Group items tagged

Studies of the effects of alcohol consumption on health outcomes should recognise the methodological biases they are likely to face, and design, analyse and interpret their studies accordingly. While regular moderate alcohol consumption during middle-age probably does reduce vascular risk, care should be taken when making general recommendations about safe levels of alcohol intake. In particular, it is likely that any promotion of alcohol for health reasons would do substantially more harm than good.

. The consistency in the vascular benefit associated with moderate drinking (compared with non-drinking) observed across different studies, together with the existence of credible biological pathways, strongly suggests that at least some of this benefit is real.

However, because of biases introduced by: choice of reference categories; reverse causality bias; variations in alcohol intake over time; and confounding, some of it is likely to be an artefact. For heavy drinking, different study biases have the potential to act in opposing directions, and as such, the true effects of heavy drinking on vascular risk are uncertain. However, because of the known harmful effects of heavy drinking on non-vascular mortality, the problem is an academic one.

What about depression? Is it impossible to define or study this state of mind empirically? I'm not sure how deep Carroll's skepticism runs, but much of psychology now appears to hang in the balance. Of course, Carroll might want to say that the problem of access to the data of first-person experience is what makes psychology often seem to teeter at the margin of science. He might have a point -- but, if so, it would be a methodological point, not a point about the limits of scientific truth. Remember, the science of determining exactly which books were in the Library of Alexandria is stillborn and going absolutely nowhere, methodologically speaking. But this doesn't mean we can't be absolutely right or absolutely wrong about the relevant facts.

While I'm happy to admit that people are morally confused, I see no evidence whatsoever that they all ultimately want the same thing. The position doesn't even seem coherent. Is it a priori necessary that people ultimately have the same idea about human well-being, or is it a contingent truth about actual human beings?

I might find that brain state X242358B is my absolute favorite, and Carroll might prefer X979793L, but the fear that we will radically diverge in our judgments about what constitutes well-being seems pretty far-fetched. The possibility that my hell will be someone else's heaven, and vice versa, seems hardly worth considering. And yet, whatever divergence did occur must also depend on facts about the brains in question.

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.

By Carlin Romano Standing up for science excites some intellectuals the way beautiful actresses arouse Warren Beatty, or career liberals boil the blood of Glenn Beck and Rush Limbaugh. It's visceral.

A brave champion of beleaguered science in the modern age of pseudoscience, this Ayn Rand protagonist sarcastically derides the benighted irrationalists and glows with a self-anointed superiority. Who wouldn't want to feel that sense of power and rightness?

You hear the voice regularly—along with far more sensible stuff—in the latest of a now common genre of science patriotism, Nonsense on Stilts: How to Tell Science From Bunk (University of Chicago Press), by Massimo Pigliucci, a philosophy professor at the City University of New York.

This post is about how one should deal with a denialist of Delingpole's ilk.

I saw someone I follow on Twitter retweet an update from another Twitter user called @AGW_IS_A_HOAX, which was this: "NZ #Climate Scientists Admit Faking Temperatures http://bit.ly/fHbdPI RT @admrich #AGW #Climategate #Cop16 #ClimateChange #GlobalWarming".

So I click on it. And this is how you deal with a denialist claim. You actually look into it. Here is the text of that article reproduced in full: New Zealand Climate Scientists Admit To Faking Temperatures: The Actual Temps Show Little Warming Over Last 50 YearsRead here and here. Climate "scientists" across the world have been blatantly fabricating temperatures in hopes of convincing the public and politicians that modern global warming is unprecedented and accelerating. The scientists doing the fabrication are usually employed by the government agencies or universities, which thrive and exist on taxpayer research dollars dedicated to global warming research. A classic example of this is the New Zealand climate agency, which is now admitting their scientists produced bogus "warming" temperatures for New Zealand. "NIWA makes the huge admission that New Zealand has experienced hardly any warming during the last half-century. For all their talk about warming, for all their rushed invention of the “Eleven-Station Series” to prove warming, this new series shows that no warming has occurred here since about 1960. Almost all the warming took place from 1940-60, when the IPCC says that the effect of CO2 concentrations was trivial. Indeed, global temperatures were falling during that period.....Almost all of the 34 adjustments made by Dr Jim Salinger to the 7SS have been abandoned, along with his version of the comparative station methodology."A collection of temperature-fabrication charts.

The authors suggest that there are two publics for science communication, one that is liberal, educated and with a number of resources at its disposals; the other with less predictable and less-formed opinions. The authors explored empirically (via a survey of 108 Colorado citizens) the responses of liberal and educated people to scientific jargon by exposing them to two “treatments”: jargon-laden vs lay terminology news articles. The results found that scientists were considered the most credible sources in the specific area of environmental science (94.3% agreed), followed by activists (61.1%). The least credible were industry representatives, clergy and celebrities. (Remember, this is among liberal educated people.) Interestingly, the use of jargon per se did not increase acceptance of the news source or of the content of the story. So the presence of scientific expertise is important, not so the presence of actual scientific details in the story.

There is no complete account of the scientific method, and again one can choose certain methods rather than others, depending on what one is trying to accomplish (a choice that is itself informed by one’s values). And of course the Duhem-Quine thesis shows that there is no straightforward way to falsify scientific theories (contra Popper). If there were supernatural causes that interact with (or override) the causes being studied by science, but are themselves undiscoverable, this would lead to false conclusions and bad predictions. Which means that the truth is discoverable empirically only if such supernatural causes are not active. Science cannot answer the question of whether such factors are present, which raises the question of whether we ought to proceed as if they were not (i.e., methodological naturalism).

Internet surveys sometimes acknowledge how unscientific (read: meaningless) they really are. They surely must be a pale imitation of the rigorous, carefully sampled, thoroughly transparent polls favored by political savants and mainstream news organizations

The line between junk and credible polling remains. But it became a little blurrier — creating concern among professional survey organizations and reason for greater skepticism by all of us — because of charges this week that one widely cited pollster may have fabricated data or manipulated it so seriously as to render it meaningless.

founder of the left-leaning Daily Kos website, filed a lawsuit in federal court in Oakland on Wednesday charging that Research 2000, the organization he had commissioned for 1 1/2 years to test voter opinion, had doctored its results.

Each group found extensive methodological holes in the evidence they disagreed with, but ignored the very same holes in the evidence that reinforced their views.

Some people go even further than this when presented with unwelcome data, and decide that science itself is broken.

history of voting math comes mainly in two chunks: the period of the French Revolution, when some members of France’s Academy of Sciences tried to deduce a rational way of conducting elections, and the nineteen-fifties onward, when economists and game theorists set out to show that this was impossible

The first mathematical account of vote-splitting was given by Jean-Charles de Borda, a French mathematician and a naval hero of the American Revolutionary War. Borda concocted examples in which one knows the order in which each voter would rank the candidates in an election, and then showed how easily the will of the majority could be frustrated in an ordinary vote. Borda’s main suggestion was to require voters to rank candidates, rather than just choose one favorite, so that a winner could be calculated by counting points awarded according to the rankings. The key idea was to find a way of taking lower preferences, as well as first preferences, into account.Unfortunately, this method may fail to elect the majority’s favorite—it could, in theory, elect someone who was nobody’s favorite. It is also easy to manipulate by strategic voting.

If the candidate who is your second preference is a strong challenger to your first preference, you may be able to help your favorite by putting the challenger last. Borda’s response was to say that his system was intended only for honest men.

Columnist David Leonhardt reports the findings of a new study which suggests that children who are fortunate enough to have an unusually good kindergarten teacher can expect to make roughly an extra twenty dollars a week by the age of twenty-seven.

it implies that during each school year a good kindergarten teacher creates an additional $320,000 of earnings.

The new research (pdf), the work of six economists—four from Harvard, one from Berkeley, and one from Northwestern—upends this finding. It is based on test scores and demographic data from a famous experiment carried out in Tennessee during the late nineteen-eighties, which tracked the progress of about 11,500 students from kindergarten to third grade. Most of these students are now about thirty years old, which means they have been working for up to twelve years. The researchers also gained access to income-tax data and matched it up with the test scores. Their surprising conclusion is that the uplifting effect of a good kindergarten experience, after largely disappearing during a child’s teen years, somehow reappears in the adult workplace. (See Figure 7 in the paper.) Why does this happen? The author don’t say, but Leonhardt offers this explanation: “Good early education can impart skills that last a lifetime—patience, discipline, manners, perseverance. The tests that 5-year-olds take may pick up these skills, even if later multiple-choice tests do not.”

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?”

Some have argued that piracy is rampant in those countries where the online Android Market is not yet available. But a recent KeyesLabs research project suggests that may not be true. KeyesLabs created a rough methodology to track total downloads of its apps, determine which ones were pirated, and the location of the end users. The results were posted in August, along with a “heat map” showing pirate activity. 

In July 2010, Google announced the Google Licensing Service, available via Android Market. Applications can include the new License Verification Library (LVL). “At run time, with the inclusion of a set of libraries provided by us, your application can query the Android Market licensing server to determine the license status of your users,” according to a blog post by Android engineer Eric Chu. “It returns information on whether your users are authorized to use the app based on stored sales records.”

Justin Case, at the Android Police Web site, dissected the LVL. “A minor patch to an application employing this official, Google-recommended protection system will render it completely worthless,” he concluded.

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.

Lever-Tracy confronted sociologists head on about their worrisome silence on the issue. Why have sociologists failed to address the greatest and most overwhelming challenge facing modern society? Why have the figureheads of the discipline, such as Anthony Giddens and Ulrich Beck, so far refused to apply their seminal notions of structuration and the risk society to the issue?

Earlier, we re-published an important contribution by Ulrich Beck, the world-renowned German sociologist and a Breakthrough Senior Fellow. More recently, Current Sociology published a powerful response by Reiner Grundmann of Aston University and Nico Stehr of Zeppelin University.

sociologists should not rush into the discursive arena without asking some critical questions in advance, questions such as: What exactly could sociology contribute to the debate? And, is there something we urgently need that is not addressed by other disciplines or by political proposals?

Mendick, H. and Moreau, M. (2010). Monitoring the presence and representation of  women in SET occupations in UK based online media. Bradford: The UKRC.

Mendick and Moreau considered the representation of women on eight ‘SET’ (science, engineering and technology) websites: New Scientist, Bad Science, the Science Museum, the Natural History Museum, Neuroskeptic, Science: So What, Watt’s Up With That and RichardDawkins.net. They also monitored SET content across eight more general sites: the BBC, Channel 4, Sky, the Guardian, the Daily Mail, Wikipedia, YouTube and Twitter.

Their results suggest online science informational content is male dominated in that far more men than women are present. On some websites, they found no SET women. All of the 14 people in SET identified on the sampled pages of the RichardDawkins.net website were men, and so were all 29 of those mentioned on the sampled pages of the Channel 4 website (Mendick & Moreau, 2010: 11).

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.

I predict that you will find this review informative. If you do, you will congratulate my foresight. If you don’t, you’ll forget I was wrong.

My playful intro summarizes the main thesis of Gardner’s excellent book, Future Babble: Why Expert Predictions Fail – and Why We Believe Them Anyway.

In Future Babble, the research area explored is the validity of expert predictions, and the primary researcher examined is Philip Tetlock. In the early 1980s, Tetlock set out to better understand the accuracy of predictions made by experts by conducting a methodologically sound large-scale experiment.

[UPDATE: Gavin Schmidt at Real Climate has a post on this subject that  -- surprise, surprise -- is perfectly consonant with what I write below.] [UPDATE 2: Andy Revkin has a great post on the representations of the precipitation paper discussed below by scientists and related coverage by the media.]  

Nature published two papers yesterday that discuss increasing precipitation trends and a 2000 flood in the UK.  I have been asked by many people whether these papers mean that we can now attribute some fraction of the global trend in disaster losses to greenhouse gas emissions, or even recent disasters such as in Pakistan and Australia.

I hate to pour cold water on a really good media frenzy, but the answer is "no."  Neither paper actually discusses global trends in disasters (one doesn't even discuss floods) or even individual events beyond a single flood event in the UK in 2000.  But still, can't we just connect the dots?  Isn't it just obvious?  And only deniers deny the obvious, right?

The Guardian has an good article today on a threatened libel suit under UK law against Gavin Schmidt, a NASA researcher who blogs at Real Climate, by the publishers of the journal Energy and Environment. 

Here are my full comments to the reporter for the Guardian, who was following up on Gavin's reference to comments I had made a while back about my experiences with E&E:

In 2000, we published a really excellent paper (in my opinion) in E&E in that has stood the test of time: Pielke, Jr., R. A., R. Klein, and D. Sarewitz (2000), Turning the big knob: An evaluation of the use of energy policy to modulate future climate impacts. Energy and Environment 2:255-276. http://sciencepolicy.colorado.edu/admin/publication_files/resource-250-2000.07.pdf You'll see that paper was in only the second year of the journal, and we were obviously invited to submit a year or so before that. It was our expectation at the time that the journal would soon be ISI listed and it would become like any other academic journal. So why not publish in E&E?