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You can read the talk here, but in a nutshell, Massimo was admonishing skeptics who reject the scientific consensus in fields in which they have no technical expertise - the most notable recent example of this being anthropogenic climate change, about which venerable skeptics like James Randi and Michael Shermer have publicly expressed doubts (though Shermer has since changed his mind).

I'm totally with Massimo that it seems quite likely that anthropogenic climate change is really happening. But I'm not sure I can get behind Massimo's broader argument that non-experts should defer to the expert consensus in a field.

First of all, while there are strong incentives for a researcher to find errors in other work in the field, there are strong disincentives for her to challenge the field's foundational assumptions. It will be extremely difficult for her to get other people to agree with her if she tries, and if she succeeds, she'll still be taking herself down along with the rest of the field.

My recent post “The War Over ‘Nice’” (describing the blogosphere’s reaction to Phil Plait’s “Don’t Be a Dick” speech) has topped out at more than 200 comments.

Many readers appear to object (some strenuously) to the very ideas of discussing best practices, seeking evidence of efficacy for skeptical outreach, matching strategies to goals, or encouraging some methods over others. Some seem to express anger that a discussion of best practices would be attempted at all. 

No Right or Wrong Way? The milder forms of these objections run along these lines: “Everyone should do their own thing.” “Skepticism needs all kinds of approaches.” “There’s no right or wrong way to do skepticism.” “Why are we wasting time on these abstract meta-conversations?”

Since then many studies reinforced this theory, showing that Catholicism, and indeed religion in general, seems to protect against suicide. Unfortunately, almost all these studies have been flawed - most often because they looked at average suicide rates and average religious beliefs across particular societies. They didn't look at the individual characteristics of those people who commit suicide.

Three new studies have addressed this problem. Each of them them takes advantage of new data to explore in some detail the link between religion and reduced suicide.

Matthias Egger, at the University of Bern in Switzerland, has cleverly linked census data to death records - not at all as straightforward as you might imagine. What that gives, for the first time, is a large database with reliable records of individual's religious affiliation in the last few years before they took their life.

Humans make errors. We make errors of fact and errors of judgment. We have blind spots in our field of vision and gaps in our stream of attention.

These weaknesses put us at a disadvantage. We make decisions with partial information. We are forced to steer by guesswork. We go with our gut.

Others use data.

science has long been married to mathematics. Generally it has been for the better. Especially since the days of Galileo and Newton, math has nurtured science. Rigorous mathematical methods have secured science’s fidelity to fact and conferred a timeless reliability to its findings.

a mutant form of math has deflected science’s heart from the modes of calculation that had long served so faithfully. Science was seduced by statistics, the math rooted in the same principles that guarantee profits for Las Vegas casinos. Supposedly, the proper use of statistics makes relying on scientific results a safe bet. But in practice, widespread misuse of statistical methods makes science more like a crapshoot.

science’s dirtiest secret: The “scientific method” of testing hypotheses by statistical analysis stands on a flimsy foundation. Statistical tests are supposed to guide scientists in judging whether an experimental result reflects some real effect or is merely a random fluke, but the standard methods mix mutually inconsistent philosophies and offer no meaningful basis for making such decisions. Even when performed correctly, statistical tests are widely misunderstood and frequently misinterpreted. As a result, countless conclusions in the scientific literature are erroneous, and tests of medical dangers or treatments are often contradictory and confusing.

Measuring and assessing academic performance is now a fact of scientific life.

Yet current systems of measurement are inadequate. Widely used metrics, from the newly-fashionable Hirsch index to the 50-year-old citation index, are of limited use1

Existing metrics do not capture the full range of activities that support and transmit scientific ideas, which can be as varied as mentoring, blogging or creating industrial prototypes.

The origin of Aids denialism lies with one man. Peter Duesberg has spent the whole of his academic career at the University of California, Berkeley. In the 1970s he performed groundbreaking work that helped show how mutated genes cause cancer, an insight that earned him a well-deserved international reputation.

in the early 1980s, something changed. Duesberg attempted to refute his own theories, claiming that it was not mutated genes but rather environmental toxins that are cancer's true cause. He dismissed the studies of other researchers who had furthered his original work. Then, in 1987, he published a paper that extended his new train of thought to Aids.

Initially many scientists were open to Duesberg's ideas. But as evidence linking HIV to Aids mounted - crucially the observation that ARVs brought Aids sufferers who were on the brink of death back to life - the vast majority concluded that the debate was over. Nonetheless, Duesberg persisted with his arguments, and in doing so attracted a cabal of supporters

The problem of replicability in science from xkcdby Massimo Pigliucci

In recent months much has been written about the apparent fact that a surprising, indeed disturbing, number of scientific findings cannot be replicated, or when replicated the effect size turns out to be much smaller than previously thought.

Arguably, the recent streak of articles on this topic began with one penned by David Freedman in The Atlantic, and provocatively entitled “Lies, Damned Lies, and Medical Science.” In it, the major character was John Ioannidis, the author of some influential meta-studies about the low degree of replicability and high number of technical flaws in a significant portion of published papers in the biomedical literature.

Massimo and Julia sit down in front of a live audience at the Jefferson Market Library in New York City for a conversation about science, non-science, and pseudo-science. Based on Massimo's book: "Nonsense on Stilts: How to Tell Science from Bunk" the topics they cover include whether the qualitative sciences are less reliable than quantitative ones, the re-running of the tape of life, and who is smarter: physicists, biologists, or psychologists? Also, why are evolutionary psychologist so fixated on sex?

Is it legitimate to cite one’s intuitions as evidence in a philosophical argument?

appeals to intuitions are ubiquitous in philosophy. What are intuitions? Well, that’s part of the controversy, but most philosophers view them as intellectual “seemings.” George Bealer, perhaps the most prominent defender of intuitions-as-evidence, writes, “For you to have an intuition that A is just for it to seem to you that A… Of course, this kind of seeming is intellectual, not sensory or introspective (or imaginative).”2 Other philosophers have characterized them as “noninferential belief due neither to perception nor introspection”3 or alternatively as “applications of our ordinary capacities for judgment.”4

Philosophers may not agree on what, exactly, intuition is, but that doesn’t stop them from using it. “Intuitions often play the role that observation does in science – they are data that must be explained, confirmers or the falsifiers of theories,” Brian Talbot says.5 Typically, the way this works is that a philosopher challenges a theory by applying it to a real or hypothetical case and showing that it yields a result which offends his intuitions (and, he presumes, his readers’ as well).

wrote a piece about James Delingpole's unfortunate appearance on the BBC program Horizon on Monday. In that piece I refered to one of his own Telegraph articles in which he criticizes renowned sceptic Dr Ben Goldacre for betraying the principles of scepticism in his regard of the climate change debate. That article turns out to be rather instructional as it highlights perfectly the difference between real scepticism and the false scepticism commonly described as denialism.

It appears that James has tremendous respect for Ben Goldacre, who is a qualified medical doctor and has written a best-selling book about science scepticism called Bad Science and continues to write a popular Guardian science column. Here's what Delingpole has to say about Dr Goldacre: Many of Goldacre’s campaigns I support. I like and admire what he does. But where I don’t respect him one jot is in his views on ‘Climate Change,’ for they jar so very obviously with supposed stance of determined scepticism in the face of establishment lies.

Scepticism is not some sort of rebellion against the establishment as Delingpole claims. It is not in itself an ideology. It is merely an approach to evaluating new information. There are varying definitions of scepticism, but Goldacre's variety goes like this: A sceptic does not support or promote any new theory until it is proven to his or her satisfaction that the new theory is the best available. Evidence is examined and accepted or discarded depending on its persuasiveness and reliability. Sceptics like Ben Goldacre have a deep appreciation for the scientific method of testing a hypothesis through experimentation and are generally happy to change their minds when the evidence supports the opposing view. Sceptics are not true believers, but they search for the truth. Far from challenging the established scientific consensus, Goldacre in Bad Science typcially defends the scientific consensus against alternative medical views that fall back on untestable positions. In science the consensus is sometimes proven wrong, and while this process is imperfect it eventually results in the old consensus being replaced with a new one.

in the magazine article Joshua mentions several studies of “folk morality,” i.e. of how ordinary people think about moral problems. The results are fascinating. It turns out that people’s views are correlated with personality traits, with subjects who score high on “openness to experience” being reliably more relativists than objectivists about morality (I am not using the latter term in the infamous Randyan meaning here, but as Knobe does, to indicate the idea that morality has objective bases).

Other studies show that people who are capable of considering multiple options in solving mathematical puzzles also tend to be moral relativists, and — in a study co-authored by Knobe himself — the very same situation (infanticide) was judged along a sliding scale from objectivism to relativism depending on whether the hypothetical scenario involved a fellow American (presumably sharing our same general moral values), the member of an imaginary Amazonian tribe (for which infanticide was acceptable), and an alien from the planet Pentar (belonging to a race whose only goal in life is to turn everything into equilateral pentagons, and killing individuals that might get in the way of that lofty objective is a duty). Oh, and related research also shows that young children tend to be objectivists, while young adults are usually relativists — but that later in life one’s primordial objectivism apparently experiences a comeback.

This is all very interesting social science, but is it philosophy? Granted, the differences between various disciplines are often not clear cut, and of course whenever people engage in truly inter-disciplinary work we should simply applaud the effort and encourage further work. But I do wonder in what sense, if any, the kinds of results that Joshua and his colleagues find have much to do with moral philosophy.

Muller calls his latest obsession the Berkeley Earth project. The aim is so simple that the complexity and magnitude of the undertaking is easy to miss. Starting from scratch, with new computer tools and more data than has ever been used, they will arrive at an independent assessment of global warming. The team will also make every piece of data it uses – 1.6bn data points – freely available on a website. It will post its workings alongside, including full information on how more than 100 years of data from thousands of instruments around the world are stitched together to give a historic record of the planet's temperature.

Muller is fed up with the politicised row that all too often engulfs climate science. By laying all its data and workings out in the open, where they can be checked and challenged by anyone, the Berkeley team hopes to achieve something remarkable: a broader consensus on global warming. In no other field would Muller's dream seem so ambitious, or perhaps, so naive.

"We are bringing the spirit of science back to a subject that has become too argumentative and too contentious," Muller says, over a cup of tea. "We are an independent, non-political, non-partisan group. We will gather the data, do the analysis, present the results and make all of it available. There will be no spin, whatever we find." Why does Muller feel compelled to shake up the world of climate change? "We are doing this because it is the most important project in the world today. Nothing else comes close," he says.

Last summer NCAR issued a dramatic press release announcing that oil from the Gulf spill would soon be appearing on the beaches of the Atlantic ocean.  I discussed it here. Here are the first four paragraphs of that press release: BOULDER—A detailed computer modeling study released today indicates that oil from the massive spill in the Gulf of Mexico might soon extend along thousands of miles of the Atlantic coast and open ocean as early as this summer. The modeling results are captured in a series of dramatic animations produced by the National Center for Atmospheric Research (NCAR) and collaborators. he research was supported in part by the National Science Foundation, NCAR’s sponsor. The results were reviewed by scientists at NCAR and elsewhere, although not yet submitted for peer-review publication. “I’ve had a lot of people ask me, ‘Will the oil reach Florida?’” says NCAR scientist Synte Peacock, who worked on the study. “Actually, our best knowledge says the scope of this environmental disaster is likely to reach far beyond Florida, with impacts that have yet to be understood.” The computer simulations indicate that, once the oil in the uppermost ocean has become entrained in the Gulf of Mexico’s fast-moving Loop Current, it is likely to reach Florida's Atlantic coast within weeks. It can then move north as far as about Cape Hatteras, North Carolina, with the Gulf Stream, before turning east. Whether the oil will be a thin film on the surface or mostly subsurface due to mixing in the uppermost region of the ocean is not known.

A few weeks ago NCAR's David Hosansky who presumably wrote that press release, asks whether NCAR got it wrong.  His answer?  No, not really: During last year’s crisis involving the massive release of oil into the Gulf of Mexico, NCAR issued a much-watched animation projecting that the oil could reach the Atlantic Ocean. But detectable amounts of oil never made it to the Atlantic, at least not in an easily visible form on the ocean surface. Not surprisingly, we’ve heard from a few people asking whether NCAR got it wrong. These events serve as a healthy reminder of a couple of things: *the difference between a projection and an actual forecast *the challenges of making short-term projections of natural processes that can act chaotically, such as ocean currents

What then went wrong? First, the projection. Scientists from NCAR, the Department of Energy’s Los Alamos National Laboratory, and IFM-GEOMAR in Germany did not make a forecast of where the oil would go. Instead, they issued a projection. While there’s not always a clear distinction between the two, forecasts generally look only days or hours into the future and are built mostly on known elements (such as the current amount of humidity in the atmosphere). Projections tend to look further into the future and deal with a higher number of uncertainties (such as the rate at which oil degrades in open waters and the often chaotic movements of ocean currents). Aware of the uncertainties, the scientific team projected the likely path of the spill with a computer model of a liquid dye. They used dye rather than actual oil, which undergoes bacterial breakdown, because a reliable method to simulate that breakdown was not available. As it turned out, the oil in the Gulf broke down quickly due to exceptionally strong bacterial action and, to some extent, the use of chemical dispersants.

as new technologies emerge to better reveal people’s experiences, the law ought to do more to take these experiences into account. In tort and criminal law, we often ignore or downplay the importance of subjective experience. This is no surprise. During the hundreds of years in which these bodies of law developed, we had very poor methods of making inferences about the experiences of others. As we get better at measuring experiences, however, I make the normative claim that we ought to change fundamental aspects of the law to take better account of people’s experiences.

Researchers are trying to develop more accurate methods of detecting deception using brain imaging.    While many in the scientific community doubt that current brain-based methods of lie detection are sufficiently accurate and reliable to use in forensic contexts, that has stopped neither companies from marketing fMRI lie detection services to the public, nor litigants from trying to introduce such evidence in court.

Given the substantial possibility that we will develop reasonably accurate lie detectors within the next thirty years, our current secretive behaviors have already become harder to hide.

Science stories usually fall into three families: wacky stories, scare stories and "breakthrough" stories.

these stories are invariably written by the science correspondents, and hotly followed, to universal jubilation, with comment pieces, by humanities graduates, on how bonkers and irrelevant scientists are.

A close relative of the wacky story is the paradoxical health story. Every Christmas and Easter, regular as clockwork, you can read that chocolate is good for you (www.badscience.net/?p=67), just like red wine is, and with the same monotonous regularity

better management of flood risks in Australia will depend up better data on flood risk.  However, collecting such data has proven problematic

As many Queenslanders affected by January’s floods are realising, riverine flood damage is commonly excluded from household insurance policies. And this is unlikely to change until councils – especially in Queensland – stop dragging their feet and actively assist in developing comprehensive data insurance companies can use.

? Because there is often little available information that would allow an insurer to adequately price this flood risk. Without this, there is little economic incentive for insurers to accept this risk. It would be irresponsible for insurers to cover riverine flood without quantifying and pricing the risk accordingly.

Arguably the most important finding from the emerging economics of happiness has been the Easterlin Paradox. What is this paradox? It is the juxtaposition of three observations: 1) Within a society, rich people tend to be much happier than poor people. 2) But, rich societies tend not to be happier than poor societies (or not by much). 3) As countries get richer, they do not get happier.

Easterlin offered an appealing resolution to his paradox, arguing that only relative income matters to happiness. Other explanations suggest a “hedonic treadmill,” in which we must keep consuming more just to stay at the same level of happiness.

We have re-analyzed all of the relevant post-war data, and also analyzed the particularly interesting new data from the Gallup World Poll. Last Thursday we presented our research at the latest Brookings Panel on Economic Activity, and we have arrived at a rather surprising conclusion: There is no Easterlin Paradox. The facts about income and happiness turn out to be much simpler than first realized: 1) Rich people are happier than poor people. 2) Richer countries are happier than poorer countries. 3) As countries get richer, they tend to get happier.

1. Putting a price on carbon is not only about the climate.Yes, humans are affecting the climate and reducing carbon dioxide emissions is a key commitment of this government, and indeed the stated views of the opposition. But there are other reasons to price carbon, primarily to put Australia at the forefront of a global energy technology revolution that is already underway.In future years and decades the world is going to need vastly more energy that is secure, reliable, clean and affordable. Achieving these outcomes will require an energy technology revolution. The purpose of pricing carbon is to raise the revenues needed to invest in this future, just as we invest in health, agriculture and defence.

2. A price on carbon raises revenues to invest in stimulating that energy technology revolution.Australia emits almost 400 million tonnes of carbon dioxide into the atmosphere every year. In round numbers, every dollar carbon tax per tonne on those emissions would raise about A$100 million. A significant portion of the proceeds from a carbon tax should be used to invest in energy technology innovation, using today’s energy economy to build a bridge to tomorrow’s economy. This is exactly the strategy that India has adopted with a small levy on coal and Germany has adopted with a tax on nuclear fuel rods, with proceeds in both instances invested into energy innovation.

3. The purpose of a carbon tax is not to make energy, food, petrol or consumer goods appreciably more expensive.Just as scientists are in broad agreement that humans are affecting the global climate, economists and other experts are in broad agreement that we cannot revolutionise our energy economy through pricing mechanisms alone. Thus, we propose starting with a low carbon tax - one that has broad political support - and then committing to increasing it in a predictable manner over time.The Coalition has proposed a “direct action plan” on carbon policy that would cost A$30 billion over the next 8 years, which is the equivalent of about a $2.50 per tonne carbon tax. The question to be put to the Coalition is not whether we should be investing in a carbon policy, as we agree on that point, but how much and how it should be paid for. The Coalition’s plans leave unanswered how they would pay for their plan.A carbon tax offers a responsible and effective manner to raise funds without harming the economy or jobs. In fact, to the extent that investments in energy innovation bear fruit, new markets will be opened and new jobs will be created. The Coalition’s plan is not focused on energy technology innovation.The question for the Coalition should thus be, at what level would you set a carbon tax (or what other taxes would you raise?), and how would you invest the proceeds in a manner that accelerates energy technology innovation?