HOW BAD IS THE GOVERNMENT’S SCIENCE? (It's worse than we thought.)

From the National Association of Scholars via an article in the Wall Street Journal.

Policy makers often cite research to justify their rules, but many of those studies wouldn’t replicate

 

Half the results published in peer-reviewed scientific journals are probably wrong. John Ioannidis, now a professor of medicine at Stanford, made headlines with that claim in 2005. Since then, researchers have confirmed his skepticism by trying—and often failing—to reproduce many influential journal articles. Slowly, scientists are internalizing the lessons of this irreproducibility crisis. But what about government, which has been making policy for generations without confirming that the science behind it is valid?

The biggest newsmakers in the crisis have involved psychology. Consider three findings: Striking a “power pose” can improve a person’s hormone balance and increase tolerance for risk. Invoking a negative stereotype, such as by telling black test-takers that an exam measures intelligence, can measurably degrade performance. Playing a sorting game that involves quickly pairing faces (black or white) with bad and good words (“happy” or “death”) can reveal “implicit bias” and predict discrimination.

All three of these results received massive media attention, but independent researchers haven’t been able to reproduce any of them properly. It seems as if there’s no end of “scientific truths” that just aren’t so. For a 2015 article in Science, independent researchers tried to replicate 100 prominent psychology studies and succeeded with only 39% of them.

Further from the spotlight is a lot of equally flawed research that is often more consequential. In 2012 the biotechnology firm Amgen tried to reproduce 53 “landmark” studies in hematology and oncology. The company could only replicate six. Are doctors basing serious decisions about medical treatment on the rest? Consider the financial costs, too. A 2015 study estimated that American researchers spend $28 billion a year on irreproducible preclinical research.

The chief cause of irreproducibility may be that scientists, whether wittingly or not, are fishing fake statistical significance out of noisy data. If a researcher looks long enough, he can turn any fluke correlation into a seemingly positive result. But other factors compound the problem: Scientists can make arbitrary decisions about research techniques, even changing procedures partway through an experiment. They are susceptible to groupthink and aren’t as skeptical of results that fit their biases. Negative results typically go into the file drawer. Exciting new findings are a route to tenure and fame, and there’s little reward for replication studies.

American science has begun to face up to these problems. The National Institutes of Health has strengthened its reproducibility standards. Scientific journals have reduced the incentives and opportunities to publish bad research. Private philanthropies have put serious money behind groups like the Meta-Research Innovation Center at Stanford, led in part by Dr. Ioannidis, and the Center for Open Science in Charlottesville, Va.

There’s more to be done, and the National Association of Scholars has made some recommendations. Before conducting a study, scientists should “preregister” their research protocols by posting the intended methodology online, which eliminates opportunities for changing the rules in the middle of the experiment. High schools, colleges and graduate schools need to improve science education, particularly in statistics. Universities and journals should create incentives for researchers to publish negative results. Scientific associations should seek to disrupt disciplinary groupthink by putting their favored ideas up for review by experts in other sciences.

All government agencies should review the scientific justifications for their policies and regulations to ensure they meet strict reproducibility standards. The economics research that steers decisions at the Federal Reserve and the Treasury Department needs to be rechecked. The social psychology that informs education policy could be entirely irreproducible. The whole discipline of climate science is a farrago of unreliable statistics, arbitrary research techniques and politicized groupthink.

Read the full story here 


Mr. Wood is president of the National Association of Scholars. Mr. Randall is the NAS’s director of research and a co-author of its new report, “The Irreproducibility Crisis of Modern Science.

A reproducibility crisis afflicts a wide range of scientific and social-scientific disciplines, from epidemiology to social psychology. Improper use of statistics, arbitrary research techniques, lack of accountability, political groupthink, and a scientific culture biased toward producing positive results together have produced a critical state of affairs. Many supposedly scientific results cannot be reproduced in subsequent investigations.

This study examines the different aspects of the reproducibility crisis of modern science. The report also includes a series of policy recommendations, scientific and political, for alleviating the reproducibility crisis.

 

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160 thoughts on “HOW BAD IS THE GOVERNMENT’S SCIENCE? (It's worse than we thought.)

  1. Federally-funded research is guided by the distribution of research funds
    1. Funds are limited to research studies that support standard models of Nature

    • Well, you get what you pay for. The gov’t likes to pay scientists to scare, as a result we’ve lots of scaredy cats. Emotion gets the job done where reason doesn’t.
      Actual science is having a rather abused life, given gov’t johns and prostitute scientists are claiming the ‘street’ domain.

    • Thank you omanuel. You are correct. But if you want to see vile hatred, deliberate attacks, and chicanery of all types, just try to publish a paper straying too far from the standard models of Nature. And the standard models of Statistics.
      Another thing hurting is people using statistics to deceive not enlighten. This is done out of ignorance or malice, but the results are the same. People will claim that the lower the p value the greater the significance of the results (even approaching the TRUTH). Far too many scientists have no idea of the relationships between Type 1 and Type 2 errors. They need to consult any good probability and statistics book. The best books are probably not Statistics in _____) but just probability and statistics.

      • To illustrate:
        The Arctic Sea Ice oscillates between 3 Mkm^2 and 14 Mkm^2 every year. It has been decreasing recently through the satellite era, but we have not gone through even half of a single PDO or AMO cycle. We simply do not know what its usual cycle is – if indeed the Arctic sea ice has period changes in extent and thickness – nor the length of even one cycle, much less several cycles to make an estimate of the average length.
        The Antarctic sea ice also oscillates between 3.0 Mkm^2 and 18 Mkm^2, but has been increasing steadily since 1992.
        But the CAGW propagandists report “Artic sea ice has decreased 30%” using the MINIMUM sea ice values and a starting point at an all-time high period in 1979-1983!
        Thus, they emphasize the MAXIMUM percent sea ice change: -1.5 Mkm^2 from 4.0 Mkm^2 is a much larger (More impressive!) decrease than a 1.5 Mkm^2 decrease from 14.0 Mkm^2 maximum, isn’t it?
        But it is only a 7% decrease of sea ice maximum over the entire 38 year-long record.
        But the Antarctic sea ice increase is trivialized by reporting ONLY the decadal rate of the Antarctic sea ice MAXIMUM!
        In truth, the excess sea ice around Antarctica as recently as 2014 was larger than the entire area of Greenland. But the CAGW publicity-fundraising-crisis manufacturing machine does not want that fact known.

  2. Yes, I’ve bookmarked retractionwatch.wordpress.com, but as I’ve noticed “climate science” seems to be getting a pass there.
    Its a miracle that the (in many ways) least understood and arguably newest “science” gets it correct when some sciences that are centuries (or more) older are having so much trouble…

    • No one dares even mention CliSci in a negative way …. career destroying attacks quickly follow.

      • and we both (we all….) know that the list, with your name at the top, is long with good men and women whose careers have been intentional destroyed, in some cases by paid political operatives, for speaking out.

      • The basic problem is that apart from many researchers not understanding statistics (what the p score and CHI squared statistic really mean) is that the base tests should be run at the 5 sigma level instead of the 2 sigma level that a lot of sciences are using. I realize that the costs involved to run at 5 sigma are much greater but what do you want? Cheap flawed science or expensive good science. What has happened is that we went for the cheap science but that ultimately leads to 100% failure to reproduce results.

      • Like flying in the Space Shuttle.
        A Machine with 2,500,000 moving parts built by the Lowest Bidder

      • Anthony,
        I don’t think your career has been destroyed by Mann. You are now one of the most well known and respected meteorologist in modern history. There is not a meteorologist or “climate scientist” on the planet that doesn’t know your name or WUWT. But, I understand where you’re coming from.
        Engineers, physicists and many other interested parties know your name and respect you for speaking out. Your efforts will long outlive you!

      • Hi Kip, I was just today thinking I hadn’t seen you around or a while.
        What exactly do you mean by ‘mention CliSci in a negative way”?
        “and we both (we all….) know that the list, with your name at the top, is long with good men and women whose careers have been intentional destroyed, in some cases by paid political operatives, for speaking out.”
        Who are these paid political operatives? Paid by whom? Of course, “mainstream” scientists have been harrassed by the government, too.
        I don’t actually know that list. Could you give a few examples, and how it happened? I’m interested. I wonder in particular how often it was a matter of disagreeing with the science, and how often it went beyond that. Thanks. I know the story of Dr. Ridd, that doesn’t seem to qualify. Judith Curry left, but was her career “intentionally destroyed”?
        That’s quite an accusation. I don’t know Anthony’s history.

      • @Kristi Silber
        just an example. now do your home work and find others all by yourself. You see, you shouldn’t rely on information source you don’t actually trust, like people here. You should think by yourself, not parroting any side opinion, and that includes finding relevant information yourself. Most of the time, people won’t spread blatant falsehood, they will omit inconvenient truth, and rely on ignorant people to spread it further in good faith (like yourself: no offense, but you are ignorant, which is easily cured if you will…).
        https://wattsupwiththat.com/2018/04/09/pielke-harasser-judd-legum-turns-tail-and-runs-from-debate-challenge/
        paid operative: Judd Lugum
        payer: Center for American Progress (CAP)
        Why do you think Ridd doesn’t qualify? Would even Galileo qualify, as per your standard?

      • @Kristi Silber
        There was also Emeritus Professor Bob Carter of James Cook University o
        fNorth Queensland (my alma mater, much to my chagrin, after the way they treated him). Though I guess, as he was Emeritus Professor his career wasn’t destroyed. However, in an act that was truly petty, spiteful and vindictive, they revoked the few perks he had by way of his Emeritus status.

    • It gets a pass because none of the climate scientists are policing their discipline in the way other scientists police theirs. It is one of the key reasons I am sceptical.

      • There are people who police climate “science”. Just try to publish a paper that conflicts with the “consensus” and see how fast your career is destroyed.

      • Yes, when the so-called “scientists” are all nodding in approval of each other’s work, you know it isn’t *actual* science.

    • Retraction Watch monitors retractions.
      A climate paper may be crap, but, unless it’s retracted, it won’t appear on that web site. And teh Climat gang would never allow a paper to be retracted. The Mann et al hockey stick is a case in point – it’s obviously wrong, no one uses it any more, but it won’t get retracted…

  3. Pfffft. Science isn’t about reproducibility… It’s entirely about funding. Just ask any Climate scientist.

      • I see your game… and you won’t get away with it. The reproducibility of climate science funding consensus means it cannot be about science… therefore it is all about the funding in climate science.
        :p

      • No, wait… the reproducibility of climate science funding consensus means it cannot be about science or funding, so it’s all about the reproducibility of consensus. But the consensus of reproducibility of consensus means it cannot be about reproducibility or consensus, so it’s about nothing whatsoever… or something.
        Now I’m confused.

    • Government science is not about reproducibility. Science is related to a government science just as a jacket is related to a straitjacket.

    • And funding is decided by politicians, or their appointees.
      How many have even a decent scientific back-ground?
      Say to age 18 – I am not asking Doctorates or Masters – but just knowing scientific method – the Feynman video covers that well in a few minutes!
      Auto

  4. How is climate “science” doing on that scorecard? Lol!
    It’s pretty bad when all the peer reviewers and people who might attempt replication are your friends and use the same jiggered data and lousy methodology and can’t reproduce your results but I suspect that is the state of things.
    I can’t see how any genuine researcher could replicate Mann’s work without a massive fiddle.

  5. There’s too many examples of “science” that has been proven wrong….that is not retracted

    • From the last paragraph of the article: “All government agencies should review the scientific justifications for their policies and regulations…” Let’s start with the EPA’s Endangerment Finding.

    • The number of successful geoengineering projects have been very limited ( cloud seeding , building dams and levees ….etc) but still; that qualifies as a separate science as does meteorology. However climate science should not exist as a separate discipline since it takes knowledge of about 20 disciplines to even have a basic understanding. Moreover, there is nothing we can do about the climate and since the whole of climate science is now based on flawed computer simulations, universities should not allow any university resources to be used in any study that uses computer simulations and thus not allow funding for it in the 1st place.

  6. And, those irreproducible studies have been cited in so many follow on studies which in turn have been cited many times, which in turn…
    Just like with the climate models, we simply do not have enough computing power to unravel this confusion.

    • You are right, but the real dirty little secret is we will never have the computing power to unravel the confusion.

  7. I’d be curious, as a non-scientist, to know how much of this publication of non-replicable studies, i.e., studies that draw incorrect conclusions, is due to an outlier effect. A study that produces an outcome that falls in the tail of the distribution of possible outcomes is surprising, and is therefore interesting, and is published.
    I read of this phenomenon in the comments of WUWT years ago and it struck me as reasonable. If 50% of studies produce an incorrect result, couldn’t that be because it’s far easier to get an outlier result, i.e., an unexpected result, published? (And spread far and wide as “Breaking News!!”)

    • Rod ==> This is a very hot topic in medical research and psychology in particular. There are a lot of studies on the why’s and and in what ways the studies go astray. A little Googling will bring you enough to read for a month or so. Start with Ioannidis .

    • There are lots of reasons, including publication bias (publishing positive results but not negative) and the awful p hacking and correlation fishing that goes on.
      I think it was one on of the cardiac journals that changed its policy a year or two ago and said it would only publish papers where what was being looked for was stated BEFORE the study took place. The number of studies with positive correlations fell from well over 60% to under 10%.

      • Like the “No Stairway” sign in the Wayne’s World guitar shop, they ought to put up a “No Texas Sharpshooter” sign in their submissions office.

      • Rod, to add to Phoenix’s comment, another idea that’s been floated (and practiced) is having researchers submit their rationale, justification and some background as well as methods, and if accepted, the journal would guarantee publication before the study began. This would eliminate the problem of negative results not getting published.
        As Kip implied, it’s important to remember that the problems are worse in some fields than others. There are a ton of papers in medicine that have very small sample sizes. Control groups aren’t always possible. Medical doctors may not have a good grounding in experimental design and statistics.
        And of course, the social sciences are infamously “soft.”
        Proper use of statistics is way harder than it looks. Some research groups – climate modelers, for instance – include statisticians with the kind of expertise needed for complex studies. This is one reason I argue that expertise is important, and laymen seldom have the depth of knowledge and experience to practice meaningful, original science. The kind of knowledge one needs these days can be so esoteric, even those in related fields don’t have the same understanding.
        That said, I don’t think the situation is quite as bad as it seems. I have read the paper about the “50% of studies are wrong.” It’s based on hypothesis and calculation, sometimes using arbitrary quantities to represent a parameter: 10% bias, for example. The paper makes many good points about problems in research, but few were news, and the title was “alarmist.” it got huge press, of course. Some questioned whether his paper were part of the false 50%.

        • Proper use of statistics is way harder than it looks. Some research groups – climate modelers, for instance – include statisticians with the kind of expertise needed for complex studies.

          Proper use of statistics is way harder than it looks. SomeA few research groups – but no climate modelers (that we know of), for instance – include statisticians with the kind of expertise needed for complex studies.

    • Rod, John Ioannidis paper “Why most published published research is false” is available at http://www.google.com/url?q=http://journals.plos.org/plosmedicine/article%3Fid%3D10.1371/journal.pmed.0020124&sa=U&ved=0ahUKEwiWx6GP3cHaAhVruVkKHWnmCUEQFggZMAA&usg=AOvVaw1wsApJxX7HgiWhiIJZ0Yhs It’s well worth reading, but it’s tough going.
      Rather remarkably,It was well received and the medical folk at least seem to be trying to do better. Ioannidis wrote a ocuple of follow-up papers BTW.
      One thing though. The paper primarily addresses experimental science. You run an experiment, analyze, and report the results. Most climate “research” doesn’t involve experimentation. It’s more like Geology and Astrophysics. It consists of analyzing (often dubious) existing data or of running elaborate unvalidated computer models. The problems that Ioannidis identified with experimentation — especially statistical naivete — often seem to show up in Climate Science, but not in the same way. And there appear to be a bunch of largely unacknowledged problems unique to observational science.
      And Climate Scientists, unlike medical researchers, definitely do NOT like to be told that they might not know what they are doing.

    • The existence of JIR suggests that scientists of previous decades knew that some published research was bad. Unable or unwilling to call it out in a serious way, they took to mockery. However, instead of causing a serious look at reproducibility, JIR made it easier to laugh off the misfeasance.

  8. The biggest myth going around for the last 100 years is that drugs cause addiction. There is no evidence for that.
    Addiction is a symptom of PTSD. Look it up.
    Dr. Lonny Shavelson found that 70% of female heroin addicts were sexually abused in childhood.

    • …Dr. Lonny Shavelson found that 70% of female heroin addicts were sexually abused in childhood…..
      Not a proper statistical argument on its own – this statement shows us in a nutshell what is wrong with using stats.
      Supposing that normally, 80% of females reported being sexually abused in childhood? Which is certainly possible, in teh current climate. Then, 70% begins to look below average…

      • Another possibility is that those who were sexually abused in childhood were more likely to try drugs.

      • or even that children who were likely to try/overdo drugs came from an environment that was more likely to lead to abuse.

    • This is an interesting idea. To be sure, there is such a thing as chemical dependence, but it may be much easier to break without and underlying emotional trauma. It would also explain why no everyone who has taken an addictive substance becomes “hooked” or why the addictive effect varies wildly between individuals. Also why some people can become addicted to non-addictive substances and behaviors.
      As part of a college class, I was required to attend an AA meeting. Nearly all the recovering alcoholics appeared to be heavy smokers and coffee drinkers – if the meeting was a reasonable example of their normal habits. I’ve often wondered if they were just trading one addiction for another. If solving their PTSD (or other psychological) issues would help end their addictions, this could help many people. I hope this approach is being studied.

      • There are definite differences in population sub-groups. Native Americans and the Irish have statistically greater rates of alcohol addiction, for instance. There is no commonality of socio-economic grouping, so it suggests, not proves, there is a genetic component that interacts with alcohol intake.

      • It is very hard to argue that tobacco does not cause addiction. I have seen it over a lifetime where a lot of my friends started off slowly smoking and soon had cravings that could not be stopped. Of course some people can stop cold turkey but for most it is a losing game. Also there are some modern drugs where after 1 dose you would sell your own mother for another fix.

    • Careful, you are treading very dangerous ground. After all, we can’t be pushing for drug legalisation since it is ‘not chemically addictive’ and still continue the narrative that the good’ole englishmen intentionally plied north american indians with alcohol to exploit their genetic pre-disposition, but this is getting off topic.
      On the vane of good climate science and bad faith, maybe there is a study that shows certain races of people exhale less C02 than others and are therefore holier than others.

    • We have dozens of automatic homeostatic processes that attempt to keep our bodies in a sustainable, balanced state of health. When you introduce a foreign chemical like a recreational drug, it tilts the scale. In the mind of the user, the “high” is pleasant and desirable, but to the body it’s an unsustainable state and undesirable. So the body works to restore homeostasis by adjusting the aforementioned processes to account for the drug. This is colloquially known as “gaining a tolerance”. When the drug is no longer present, the body starts to roll back the changes, but until it does you feel terrible, even to the point of becoming seriously ill. This is colloquially known as “withdrawal symptoms” or in the case of alcohol, “a hangover”. Alcohol is somewhat unique in that it metabolizes out of the body so quickly (within 24 hours in most cases), that even steady drinkers rarely build up a significant tolerance.
      Drug addiction can be just as much about “running from the crash” as about “chasing the high”.

      • A hangover, medical term veisalgia, is a combination of symptoms. Withdrawal may be a part of it, but the symptoms felt by most are headache and nausea. The headache is caused by vasodilation and inflammation induced by the alcohol. The vasodilation causes the “sinus headache” portion of the hangover. The inflammation causes the headache at the base of the skull. Oral decongestants and anti-inflammatory medications can alleviate and even prevent nearly all hangover symptoms.
        Nausea is caused by alcohol induced stimulation of the chemoreceptor trigger zone. Overstimulate the CTZ and nausea/vomiting result.

    • Or addiction in parents leads both to abuse of offspring and the model for their addiction.
      The idea that addiction comes from PTSD has been shot down by the opium epidemic, which can strike people of all backgrounds. It’s a greater killer than road accidents. And we still don’t have a drug czar.
      Drugs don’t necessarily cause addiction, but some drugs are definitely addictive.

  9. Recognizing this is fine, except beware the cures. Possible problems in some fields include rare events, unpopular area for funding (lack of researcher control over process), inappropriate for statistical analysis, lack of a real problem, changes in study environment, difficulty in precise standardization, etc. Then I looked at the article summary.
    For example–“Uncontrolled researcher freedom makes it easy for researchers to err in all the ways described above.” …”6. Researchers should pre-register their research protocols, filing them in advance with an appropriate scientific journal, professional organization, or government agency. 7. Researchers should adopt standardized descriptions of research materials and procedures.”
    Science went down with such centralized control. Works fine with easy to standardize situations, others not. One might think those in medicine would know about curing symptoms. Might keep you alive though. Some suggestions Ok, but this needs real peer review.

    • HDHoese ==> “6. Researchers should pre-register their research protocols, filing them in advance with an appropriate scientific journal, professional organization, or government agency.” A huge part of the problem is failures in study design — and the pre-registration of study design allows peers to review the design, point out faults that will make the study irreproducible or irrelevant, and defines what end points are being looked at, statistical methods to be used to analyze results, etc. [This doesn’t apply to “blue-sky” research, of course].
      Ocean Acidification research wasted years and a lot of money before the field self-regulated to standardize and establish appropriate methods — most researchers didn’t even have the basic sea-water chemistry right. Those that did could have helped those that has grants but lacked the necessary knowledge.
      A lot of medical research that is garbage is the result of data torturing — data dredging — in attempts to find something — anything — “publishable” from some long-term expensive study that in reality, found nothing at all interesting. Post Hoc redesigning of a study to get a result.

      • Back in the early 1980s I spent a week working and learning from one of the top biometricians in the country. He was the chief statistical consultant for several medical research institution. We had lunch most days that week. He told me and others in the class he was teaching at our marine research institution that medical doctors were some of the worst scientists he had ever dealt with. He was on retainer, they could call him at any time. He held meeting each year at each institution to advise them of his services and they should come to him during the experimental design phase. Yet the doctors would still conduct research or do an “experiment” and then after they were finish come to him and say, “Now what statistics should I use?” He told me that if it happened just once it would have been one thing but some went through this scenario repeatedly. Some would even get angry when he told them he couldn’t help them.

        • Edwin ==> One of the major recommendation is that experimental design include what statistical methods will be used — and why — to analyze the resultant data.
          Your friend is absolutely correct — the use of ad hoc statistics means the experiment is already compromised.

      • KH
        You are entirely correct. We had a good statistics department where we sent students to help with design. When the ocean pH nonsense started I got into it as a reviewer for the NIPCC. I thought I didn’t know much about it until I read a number of papers. Having centralized reviewers that know little of the basics won’t help, I would argue, and as others note problems with post hoc application and statistics shopping used to be well known.
        I worked with a couple of very good government modelers and many scientists. When you run into a bad one, they are really, really bad. Back in those days we did not have press releases and I may have been wrong thinking that we needed to put out more good science to the public. Best available ‘science’ can have lots of problems.
        Edwin
        We have a doctor with a hobby, he says, to read the medical literature. He is very good and admits shortcomings. We hope he will survive the deluge of paperwork.

      • “most researchers didn’t even have the basic sea-water chemistry right.”
        I think peer review is supposed to catch problems like acidifying with hydrocholoric acid instead of CO2 /arbonic acid when you are studying carbonate chemistry. But it doesn’t seem to have done so. That seems to me to be a bit disconcerting. Hard not to conclude that the peer review process is broken.

      • Edwin, that doesn’t surprise me at all. Doctors aren’t taught how to do science, they are taught how to cure people. They might study some statistics for epidemiology, but not things like experimental design. I imagine in some instances they did some procedures, found something interesting, then wanted to publish it. Which is fair enough, but it’s observation rather than science.
        Kip, I think the idea of publishing methods online before the study has the fatal flaw that people could steal ideas. It’s a matter of intellectual property rights. The methods and rationale should be recorded and submitted beforehand, but not to the public. Often this is done at least to some extent in a research proposal on a grant application.

  10. …A deeper issue is that the irreproducibility crisis has remained largely invisible to the general public and policy makers. That’s a problem given how often the government relies on supposed scientific findings to inform its decisions….
    On the contary! policy makers are not interested in science INFORMING their decisions. They are interested in science SUPPORTING their decisions.
    Policy decisions invariably benefif someone, and you can lay odds that that someone has ‘commissioned’ the policy decision, usually through lobbying. All science is there for is to provide a justification…

    • “A deeper issue is that the irreproducibility crisis has remained largely invisible to the general public and policy makers…”
      I don’t think it is invisible to the generally public. After being bombarded by a seemingly endless series of studies with contradictory findings on, for example, what is healthy to eat and what is bad to eat, the General Public often just shrugs their shoulders and ignores the whole sorry lot.

  11. Our sons girlfriend is studying Bio Medicine at university and has just had to write a lab report in it she must have 40 citations, when she told me that all I could think was that it would almost create a merrygoround of new researchers being forced to copy the mistakes of those that have gone before in order to pass the course.
    James Bull

    • James, Did she read all 40 citations? I have reviewed papers, sat on editorial boards, where the scientists quoted lots of papers but had actually read hardly any of them. They would read a paper that quoted other papers, which they didn’t read, then they would cite all of them. There have been times when people quote papers, that quote papers but never bothered to look at the original source. Therefore mistakes or misinterpretations took place and were perpetuated through time.

      • It’s worse than that. Often the paper being cited contradicts the conclusions being made by the author and in no way supports their research.

      • Another major problem is with papers that have many authors. If you join a team like this you may be 10th in the list of authors but wind up with hundreds of citations if any one of the papers becomes popular. Citation indices have lost their value from long list of authors just as peer review by pals has lost its value.

  12. One of the ‘dirty little secrets’ of science is just how rubbish peer review can be in practice. It is sold as a check on BS but in reality it can act as as actually promotor of the same. Climate ‘science’ being the classic example, any old sh*t both can and does get through peer review, if it supports the consensus.

    • We had a scientist at our institution that deliberately, at the prompting of several in the federal government, bypassed our editorial board and review process. Their paper was to be published in a major federal journal that claimed to be peer reviewed. I found out that the paper had bypassed our process when one of the peer reviewers that I knew well called and ask how we let such a poor paper out of house, though he bet I didn’t know. Later another peer reviewer called to complain that none of his comments had been addressed by either the author or the journal editors, not even the math errors and misuse of at least two statistical models. He was upset that the federal journal editors were basically ignoring his telephone calls and letters. This took place “way back” in the 1980s. Over the years I was a peer reviewer on several papers for the same journal where the authors and editors ignored my comments and corrections. I finally quit reviewing for the journal. I wrote them a nasty letter about their failure to properly use peer reviewers. I got no response. So such problems have been going on for a good while. As we use to say in the Navy when we repeatedly did dumb things mandated or uncorrected from on high, “200 hundred years of tradition, unhampered by progress.”

  13. “He uses statistics as a drunken man uses lamp-posts.. . for support rather than illumination.”
    (Andrew Lang)

    • “Statistics used to garner attention should remain suspect. 50% of the people in this classroom have only one testicle … you in the back, are you listening now?”
      (surveying professor … paraphrased)

  14. ‘Acceptance’ of glib theory and daft word-view interpretations of ‘data’, is where it all falls down.
    The only people who don’t accept so easily are those who have both a clue, and a spine.
    It makes little difference if what’s being ‘accepted: is completely false, or not. Cohesion to the BS is valued far more highly than facts, or messy stuff like repeatability, because sucking-up gets the public money.
    Unaccepting is unacceptable to the accepting— it doesn’t pay $$$ to be right.

  15. There are no watchdogs for this stuff. The press and politicians simply corrupt science to push political agendas. There should be a standard requirement that any research used to support public policy:
    1) Releases their data to the public
    2) Must be independently verified and reproduced
    3) Must be done in a double-blind manner so the verifier doesn’t know what they are verifying
    4) Penalties must be stiff for scientific fraud

  16. There’s so much guesswork in statistics that they’re nearly useless. I think that they are still useful in creating a hypothesis, but shouldn’t be used as evidence to prove anything. A good starting point, but often wrong.

    • Well, you’re right about one thing – statistics don’t prove anything. That’s not what they are meant to do. That’s not what science does.
      But you are dead wrong about them being nearly useless. They are not guesswork when used appropriately. They are a tool that can be misused and abused, but that doesn’t make the tool useless.

  17. How discouraging to find Watts Up With That using an apparently thoughtful article as bait to land a WSJ subscription.JGL
    >

  18. And a valid experiment must not only be reproducible, it must be consistently reproducible. If it is reproducible only a fraction of the time then it is not actually validating the hypothesis.

  19. “Half the results published in peer-reviewed scientific journals are probably wrong.”
    Half? Only Half? I think that makes it better than we thought not worse.

  20. Irreproducibility is a certain hallmark of bad science. But there are many others equally certain to be indicative. In statistics, autocorrelated ‘statistical validity’ without a Bonferroni correction. In clisci, reliance on unvalidated (or worse, proven wrong) models. In renewable energy, failure to address the system effects of intermittency and lack of grid inertia. In regulation, modification of or ignoring contrary findings (recent example EU glyphosate cancer warning). Wrote a whole book with hundreds of examples in different categories, The Arts of Truth. Used clisci as the penultimate chapter because so rich with e amples from each of the previous chapter categories.

    • In the social sciences and in climate science, there is also mis (or dis)-applied statistical methods, which allow the author to claim significance where there is none.

  21. Alot of wordy & unnecessary analysis from the National Association of Scholars. Simply — much “science” is nowadays conducted by corrupt, grant-money-grubbing sycophants.

  22. Journals have promoted their value by convincing everyone that “peer” review is the gold standard of determining whether research is correct or not. This is a joke as people are finally recognizing. Research should be judged by others doing the physical work (physical is important) to verify and replicate findings. The current social construction where replicators finding problems have their careers shut down should become a thing of the past. Those scientists who try to damage others should have their careers damaged and even be fired.
    Look at the Big Bang Theory. Sheldon is the theorist and Leonard is an experimental physicist who attempts to verify and duplicate findings of other researchers. Who is really more important?
    Much of current statistics work came about from Bell Labs and others who tried to tease information out of noisy communications signals. Many scientists need to review this work in order to learn how many attempts were unsuccessful because you just can’t do it, that is, retrieve actual, useful INFORMATION from noise. Nyquist rules. They did have one advantage, what goes in, should also come out. Today’s scientists need to realize that statistics is not the end all or be all, you may just be ending up with noise.

    • What do you suggest take the place of statistics? What is a better way to find a relationship?

      • Kristi —> You missed the point. I’m not suggesting that statistics aren’t a valuable tool but they DO NOT provide evidence. Only real physical measurements can provide evidence. That was the whole point about Bell Labs research. You can do all kinds of statistical manipulations and think you have discovered something yet the real answer lies in knowing that when you physically input “Mr. Watson, come here, I need you.” that your physical output is “Mr. Watson, come here, I need you.”
        Statistics do not provide physical evidence, models do not provide physical evidence. At best they provide you with educated guesses about what may occur. In the end, they are only guesses and that is never stated.

  23. A good number of activists do not really want valid science. Consider the foofraw over Secretary Pruitt at EPA requiring that all studies used to support policies have checkable data bases. The greens went ballistic, as some of their favored policies depended on studies with no reported supporting data.

  24. As bad is the claim by governments that the “latest research” shows – when the latest is the least likely to have gone through the necessary years of being tested, reproduced, amended, etc etc. And as we know, it is perhaps 50% likely to simply be wrong.

  25. Many years ago, as a graduate physics student, I had spent a great deal of time and effort developing a new method of measuring – well, never mind what, it seems rather inconsequential at this distance – and I had just made the first measurements on my apparatus using a known test case. To my delight, I got exactly what I knew the result should be, so I went immediately into measuring unknown cases.
    After a few measurements, I realised that there was something wrong with my measurements, which were internally inconsistent. It took a couple of weeks of work, but I finally realised that the noise level in my rather primitive electronics was so high that I was measuring little more than random noise, and my first, supposedly perfect test case was just a fluke. I went back and measured it again, and sure enough, I got a completely different result.
    I must admit that the urge to publish something, no matter how spurious, was quite high, but in those far-off days there was a certain level of morality? honour? call it what you will, but publishing doubtful results was just not done.
    Things are different now, apparently.

  26. 50%? More like 80%-90%. Causes: pressure to publish immature research, and/or overestimating significance by applying faulty statistical techniques and, not to be underestimated, political agendas.

  27. That the issue was clearly foreseen by Dwight Eisenhower, (possibly the last American president elected before PR media manipulation professionals controlled everything) in his 1961 farewell address:
    “The prospect of domination of the nation’s scholars by Federal employment, project allocations, and the power of money is ever present and is gravely to be regarded.”
    “In this revolution, research has become central; it also becomes more formalized, complex, and costly. A steadily increasing share is conducted for, by, or at the direction of, the Federal government.
    Today, the solitary inventor, tinkering in his shop, has been overshadowed by task forces of scientists in laboratories and testing fields. In the same fashion, the free university, historically the fountainhead of free ideas and scientific discovery, has experienced a revolution in the conduct of research. Partly because of the huge costs involved, a government contract becomes virtually a substitute for intellectual curiosity. For every old blackboard there are now hundreds of new electronic computers.
    Yet, in holding scientific research and discovery in respect, as we should, we must also be alert to the equal and opposite danger that public policy could itself become the captive of a scientific technological elite.”

  28. There is a related problem which also gets little discussion. This is that while a “new” finding receives heaps of press and praise, it’s hard to get a paper even published that shows that the “new” finding was totally bogus. Journals don’t like to print them, and when they do the actual truth receives little of either press or praise.
    Take the Mann “hockey-stick” as an example. It was picked up and used by the IPCC, lauded in the press, and published everywhere. But when Steve McIntyre showed that it was total nonsense, that didn’t get any traction at all.
    As Mark Twain never said, “A lie can travel halfway ’round the Internet while the truth is getting its boots laced up”
    w.

    • The reason that McIntyre’s paper fell flat on it face as shown by Huybers 2005 and Wahl & Ammann 2007 .
      ..
      This is besides the fact that Mann’s work has been replicated in subsequent studies.

      • Mann’s work has been replicated
        ========
        That brings up an interesting point. An erroneous conclusion can be infinitely replicated by following the same error of method. Thus replication is no guarantee of correctness.
        Calibration of tree rings violates the statistical prohibition against selection on the dependent variable. It leads to spurious correlations.
        however this problem is poorly understood by many scientists because it is counter intuitive. Intuition tells us that to better understand illness we need to concentrate on sick people. Statistics tells us we need to study both sick and well people.

      • Huybers’ paper is bunch of arcane technical points about whether the extent to which Mann’s method mines hockey sticks might have been exagerated. Huybers agrees that it mines hockey sticks. Huybers’s paper makes a nice talking point, since it’s going to be incomphrehesible to the casual reader.
        The “replicated in subsequent studies” is actually very subjective. It means how much these graphs look like each other. Here’s an example of someone who thinks they don’t:
        https://www.skepticink.com/prussian/2014/03/19/about-those-mann-replications/

      • David Dirkse,
        I don’t think any paper of the kind submitted to or published in a peer reviewed journal could do that much better at conveying the information in these top notch blog posts I linked to. They also wouldn’t be as clear and accessible.

      • Then the question becomes: If the Hockey Stick is so good, and the models are so good, then why has the GMT deviated so much from their predictions? I remember reading a National Geographic years ago and the Hockey Stick was presented in a flashy chart but even then actual global temperature was deviating, and doing so dramatically, from the Stick. I wondered then how the editors would let that pass.

      • David, we are not going to agree on this subject (and I respect your opinion on the matter). I am not a climatologist/meteorologist as Ristvan, Willis and a bunch of others will attest but biological indicators are in my world. Much of the Stick (and other studies) hooked different indicators (biological and non-biological) together to form a “smoothed” historical line and then took that line into the future. (Note: I made a distinction between the Stick and models but both make predictions of future temperature.) The problem with that approach is that the different Bio-indicators in particular will be affected by different sets of environmental conditions which culminates in exceedingly large error bars, and these are rarely reported. If the authors report the large error associated with their studies and treat their conclusions appropriately, then fine. But, using bio-indicators (and many, maybe all, other proxies for temperature) and assigning the same precision and accuracy as calibrated direct measurement instrumentation is…..insane. And taking those data/results/conclusions to the political sphere to drastically change people’s lives is questionable to say the least.
        Now, I recognize, when doing paleo-anything, you can only use what’s available but Mann, for instance, only used Yamal Bristlecones and not others that presented a different result. And the tone of the CRU email hack is troubling. But, let me say that I do not know Dr. Mann, have not had any dealings with the man, so I will not question his sincerity or character, just the methodology that was used.
        Still, real world data varies from at least most of the model predictions and the Stick.

      • “both make predictions of future temperature”

        Nope, the “hockey stick” does not make any prediction(s). Reconstructions of existing data and/or proxy data are not predictive. They are summations of what we know of the various datasets.

        Now you run the gamut of “political sphere” to purloined emails. Take my advice and try to stick to the science and ignore the fluff.
        ….
        You have yet to address the subsequent reconstructions that use data that Mann did not use, yet they all arrive at surprisingly similar results. How do you account for that?

      • Perhaps semantics regarding “predictions”? Did Dr. Mann stop the Stick at the then present day and others extended it into the future (such as NG)? If so, I stand corrected regarding Dr. Mann’s Stick and apply the comments to others. However, I do believe that Dr. Mann has commented otherwise about the ramifications of future CO2 increases (and is entitled to those).
        Regarding others’ proxies, if similar methods were used similar results might be expected. But, I invoke the spirit of W.E. and ask for a link (one or two will do) to another dataset. (It will be tomorrow before I can return to WUWT.)
        And regarding the emails and “political sphere”, I believe those statements are accurate though not pertaining to the science of the subject as you noted. However, whether fortunate or not, the whole subject of climate/pick-your-term is in that “sphere” with implications on our use of energy, transportation, population, food production and taxation. Certainly they are separate from the science but those will be the practical offspring of the marriage of the science and the politics.

    • David, I did go back to refresh my memory of the Mann, Bradley and Hughes papers of 1998 and 1999 and their data did stop in the “then present” and extended to 1400 in the 1998 paper and to 1000 in the 1999 paper. They did include and uncertainty band which was quite wide in the more distant past and narrowed as instrumentation became available. I did note that the upward trend toward the recent end of the data in the original papers, which was influenced by the beginnings, at least, of the 1998 El Nino, was within the uncertainty band of earlier centuries. I guess that HadCRUT4 data (1850-2013) were added later but, indeed, the graph in the original paper did not include information beyond the “then present”. So, my apologies there. Others have speculated on future temperatures to 2100 and some beyond.
      My other comments remain unchanged.
      As an FYI, my interest in the issues of climate revolve around three areas:
      1. Why do real world data deviate from model predictions in the past? My hat is off to the modelers as they have a difficult task at handling all possible variables and getting the physics correct but, so far, something seems amiss. Ristvan and others have pointed me to resources in this area that have been helpful.
      2. Do the various datasets actually contain high-quality information? Questions abound here, even with the satellite data. My hope is in the USCRN and similar.
      3. What is the solar connection (not necessarily sunspots) to climate? Hmmm, a dilemma, I think.
      Time for some shut-eye.

      • There are so many other nails in the CO2 coffin A partial list
        1) Why did sea level rise faster in early 2Oth century than now and even now is not acclerating?
        2) Why do only rural land temperature data sets show no warming?
        3) Why did climate scientists in the climategate emails worry about no warming trends . They are supposed to be unbiased either way.
        4) Why do some local temperature land based datasets like Ottawa Canada show no warming for last 146 years and Augusta Georgia show no warming for last 83 years? There must be 1000’s of other places like this.
        5) why do 10 of the 13 weather stations in Antarctica show no warming in last 60 years? the 3 that do are near undersea volcanic ridges.
        6) Why does the lower troposphere satellite data of UAH show very little warming and in fact showed cooling from 1978 to 1997?
        7) Why is there only a 21% increase in net atmosphere CO2 pppm since 1980 bu yet mankind increased fossil fuel emmissions CO2 by 75%?
        8) Why did National Academy of Sciences in 1975 show warming in the 30’s and 40’s and NASA in 1998 and 2008 not show nearly as much warming for tose time periods? .
        9) Why has no one been able to disprove Lord Monckton’s finding of the basic flaw in the climate sensitivity equations?
        10) Why has there never been even 1 accurate prediction by a climate model. Even if one climate model is less wrong than another one it is still wrong.
        11) Why do most climate scientists not understand the difference between accuracy and precision?
        12) Why have many scientists resigned from the IPCC in protest?
        13) Why do many politicians, media and climate scientists continue to lie about CO2 causing extreme weather events? Every data set in the world shows there are no more extreme weather events than there ever were
        14) Why do clmate scientists call skeptics deniers as if we were denying the holocaust?
        !5) Why did Michael Mann refuse to hand over his data when he sued Tim Ball for defamation and why did Mann subsequently drop the suit?
        16) Why have every climate scientist that has ever debated the science of global warming lost every debate that has ever occurred?
        17) Why does every climate scientist now absolutely refuse to debate anymore?
        18) Why do careers get ruined when scientists dare to doubt global warming in public?
        19) Why do most of the scientists that retire come out against global warming?
        20) Why is it next to impossible to obtain a PhD in Atmospheric science if one has doubts about global warming?
        21) Why is it very very difficult to get funding for any study that casts doubt on global warming?
        22) Why has the earth greened by 18% in the last 30 years?
        23) Why do clmate scientists want to starve plants by limiting their access to CO2? Optimum levels are 1200 ppm not 410ppm.
        24) Why do most climate scientists refuse to release their data to skeptics?
        25) Why should the rest of the world ruin their economies when China and India have refused to stop increasing their emmissions of CO2 till 2030?
        26) Why have the alarmist scientists like Michael Mann called Dr. Judith Curry an anti scientist?
        27) Why does the IPCC not admit that under their own calculations a business as usual policy would have the CO2 levels hitb 590 in 2100 which is exactly twice the CO2 level since 1850.?
        28) Why do the climate modellers not admit that thie error factor for clouds makes their models worthless?
        29)Why did NASA show no increase in atmospheric water vapour for 20 years before James Hansen shut the project down in 2009?
        30) Why did Ben Santer change the text to result in an opposite conclusion in the IPCC report of 1996 and did this without consulting the scientists that had made the original report?
        31) Why does the IPCC say with 90% confidence that anthropogenic CO2 is causing warming when they have no evidence to back this up except computer model predictions which are coded to produce results that CO2 causes warming?
        32) How can we believe climate forecasts when 4 day weather forecasts are very iffy?.
        33) Why do all climate models show the tropical troposhere hotspot when no hotspot has actually been found in nature?
        34) Why does the extreme range of the climate models increase as the number of runs increases on the same simulation?
        35) Why is the normal greenhouse effect not observed for SST?
        36) Why is SST net warming increase close to 0?
        37) Why is the ocean ph level steady over the lifetime of the measurements?
        38) what results has anyone ever seen from global warming if it exists? I have been waiting for it for 40 years and havent seen it yet?
        39) If there were times in the past when CO2 was 20 times higher than today why wasnt there runaway global warming then?
        40) Why was there a pause in the satellite data warming in the early 2000’s?
        41) Why did CO2 rise after WW2 and temperatures fall?
        42) For the last 10000 years over half of those years showed more warmung than today Why?
        43) Why does the IPCC refuse to put an exact % on the AGW and the natural GW?
        44) Why do the alarmists still say that there is a 97% consensus when everyone knows that figure was madeup?
        45) The latest polls show that 33% do not believe in global warming and that figure is increasing poll by poll ? why?
        46) If CO2 is supposed to cause more evaporation how can there ever be more droughts with CO2 forcing?
        47) Why are there 4 times the number of polar bears as in 1960?
        48) Why did the oceans never become acidic even with CO2 levels 15-20 times higher than today?
        49) Why does Antarctica sea ice extent show no decrease in 25 years?
        50) Why do alarmists resent skeptics getting funding from fossil fuel companies ( when alarmists get billions from the government and leftest think tanks) and skeptics get next to nothing from governments for climate research?

      • Alan, thank you for your list of very interesting questions! I will keep these close at hand. I can add a little to #4: a few years ago, Joe D’Aleo at WeatherBell did an analysis of US weather stations, looking for rural stations that were unaffected by siting issues and UHI. As I recall, he found about 200 stations with 80 years of records and found no warming associated with the set. (Maybe Joe D. will stumble across this tread and comment further.)

  29. ” lack of accountability, political groupthink” These are the primary points that need to be attacked in order to reverse this mess we find ourselves in. People pushing this politically driven crap have to be severely punished, publicly and loudly, so that others will not “replicate” the results they have been creating.

  30. As long as irreproducible science continues to reliably produce funding, the Climate Science farce will continue.

  31. Since we’ve begun our post-Christian journey in what was once a thoroughly Protestant made experiment, it shouldn’t be a surprise when science is bent to bow and scrape to the humanist politics of the day. And why on Earth would any pol stick his head up only to have it shot off? 535 elected officials in Congress but I challenge any WUWT reader to name 10 skeptics who aren’t portrayed as lunatics. Sorry, just my latest missive from Bluesville…

    • Everyone thought Galileo was a lunatic. Us skeptics always argue on the science. The alarmists always argue on the consensus. However their consensus is actually that only 2/3 of people believe in global warming. 1/3 dont and that fraction is growing every day. However back to the real consensus where it counts. Among PhD scientists of all disciplines, the majority now think that global warming has been too much hyped and there is really nothing to worry about. Only in the climate science field is there a majority who adhere to the party line because their careers are at stake. When they retire the majority now come out against global warming because they have nothing to lose. Just look at the growing number of retired NASA employees who think global warming is a joke. As soon as 75% of the public realizes the global warming hoax the politicians will change their tune and the media will follow. The whole thing will collapse very quickly at some point. Every climate scientist has lost every debate with a skeptic to the point that every climate scientist now refuses to debate it. The skeptics have truth on their side. What do the alarmists have? Groupthink!!!!!!!!!!!!!!!!!!!!

      • Alan. Do you mind if I snitch your 50 nails in the coffin piece? I would like to see that get around. Thanks.

  32. This is all a symptom, basically, of the corruption – which IS, in fact, a LOT worse than I thought.
    And I thought it was pretty bad.

  33. I work in pharmaceuticals and we have the same problem. Clinical research that is not stacking up and negative results becoming ‘file on data’.

  34. Outcome based science was necessary for the globalists and so called clean energy rent seekers
    to justify their plans . The UN admitted so and the global warming cheerleaders waiting for government cash to line their pockets helped pump the tires .
    The result no temperature change difference after wasting over a $trillion dollars and an annual fuel poverty death count of at least 100, 000 .
    Why aren’t people in jail ?
    Now what was the latest on the other significant event …. Stormy Daniels /
    That’s where we are folks .

  35. Here is a new idea. Take part of the funding for NIH, NIST, and CDC to build a government science replication lab and institute. This is a needed function for government to improve policy formation, regulation, and the judicial system.

    • The CDC… that agency that needed to be restrained by law from promoting gun control? That agency that went out of the way to hide the origin Haiti cholera outbreak?
      You think you can salvage something from these US agencies with an epidemic of manipulations, half truths, or plain cheating?
      (Yes, I’m ALSO looking at you, Federal Bureau of Matters.)

  36. Regarding “bad science”, a buddy of mine used to work at Econ Journal Watch https://econjwatch.org . He explained to me years ago how this group reviews various claims of economic “science” — claims which inspired bogus laws to have been created — and refutes them.
    no doubt this sort of thing occurs all of the time in other areas of “science”. 😎

  37. I went back and looked at some of the document.
    From —–IMPLICATIONS FOR POLICYMAKING
    “Reformed standards may also favor other liberal policies in the end: scientists who worry about climate change have already begun to marshal crisis-of-reproducibility arguments to discredit their skeptical opponents.”170
    From Endnote 170
    Rasmus E. Benestad, et al., “Learning from mistakes in climate research,” Theoretical and Applied Climatology. 126, 3-4 (2016), pp. 699-703, https://link.springer.com/article/10.1007/s00704-015-1597-5
    “There have been attempts in the scientific literature to correct some misconceptions, such as a myth regarding an alleged recent “slow-down” in global warming, a so-called hiatus.”…”The sample was drawn based on expert opinion according to the criterion of being contrarian papers with high public visibility and with results that are not in agreement with the mainstream view.”…. ” There may also be flawed papers agreeing with the mainstream view, but they have little effect on the gap of perception between the public perception and the scientific consensus.” Based on analysis of 38 papers available in supplementary materials
    and
    Goldman, et al., “Ensuring scientific integrity in the Age of Trump,” Science 355 (2017), pp. 696-98, http://science.sciencemag.org/content/355/6326/696
    Behind a paywall, but first two lines of summary.
    “With the new Donald J. Trump Administration comes uncertainty in the role that science will play in the U.S. federal government. Early indications that the Administration plans to distort or disregard science and evidence, coupled with the chaos and confusion occurring within federal agencies, now imperil the effectiveness of our government.”
    I dare not enter into the minutiae of the analysis in the supplementary material, but there is enough to suggest further review which I would appreciate reading, especially since I am sure that this problem predates both climate science and the US presidents of this century. Hope I have everything correct.
    Learning through replication in climate research by R.E. Benestad, H.O. Hygen, R. van Dorland, J. Cook, D. Nuccitelli, S. Lewandowsky, K. Hayhoe https://static-content.springer.com/esm/art%3A10.1007%2Fs00704-015-1597-5/MediaObjects/704_2015_1597_MOESM1_ESM.pdf

    • I just read the WSJ report (paper edition) and I think I got the National Association of Scholars report mixed up with another, too much information. This one belongs somewhere else apparently but don’t see it. My apologies. It looks like they are on the right track. Dueling reports?

  38. The criterion of reproducibility is very important, but even more so is a commitment to falsifiability, and subjecting findings to active attempts to falsify them. Sir Karl Popper style.

  39. Take for instance, the AGW conjecture. AT first it sounds quite plausible but then listing “scientific consensus” as a reason to believe ti tells me that something has got to be wrong. Of course “scientific consensus” is really an oxymoron since science is not done that way. Consensus is a political rather than a scientific argument All this work they have done with computer simulations is not much better than make believe. They hard code in that CO2 causes warming so that is what their simulations show. The whole thing begs the question and is hence useless..
    When one looks more critically at the AGW conjecture one realizes that it is based on only partial science. According to the paleoclimate record and the work done with real models, one can conclude that the climate change we have been experiencing is caused by the sun and the oceans over which mankind has no control. There is no real evidence that CO2 has any effect on climate and plenty of scientific rational to support the idea that the climate sensitivity of CO2 is really zero. The AGW conjecture would have one believe that all but a few trace gases in the Earth’s atmosphere are thermally inert. The AGW conjecture ignore’s the fact that heat energy transport by conduction, convection, and H2O phase change dominate over LWIR absorption band radiation by trace gases. An important part of the AGW conjecture is that more CO2 warms the atmosphere which allows more H2O to enter the atmosphere and because H2O is also a greenhouse gas, the additional H2O provides more warming and hence provides a positive feedback which amplifies the effect of adding more CO2 to the atmosphere. The AGW conjecture ignore’s the fact that H2O is a net coolant as exemplified by the fact that the wet lapse rate is significantly less than the dry lapse rate. If CO2 really affected climate then one would expect that the increase in CO2 over the past 30 years would have caused at least a measurable increase in the dry lapse rate in the troposphere but such has not happened.
    The AGW conjecture depends upon the existence of a radiant greenhouse effect caused by trace gases in the Earth’s atmosphere with LWIR absorption bands, yet such a radiant greenhouse effect has not been observed in a real greenhouse, in the Earth’s atmosphere, or anywhere else in the solar system. The radiant greenhouse effect is science fiction so hence the AGW conjecture is science fiction. .

  40. Over a period of 13 years my job was to design and manage a series of scientific studies. In the design of a scientific study the key requirement was for the claims that were made by the model that was the product of the study to be falsifiable for if these claims were not falsifiable the scientific method was not followed.

  41. It is astounding the consistency of the comments here that show complete distrust in science – and particularly in climate science, of course. Not just that, but accusations of corruption, fraud, greed, desire for glory…just about anything scientists could be accused of, it’s one this page. And you are all so CERTAIN of yourselves!
    This is exactly what I hate about the movement to ensure climate change is not considered in policy-making: it has bred an unquestioning dismissal of a vast range of science. A few weeks back there was a study on WUWT that actually had nothing to do with climate change, but it was trashed, ridiculed and completely misunderstood. The comment about it by the WUWT writer ridiculing it was more than enough to get everyone to identify its imagined flaws.
    The “skeptic” side of the debate is not bent on proving a theory, but on tearing one down. That is bias. And because it’s so mixed up in the reverence of fossil fuels and the idea that the nation would collapse if we used more renewables, there’s conflict of interest ensuring that bias.
    Are you all certain that scientists are wrong in predicting major climatic disruption, with significant negative effects? Are you sure?
    If you are sure, you are not a skeptic.

    • Oddly it is often not the scientists who make doom and gloom predictions, but other who are pushing AGW for their own reasons, such as St Gore.
      Although I am biased, as I do not considered those whose standards are lower than would be expected for undergraduate in writing an essays to be scientists at all. And given that does cover quite a few working in climate ‘science ‘, such has Mann , you can see the problem. But it would be good no why industrial scale levels of smoke and mirrors are required in what is claimed to be ‘settled science’

    • Kristi —> “The “skeptic” side of the debate is not bent on proving a theory, but on tearing one down. That is bias. ” This is not bias, it is the scientific method at work. A theory is not proven nor does it become a
      law by recreating experiments that “prove” it but by devising experiments (or other theories) that attempt to disprove it. It only take one experiment to disprove a theory but an infinite number to prove it.
      Heck, for hundreds of years Newton’s laws of gravity were “proven” all the time by experiments in grade school and beyond. Then along comes Einstein and revolutionizes the theories about gravity and Newton’s laws, while accurate with the right assumptions, are no longer the be all and end all. Was Einstein a skeptic?

      • Yes. Proper science isn’t about coddling your intellectual darlings. It’s about trying your very best to murder them.

    • Yet you are so *sure* about our *sureness*?
      We don’t have to reinvent the wheel to point out that the wheel-of-the-week is not rolling.

  42. In the Wall Street Journal article one finds the following:
    “The whole discipline of climate science is a farrago of unreliable statistics, arbitrary research techniques and politicized grouptthink.”
    Bout says it all.

    • “The whole discipline of climate science is a farrago of unreliable statistics, arbitrary research techniques and politicized grouptthink.”
      Also true for vaccine research.
      (We are still waiting for the evidence showing that most vaccines are more useful dangerous.)

  43. The problem is made worse by the following:
    1) Scientists often think that “no effect” of some treatment is a failed study and don’t even try to publish it. I heard this twice in the past week. This “only positive results are science” bias is simply wrong.
    2) Journal are loath to publish critiques of studies they published, even if you can show the study was a disaster.
    3) The pressure on junior scientists to publish in order to get tenure are extreme and motivate cheating. If you don’t get tenure you may be ruined. To make this even worse, at this stage in their career, a scientist may not have funds or grad students so the pressure is even worse.
    4) In cancer studies, there is a huge problem of contamination of cultures such that melanoma (a very aggressive cancer) is often what people are testing rather than what they think they are testing.
    5) In both cancer studies and toxicology, the white rats being used are so pure-bred that they are highly susceptible to even being looked at funny.
    6) Dont’ get me started on models.

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