in what economists call a "poverty trap." Until something is done about these problems, neither free markets nor democracy will do very much for them.

But then there are others, equally vocal, who believe that all of Sachs's answers are wrong. William Easterly, who battles Sachs from New York University at the other end of Manhattan, has become one of the most influential aid critics in his books, The Elusive Quest for Growth and The White Man's Burden. Dambisa Moyo, an economist who worked at Goldman Sachs and the World Bank, has joined her voice to Easterly's with her recent book, Dead Aid. Both argue that aid does more bad than good. It prevents people from searching for their own solutions, while corrupting and undermining local institutions and creating a self-perpetuating lobby of aid agencies.

The best bet for poor countries, they argue, is to rely on one simple idea: When markets are free and the incentives are right, people can find ways to solve their problems. They do not need handouts from foreigners or their own governments.

According to Easterly, there is no such thing as a poverty trap.

To find out whether there are in fact poverty traps, and, if so, where they are and how to help the poor get out of them, we need to better understand the concrete problems they face. Some aid programs help more than others, but which ones? Finding out required us to step out of the office and look more carefully at the world. In 2003, we founded what became the Abdul Latif Jameel Poverty Action Lab, or J-PAL. A key part of our mission is to research by using randomized control trials -- similar to experiments used in medicine to test the effectiveness of a drug -- to understand what works and what doesn't in the real-world fight against poverty. In practical terms, that meant we'd have to start understanding how the poor really live their lives.

it still leaves a lot of areas open for linguists to argue about. And the study did not build an exhaustive tree of any of the language families, in part because we probably don't have enough information to classify all of them at this point.

Still, it's hard to imagine any further details could overturn the gist of things, given how badly features failed to correlate across language families. And the work might be well received in some communities, since it provides an invitation to ask a fascinating question: given that there aren't obvious word order patterns across languages, how does the human brain do so well at learning the rules that are a peculiarity to any one of them?

systems that allow crowdsourced judgment to be tweaked, not to the taste of the general mass, which produces lowest common denominator effects, but to people and experts that you can trust for their judgment.

these systems are now implemented by Buzz and Digg 4

Important for me though, is that they don’t just take your social graph as is, because that mixes many different people for different reasons, but that you can tweak the groups.

“This is the problem with the internet! It’s full of crap!” Many would argue that without professional producers, editors, publishers, and the natural scarcity that we became accustomed to, there’s a flood of low-quality material that we can’t possible sift through on our own. From blogs to music to software to journalism, one of the biggest fears of the established order is how to handle the oncoming glut of mediocrity. Who shall tell us The Good from The Bad? “We need gatekeepers, and they need to be paid!”

The Internet has enabled us to build our social graph, and in turn, that social graph acts as an aggregate gatekeeper. The better that these systems for crowdsourcing the curation of content become, the more accurate the results will be.

This social-graph-as-curation is still relatively new, even by Internet standards. However, with tools like Buzz and Digg 4 (which allows you to see the aggregate ratings for content based on your social graph, and not the whole wide world) this technique is catching up to human publishers fast. For those areas where we don’t have strong social ties, we can count on reputation systems to help us “rate the raters”. These systems allow strangers to rate each other’s content, giving users some idea of who to trust, without having to know them personally. Yelp has a fairly mature reputation system, where locations are rated by users, but the users are rated, in turn, by each other.

Reputation systems and the social graph allow us to crowdsource curation.

Can you imagine if Apple had to approve your videos for posting on Youtube, where every minute, 24 hours of footage are uploaded? There’s no way humans could keep up! The traditional forms of curation and gatekeeping simply can not scale to meet the increase in production and transmission that the Internet allows. Crowdsourcing is the only curatorial/editorial mechanism that can scale to match the increased ability to produce that the Internet has given us.

is a problem of the utilization of knowledge which is not given to anyone in its totality.

who is to do the planning. It is about this question that all the dispute about "economic planning" centers. This is not a dispute about whether planning is to be done or not. It is a dispute as to whether planning is to be done centrally, by one authority for the whole economic system, or is to be divided among many individuals. Planning in the specific sense in which the term is used in contemporary controversy necessarily means central planning—direction of the whole economic system according to one unified plan. Competition, on the other hand, means decentralized planning by many separate persons. The halfway house between the two, about which many people talk but which few like when they see it, is the

Which of these systems is likely to be more efficient depends mainly on the question under which of them we can expect that fuller use will be made of the existing knowledge.

It may be admitted that, as far as scientific knowledge is concerned, a body of suitably chosen experts may be in the best position to command all the best knowledge available—though this is of course merely shifting the difficulty to the problem of selecting the experts.

Today it is almost heresy to suggest that scientific knowledge is not the sum of all knowledge. But a little reflection will show that there is beyond question a body of very important but unorganized knowledge which cannot possibly be called scientific in the sense of knowledge of general rules: the knowledge of the particular circumstances of time and place. It is with respect to this that practically every individual has some advantage over all others because he possesses unique information of which beneficial use might be made, but of which use can be made only if the decisions depending on it are left to him or are made with his active coöperation.

the relative importance of the different kinds of knowledge; those more likely to be at the disposal of particular individuals and those which we should with greater confidence expect to find in the possession of an authority made up of suitably chosen experts. If it is today so widely assumed that the latter will be in a better position, this is because one kind of knowledge, namely, scientific knowledge, occupies now so prominent a place in public imagination that we tend to forget that it is not the only kind that is relevant.

It is a curious fact that this sort of knowledge should today be generally regarded with a kind of contempt and that anyone who by such knowledge gains an advantage over somebody better equipped with theoretical or technical knowledge is thought to have acted almost disreputably. To gain an advantage from better knowledge of facilities of communication or transport is sometimes regarded as almost dishonest, although it is quite as important that society make use of the best opportunities in this respect as in using the latest scientific discoveries.

The common idea now seems to be that all such knowledge should as a matter of course be readily at the command of everybody, and the reproach of irrationality leveled against the existing economic order is frequently based on the fact that it is not so available. This view disregards the fact that the method by which such knowledge can be made as widely available as possible is precisely the problem to which we have to find an answer.

One reason why economists are increasingly apt to forget about the constant small changes which make up the whole economic picture is probably their growing preoccupation with statistical aggregates, which show a very much greater stability than the movements of the detail. The comparative stability of the aggregates cannot, however, be accounted for—as the statisticians occasionally seem to be inclined to do—by the "law of large numbers" or the mutual compensation of random changes.

the sort of knowledge with which I have been concerned is knowledge of the kind which by its nature cannot enter into statistics and therefore cannot be conveyed to any central authority in statistical form. The statistics which such a central authority would have to use would have to be arrived at precisely by abstracting from minor differences between the things, by lumping together, as resources of one kind, items which differ as regards location, quality, and other particulars, in a way which may be very significant for the specific decision. It follows from this that central planning based on statistical information by its nature cannot take direct account of these circumstances of time and place and that the central planner will have to find some way or other in which the decisions depending on them can be left to the "man on the spot."

We need decentralization because only thus can we insure that the knowledge of the particular circumstances of time and place will be promptly used. But the "man on the spot" cannot decide solely on the basis of his limited but intimate knowledge of the facts of his immediate surroundings. There still remains the problem of communicating to him such further information as he needs to fit his decisions into the whole pattern of changes of the larger economic system.

The problem which we meet here is by no means peculiar to economics but arises in connection with nearly all truly social phenomena, with language and with most of our cultural inheritance, and constitutes really the central theoretical problem of all social science. As Alfred Whitehead has said in another connection, "It is a profoundly erroneous truism, repeated by all copy-books and by eminent people when they are making speeches, that we should cultivate the habit of thinking what we are doing. The precise opposite is the case. Civilization advances by extending the number of important operations which we can perform without thinking about them." This is of profound significance in the social field. We make constant use of formulas, symbols, and rules whose meaning we do not understand and through the use of which we avail ourselves of the assistance of knowledge which individually we do not possess. We have developed these practices and institutions by building upon habits and institutions which have proved successful in their own sphere and which have in turn become the foundation of the civilization we have built up.

To assume all the knowledge to be given to a single mind in the same manner in which we assume it to be given to us as the explaining economists is to assume the problem away and to disregard everything that is important and significant in the real world.

That an economist of Professor Schumpeter's standing should thus have fallen into a trap which the ambiguity of the term "datum" sets to the unwary can hardly be explained as a simple error. It suggests rather that there is something fundamentally wrong with an approach which habitually disregards an essential part of the phenomena with which we have to deal: the unavoidable imperfection of man's knowledge and the consequent need for a process by which knowledge is constantly communicated and acquired. Any approach, such as that of much of mathematical economics with its simultaneous equations, which in effect starts from the assumption that people's knowledge corresponds with the objective facts of the situation, systematically leaves out what is our main task to explain. I am far from denying that in our system equilibrium analysis has a useful function to perform. But when it comes to the point where it misleads some of our leading thinkers into believing that the situation which it describes has direct relevance to the solution of practical problems, it is high time that we remember that it does not deal with the social process at all and that it is no more than a useful preliminary to the study of the main problem.

Bhrigu's actions are surprising, but probably not unique. There are few firm numbers showing the prevalence of research sabotage, but conversations with graduate students, postdocs and research-misconduct experts suggest that such misdeeds occur elsewhere, and that most go unreported or unpoliced. In this case, the episode set back research, wasted potentially tens of thousands of dollars and terrorized a young student. More broadly, acts such as Bhrigu's — along with more subtle actions to hold back or derail colleagues' work — have a toxic effect on science and scientists. They are an affront to the implicit trust between scientists that is necessary for research endeavours to exist and thrive.

Despite all this, there is little to prevent perpetrators re-entering science.

federal bodies that provide research funding have limited ability and inclination to take action in sabotage cases because they aren't interpreted as fitting the federal definition of research misconduct, which is limited to plagiarism, fabrication and falsification of research data.

In Bhrigu's case, administrators at the University of Michigan worked with police to investigate, thanks in part to the persistence of Ames and her supervisor, Theo Ross. "The question is, how many universities have such procedures in place that scientists can go and get that kind of support?" says Christine Boesz, former inspector-general for the US National Science Foundation in Arlington, Virginia, and now a consultant on scientific accountability. "Most universities I was familiar with would not necessarily be so responsive."

Some labs are known to be hyper-competitive, with principal investigators pitting postdocs against each other. But Ross's lab is a small, collegial place. At the time that Ames was noticing problems, it housed just one other graduate student, a few undergraduates doing projects, and the lab manager, Katherine Oravecz-Wilson, a nine-year veteran of the lab whom Ross calls her "eyes and ears". And then there was Bhrigu, an amiable postdoc who had joined the lab in April 2009.

Some people whom Ross consulted with tried to convince her that Ames was hitting a rough patch in her work and looking for someone else to blame. But Ames was persistent, so Ross took the matter to the university's office of regulatory affairs, which advises on a wide variety of rules and regulations pertaining to research and clinical care. Ray Hutchinson, associate dean of the office, and Patricia Ward, its director, had never dealt with anything like it before. After several meetings and two more instances of alcohol in the media, Ward contacted the department of public safety — the university's police force — on 9 March. They immediately launched an investigation — into Ames herself. She endured two interrogations and a lie-detector test before investigators decided to look elsewhere.

At 4:00 a.m. on Sunday 18 April, officers installed two cameras in the lab: one in the cold room where Ames's blots had been contaminated, and one above the refrigerator where she stored her media. Ames came in that day and worked until 5:00 p.m. On Monday morning at around 10:15, she found that her medium had been spiked again. When Ross reviewed the tapes of the intervening hours with Richard Zavala, the officer assigned to the case, she says that her heart sank. Bhrigu entered the lab at 9:00 a.m. on Monday and pulled out the culture media that he would use for the day. He then returned to the fridge with a spray bottle of ethanol, usually used to sterilize lab benches. With his back to the camera, he rummaged through the fridge for 46 seconds. Ross couldn't be sure what he was doing, but it didn't look good. Zavala escorted Bhrigu to the campus police department for questioning. When he told Bhrigu about the cameras in the lab, the postdoc asked for a drink of water and then confessed. He said that he had been sabotaging Ames's work since February. (He denies involvement in the December and January incidents.)

Some say that the structure of the scientific enterprise is to blame. The big rewards — tenured positions, grants, papers in stellar journals — are won through competition. To get ahead, researchers need only be better than those they are competing with. That ethos, says Brian Martinson, a sociologist at HealthPartners Research Foundation in Minneapolis, Minnesota, can lead to sabotage. He and others have suggested that universities and funders need to acknowledge the pressures in the research system and try to ease them by means of education and rehabilitation, rather than simply punishing perpetrators after the fact.

Bhrigu says that he felt pressure in moving from the small college at Toledo to the much bigger one in Michigan. He says that some criticisms he received from Ross about his incomplete training and his work habits frustrated him, but he doesn't blame his actions on that. "In any kind of workplace there is bound to be some pressure," he says. "I just got jealous of others moving ahead and I wanted to slow them down."

At Washtenaw County Courthouse in July, having reviewed the case files, Pollard Hines delivered Bhrigu's sentence. She ordered him to pay around US$8,800 for reagents and experimental materials, plus $600 in court fees and fines — and to serve six months' probation, perform 40 hours of community service and undergo a psychiatric evaluation.

But the threat of a worse sentence hung over Bhrigu's head. At the request of the prosecutor, Ross had prepared a more detailed list of damages, including Bhrigu's entire salary, half of Ames's, six months' salary for a technician to help Ames get back up to speed, and a quarter of the lab's reagents. The court arrived at a possible figure of $72,000, with the final amount to be decided upon at a restitution hearing in September.

Ross, though, is happy that the ordeal is largely over. For the month-and-a-half of the investigation, she became reluctant to take on new students or to hire personnel. She says she considered packing up her research programme. She even questioned her own sanity, worrying that she was the one sabotaging Ames's work via "an alternate personality". Ross now wonders if she was too trusting, and urges other lab heads to "realize that the whole spectrum of humanity is in your lab. So, when someone complains to you, take it seriously."

She also urges others to speak up when wrongdoing is discovered. After Bhrigu pleaded guilty in June, Ross called Trempe at the University of Toledo. He was shocked, of course, and for more than one reason. His department at Toledo had actually re-hired Bhrigu. Bhrigu says that he lied about the reason he left Michigan, blaming it on disagreements with Ross. Toledo let Bhrigu go in July, not long after Ross's call.

Now that Bhrigu is in India, there is little to prevent him from getting back into science. And even if he were in the United States, there wouldn't be much to stop him. The National Institutes of Health in Bethesda, Maryland, through its Office of Research Integrity, will sometimes bar an individual from receiving federal research funds for a time if they are found guilty of misconduct. But Bhigru probably won't face that prospect because his actions don't fit the federal definition of misconduct, a situation Ross finds strange. "All scientists will tell you that it's scientific misconduct because it's tampering with data," she says.

Ames says that the experience shook her trust in her chosen profession. "I did have doubts about continuing with science. It hurt my idea of science as a community that works together, builds upon each other's work and collaborates."

Of the 49 articles, 45 claimed to have uncovered effective interventions. Thirty-four of these claims had been retested, and 14 of these, or 41 percent, had been convincingly shown to be wrong or significantly exaggerated. If between a third and a half of the most acclaimed research in medicine was proving untrustworthy, the scope and impact of the problem were undeniable. That article was published in the Journal of the American Medical Association. [here's the link.]

David Freedman -- has quite a bit on the sociology of research in medical science. Here are a few quotes:

Even when the evidence shows that a particular research idea is wrong, if you have thousands of scientists who have invested their careers in it, they’ll continue to publish papers on it,” he says. “It’s like an epidemic, in the sense that they’re infected with these wrong ideas, and they’re spreading it to other researchers through journals.”

the peer-review process often pressures researchers to shy away from striking out in genuinely new directions, and instead to build on the findings of their colleagues (that is, their potential reviewers) in ways that only seem like breakthroughs—as with the exciting-sounding gene linkages (autism genes identified!) and nutritional findings (olive oil lowers blood pressure!) that are really just dubious and conflicting variations on a theme.

The ultimate protection against research error and bias is supposed to come from the way scientists constantly retest each other’s results—except they don’t. Only the most prominent findings are likely to be put to the test, because there’s likely to be publication payoff in firming up the proof, or contradicting it.

Doctors may notice that their patients don’t seem to fare as well with certain treatments as the literature would lead them to expect, but the field is appropriately conditioned to subjugate such anecdotal evidence to study findings.

[B]eing wrong in science is fine, and even necessary—as long as scientists recognize that they blew it, report their mistake openly instead of disguising it as a success, and then move on to the next thing, until they come up with the very occasional genuine breakthrough. But as long as careers remain contingent on producing a stream of research that’s dressed up to seem more right than it is, scientists will keep delivering exactly that.

The natural scientific doubt was this: scientists could not say with absolute certainty that smoking caused cancer, because there wasn’t an invariable effect. “Smoking does not kill everyone who smokes, it only kills about half of them.” All scientists could say was that there was an extremely strong association between smoking and serious health risks

the “Tobacco Strategy” was created, and had two tactics: To “use normal scientific doubt to undermine the status of actual scientific knowledge” and To exploit the media’s adherence to the fairness doctrine, which would give equal weight to each side of a debate, regardless of any disparity in the supporting scientific evidence

Fred Seitz was a scientist who learned the Tobacco Strategy first-hand. He had an impressive resume. An actual rocket scientist, he helped build the atomic bomb in the 1940s, worked for NATO in the 1950s, was president of the U.S. National Academy of Sciences in the 1960s, and of Rockefeller University in the 1970s.

After his retirement in 1979, Seitz took on a job for the tobacco industry. Over the next 6 years, he doled out $45 million of R.J. Reynolds’ money to fund biomedical research to create “an extensive body of scientifically well-grounded data useful in defending the industry against attacks” by such means as focussing on alternative “causes or development mechanisms of chronic degenerative diseases imputed to cigarettes.” He was joined by, most notably, two other physicists: William Nierenberg, who also worked on the atom bomb in the 1940s, submarine warfare, NATO, and was appointed director or the Scripps Institution of Oceanography in 1965; and Robert Jastrow, who founded NASA’s Goddard Institute for Space Studies, which he directed until he retired in 1981 to teach at Dartmouth College.

In 1984, these three founded the think tank, the George C. Marshall Institute

None of these men were experts in environmental and health issues, but they all “used their scientific credentials to present themselves as authorities, and they used their authority to discredit any science they didn’t like.” They turned out to be wrong, in terms of the science, on every issue they weighed in on. But they turned out to be highly successful in preventing or limiting regulation that the scientific evidence would warrant.

The bulk of the book details at how these men and others applied the Tobacco Strategy to create doubt on the following issues: the unfeasibility of the Strategic Defense Initiative (Ronald Reagan’s “Star Wars”), and the resultant threat of nuclear winter that Carl Sagan, among others, pointed out acid rain depletion of the ozone layer second-hand smoke, and most recently, and significantly, global warming.

Having pointed out the dangers the doubt-mongers pose, Oreskes and Conway propose a remedy: an emphasis on scientific literacy, not in the sense of memorizing scientific facts, but in being able to assess which scientists to trust.

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.

However, a greater concern lies in the notion of climate change itself. Climate change is in essence one kind of nature-society relationship, in which humans influence the climate through greenhouse gas (particularly CO2) emissions, and the climate strikes back by heating up and going crazy at times. This can be further simplified into a battle between humans and CO2: reducing CO2 guards against climate change, and increasing it aggravates the consequences. This view is anchored in scientists’ recommendation that a ‘safe’ level of CO2 should be at 350 parts per million (ppm) instead of the current 390. Already, the need to reduce CO2 is understood, as is evident in the push for greener fuels, more efficient means of production, the proliferation of ‘green’ products and companies, and most recently, the Cancun talks.

So can there be anything wrong with reducing CO2? No, there isn’t, but singling out CO2 as the culprit of climate change or of the environmental problems we face prevents us from looking within. What do I mean? The enemy, CO2, is an ‘other’, an externality produced by our economic systems but never an inherent component of the systems. Thus, we can declare war on the gas or on climate change without taking a step back and questioning: is there anything wrong with the way we develop?  Take Singapore for example: the government pledged to reduce carbon emissions by 16% under ‘business as usual’ standards, which says nothing about how ‘business’ is going to be changed other than having less carbon emissions (in fact, it is questionable even that CO2 levels will decrease, as ‘business as usual’ standards project a steady increase emission of CO2 each year). With the development of green technologies, decrease in carbon emissions will mainly be brought about by increased energy efficiency and switch to alternative fuels (including the insidious nuclear energy).

Thus, the way we develop will hardly be changed. Nobody questions whether our neoliberal system of development, which relies heavily on consumption to drive economies, needs to be looked into. We assume that it is the right way to develop, and only tweak it for the amount of externalities produced. Whether or not we should be measuring development by the Gross Domestic Product (GDP) or if welfare is correlated to the amount of goods and services consumed is never considered. Even the UN-REDD (Reducing Emissions from Deforestation and Forest Degradation) scheme which aims to pay forest-rich countries for protecting their forests, ends up putting a price tag on them. The environment is being subsumed under the economy, when it should be that the economy is re-looked to take the environment into consideration.

when the world is celebrating after having held at bay the dangerous greenhouse gas, why would anyone bother rethinking about the economy? Yet we should, simply because there are alternative nature-society relationships and discourses about nature that are more or of equal importance as global warming. Annie Leonard’s informative videos on The Story of Stuff and specific products like electronics, bottled water and cosmetics shed light on the dangers of our ‘throw-away culture’ on the planet and poorer countries. What if the enemy was instead consumerism? Doing so would force countries (especially richer ones) to fundamentally question the nature of development, instead of just applying a quick technological fix. This is so much more difficult (and less economically viable), alongside other issues like environmental injustices – e.g. pollution or dumping of waste by Trans-National Corporations in poorer countries and removal of indigenous land rights. It is no wonder that we choose to disregard internal problems and focus instead on an external enemy; when CO2 is the culprit, the solution is too simple and detached from the communities that are affected by changes in their environment.

We need hence to allow for a greater politics of the environment. What I am proposing is not to diminish our action to reduce carbon emissions, for I do believe that it is part of the environmental problem that we are facing. What instead should be done is to reduce our fixation on CO2 as the main or only driver of climate change, and of climate change as the most pertinent nature-society issue we are facing. We should understand that there are many other ways of thinking about the environment; ‘developing’ countries, for example, tend to have a closer relationship with their environment – it is not something ‘out there’ but constantly interacted with for food, water, regulating services and cultural value. Their views and the impact of the socio-economic forces (often from TNCs and multi-lateral organizations like IMF) that shape the environment must also be taken into account, as do alternative meanings of sustainable development. Thus, even as we pat ourselves on the back for having achieved something significant at Cancun, our action should not and must not end there. Even if climate change hogs the headlines now, we must embrace more plurality in environmental discourse, for nature is not and never so simple as climate change alone. And hopefully sometime in the future, alongside a multi-lateral conference on climate change, the world can have one which rethinks the meaning of development.

I could just as well get the same feel or texture of the prevailing sentiment by counting how many times people search for the word, “market down turn” – “recession” – “unemployment,” in Google or counting how many times those words appear in the Herald Tribune and WSJ – in either case, my point is resorting to unconventional methods to make sense of our world may actually hold out more prospects than resorting to a conventional methods.

we need to be mindful whenever we talk about productivity in the context of statistics bc it can skewer the picture

Statistics can even tell you what’s your chances of living beyond 70 years if you dont smoke and drink like me. But it can’t tell you really simple things like how much of life you lived in those years. In fact, it can tell you very little about the human condition – It can’t tell you for example why a parent believes so much in a disabled child, that to them, he’s god given; it cant tell you why people choose to fight and even die for their country - it can tell you even less about your story, love & hate, war & peace………or for that matter anything about the human condition. Man Stastistics has got no soul……. It’s machine language. And less of a heart. It’s good calculating how big manhole covers should be or how many nuts do you need to hold up a bridge under X, Y and Z conditions - other than that, its good for nothing else - that’s why whenever I see a man spouting statistics – I just know he is full of shit; doesn’t matter who he is -could well be a man on TV, a bent pastor who thinks Jesus asked him to build another shopping mall or even someone who just wants to sell you something you dont need - they’re all full of invisibe and odorless shit – and that’s the deadliest type of shit, bc you can be neck deep in it and still not know that you are in shit.”

"Pay levels often don't reflect the true value that is being created. As a society, we need a pay structure which rewards those jobs that create most societal benefit rather than those that generate profits at the expense of society and the environment".

"The point we are making is more fundamental - that there should be a relationship between what we are paid and the value our work generates for society. We've found a way to calculate that,"

The research also makes a variety of policy recommendations to align pay more closely with the value of work. These include establishing a high pay commission, building social and environmental value into prices, and introducing more progressive taxation.

“It was just too sensitive, and we didn’t want to go there,” said Eric E. Schmidt, the chief executive of Google. “You want to avoid enabling stalker behavior.”

The second article focuses on innovations in high frequency trading in financial markets, which bears some responsibility for the so-called "flash crash" of May 6th last year, in which the DJIA plunged more than 700 points in just minutes.

One debate has focused on whether some traders are firing off fake orders thousands of times a second to slow down exchanges and mislead others. Michael Durbin, who helped build high-frequency trading systems for companies like Citadel and is the author of the book “All About High-Frequency Trading,” says that most of the industry is legitimate and benefits investors. But, he says, the rules need to be strengthened to curb some disturbing practices.

This situation raises what I see to be core questions in the governance of innovation -- to what degree can innovation be shaped for achieving intended purposes? and, To what degree can the consequences of innovation be anticipated?

What, in your view, are the best global solutions?

There are plenty aid programs that seem to work, from de-worming to small business grants to incentives to send children to school. But none of these programs are likely to have transformative effects.

The difference between a country with $1,500 and $15,000 of income a head a head is simple: industry. All the microfinance and microenterprise programs in the world are not going to build large firms and import technology and provide most people with what they really want: a stable job, regular wages, and a decent work environment.

How you get these firms is the tricky question. Only a few firms will be home grown; most will be firms that spread across borders, because they have the markets and know-how. Probably we’ll need to see wages rise in China and India before manufacturing ever spreads to the poorest places on the planet, like Central Asia and Africa.The countries that will get them first are the ones that are close to trade routes, have stable political climates, make it easy to get finance, are open to trade, have large domestic markets, have able and educated workforces (i.e. secondary education), and have leaders in charge who don’t see the industrial sector as either a threat to their power or a garden from which they get to select the sweetest fruits for themselves.

How urgent is it to act (in the context of climate change)?The short answer: I wouldn’t know. For the US and China and Europe and India, they must change because if they don’t nothing will.For the Ugandas or Uzbekistans or Bolivias of the world, I can’t see it making a difference. Let them develop as green as possible, but let’s not impede their growth because of it, and rob them of the opportunity we took ourselves.

BMW acknowledged that it had set up “doorway pages,” which exist just to attract search engines and then redirect traffic to a different site. The company at the time said it had no intention of deceiving users, adding “if Google says all doorway pages are illegal, we have to take this into consideration.”

The Times sent Google the evidence it had collected about the links to JCPenney.com. Google promptly set up an interview with Matt Cutts, the head of the Webspam team at Google, and a man whose every speech, blog post and Twitter update is parsed like papal encyclicals by players in the search engine world.

He said Google had detected previous guidelines violations related to JCPenney.com on three occasions, most recently last November. Each time, steps were taken that reduced Penney’s search results — Mr. Cutts avoids the word “punished” — but Google did not later “circle back” to the company to see if it was still breaking the rules, he said.

He and his team had missed this recent campaign of paid links, which he said had been up and running for the last three to four months. “Do I wish our system had detected things sooner? I do,” he said. “But given the one billion queries that Google handles each day, I think we do an amazing job.”

Mr. Cutts sounded remarkably upbeat and unperturbed during this conversation, which was a surprise given that we were discussing a large, sustained effort to snooker his employer. Asked about his zenlike calm, he said the company strives not to act out of anger.

PENNEY reacted to this instant reversal of fortune by, among other things, firing its search engine consulting firm, SearchDex. Executives there did not return e-mail or phone calls.

“Am I happy this happened?” he later asked. “Absolutely not. Is Google going to take strong corrective action? We absolutely will.” And the company did. On Wednesday evening, Google began what it calls a “manual action” against Penney, essentially demotions specifically aimed at the company.

At 7 p.m. Eastern time on Wednesday, J. C. Penney was still the No. 1 result for “Samsonite carry on luggage.” Two hours later, it was at No. 71.

Carlo Rovelli, a physicist at the University of Aix-Marseille, emphasised the uselessness of certainty. He said that the idea of something being "scientifically proven" was practically an oxymoron and that the very foundation of science is to keep the door open to doubt.

"A good scientist is never 'certain'. Lack of certainty is precisely what makes conclusions more reliable than the conclusions of those who are certain: because the good scientist will be ready to shift to a different point of view if better elements of evidence, or novel arguments emerge. Therefore certainty is not only something of no use, but is in fact damaging, if we value reliability."

physicist Lawrence Krauss of Arizona State University agreed. "In the public parlance, uncertainty is a bad thing, implying a lack of rigour and predictability. The fact that global warming estimates are uncertain, for example, has been used by many to argue against any action at the present time," he said.

however, uncertainty is a central component of what makes science successful. Being able to quantify uncertainty, and incorporate it into models, is what makes science quantitative, rather than qualitative. Indeed, no number, no measurement, no observable in science is exact. Quoting numbers without attaching an uncertainty to them implies they have, in essence, no meaning."

Neil Gershenfeld, director of the Massachusetts Institute of Technology's Centre for Bits and Atoms wants everyone to know that "truth" is just a model. "The most common misunderstanding about science is that scientists seek and find truth. They don't – they make and test models," he said.

Building models is very different from proclaiming truths. It's a never-ending process of discovery and refinement, not a war to win or destination to reach. Uncertainty is intrinsic to the process of finding out what you don't know, not a weakness to avoid. Bugs are features – violations of expectations are opportunities to refine them. And decisions are made by evaluating what works better, not by invoking received wisdom."

writer and web commentator Clay Shirky suggested that people should think more carefully about how they see the world. His suggestion was the Pareto principle, a pattern whereby the top 1% of the population control 35% of the wealth or, on Twitter, the top 2% of users send 60% of the messages. Sometimes known as the "80/20 rule", the Pareto principle means that the average is far from the middle.It is applicable to many complex systems, "And yet, despite a century of scientific familiarity, samples drawn from Pareto distributions are routinely presented to the public as anomalies, which prevents us from thinking clearly about the world," said Shirky. "We should stop thinking that average family income and the income of the median family have anything to do with one another, or that enthusiastic and normal users of communications tools are doing similar things, or that extroverts should be only moderately more connected than normal people. We should stop thinking that the largest future earthquake or market panic will be as large as the largest historical one; the longer a system persists, the likelier it is that an event twice as large as all previous ones is coming."

Kevin Kelly, editor-at-large of Wired, pointed to the value of negative results. "We can learn nearly as much from an experiment that does not work as from one that does. Failure is not something to be avoided but rather something to be cultivated. That's a lesson from science that benefits not only laboratory research, but design, sport, engineering, art, entrepreneurship, and even daily life itself. All creative avenues yield the maximum when failures are embraced."

Michael Shermer, publisher of the Skeptic Magazine, wrote about the importance of thinking "bottom up not top down", since almost everything in nature and society happens this way.

But most people don't see things that way, said Shermer. "Bottom up reasoning is counterintuitive. This is why so many people believe that life was designed from the top down, and why so many think that economies must be designed and that countries should be ruled from the top down."

Roger Schank, a psychologist and computer scientist, proposed that we should all know the true meaning of "experimentation", which he said had been ruined by bad schooling, where pupils learn that scientists conduct experiments and if we copy exactly what they did in our high school labs we will get the results they got. "In effect we learn that experimentation is boring, is something done by scientists and has nothing to do with our daily lives."Instead, he said, proper experiments are all about assessing and gathering evidence. "In other words, the scientific activity that surrounds experimentation is about thinking clearly in the face of evidence obtained as the result of an experiment. But people who don't see their actions as experiments, and those who don't know how to reason carefully from data, will continue to learn less well from their own experiences than those who do

Lisa Randall, a physicist at Harvard University, argued that perhaps "science" itself would be a useful concept for wider appreciation. "The idea that we can systematically understand certain aspects of the world and make predictions based on what we've learned – while appreciating and categorising the extent and limitations of what we know – plays a big role in how we think.

"Many words that summarise the nature of science such as 'cause and effect', 'predictions', and 'experiments', as well as words that describe probabilistic results such as 'mean', 'median', 'standard deviation', and the notion of 'probability' itself help us understand more specifically what this means and how to interpret the world and behaviour within it."