July 17, 2017
Over the past century, the deniers of scientific facts and conclusions have developed more sophisticated methods, but they still pick and choose from a fairly well-defined toolbox of approaches to convince non-experts of their fraudulent claims. In this blog entry, we introduce the basic elements of this toolbox, so that teachers and students may learn to recognize and refute the arguments. We break down the elements into eight categories, with several illustrations of each category given in this entry, but much more extensive explorations to be given in future blog entries.
1) Cast doubt on the scientific consensus, but avoid presenting peer-reviewed evidence in opposition to that consensus (or choose your friends for reviewers):
• Exploit the public’s challenge to distinguish truth from fiction they want to hear
• Cherry-pick published results to support your misinformation campaign
• Repeat misinformation often, ignoring evidence-based refutations of your claims
• “Debate” the issues via mass media, demanding “balance,” rather than in science journals
• The goal need not be to disprove the science, but only to delay policy decisions until it is too late to act, or your supporters (funders) can control the situation (profits)
The basic approach of item (1) has been exhaustively highlighted, across many scientific issues, in the excellent book Merchants of Doubt by Naomi Oreskes and Erik Conway. Examples of the cherry-picking of data – directing the reader’s attention to one or two interesting trees, and away from the forest — abound in ongoing climate change denial circles. We present two of them here as examples. The first, illustrated below, shows that when presented with a centuries-long trend of increasing measured average land temperatures, the deniers direct your attention instead to the fluctuations over the past 14 years or so, where they claim the evidence for global warming has vanished. In fact, as we’ll deal with in subsequent blog entries, the best current climate models indicate that short-term fluctuations during this period associated with el niño, volcanoes and solar fluctuations have masked a steady, ongoing increase in global temperatures attributed to human activities.
The second example illustrates an even more drastic attempt to direct the public’s attention away from the “offending” data, by pretending it does not exist! The plot on the left is taken from the Heartland Institute’s recent manifesto, Why Scientists Disagree About Global Warming, of which copies have been provided free of charge to most U.S. science teachers in the hope that they will then mislead their students. In order to make the point that there are frequently warming and cooling trends in Earth’s climate, they conveniently truncate their qualitative graph at the year 1900, which should immediately trigger the reader’s bullshit detector. The plot on the right below contains the published, peer-reviewed data from many different sources on global Earth temperatures deduced over the past couple of millennia, but including measurements since 1900. The dramatic rise since 1900, dwarfing the natural variations before then, makes it obvious why the Heartland Institute chose to truncate their graph.
2) Recruit a small number of scientists, whether or not they have relevant expertise, to support your spin that there is no consensus, and thereby confuse the public:
- Blur the distinction between “consensus” and “unanimity”
- Magnify quibbles about details to claim fundamental disagreements about basic conclusions
- Complain about conspiracies, self-interest and politicization among research scientists, but launder money to hide your own funding sources and political agenda
- Promote scientific skeptics or deniers to positions of authority and “eliminate” or discredit the scientists who support the consensus and the agencies that fund them
History is rich with examples of scientists who willingly contributed to the promotion of ideology over science, despite the fact that they should have known better. In the 3rd Reich, Hitler’s government used prominent scientists (including Nobel Prize winners Phillipp Lenard and Johannes Stark) to label much research, including Einstein’s Theory of Relativity, as fraudulent “Jewish science.” Needless to say, experimental evidence confirmed Einstein’s theory, which has long outlasted the 3rd Reich. In the Soviet Union, Stalin labeled genetics a “bourgeois pseudoscience” incompatible with Communist principles. He closed genetics laboratories, fired and imprisoned a generation of geneticists, and promoted co-denier Trofim Lysenko to lead Soviet agricultural policy development. Lysenko’s pseudoscientific “ideas,” with no reproducible experimental verification, led to chronic agricultural underproduction that starved generations of Soviet citizens.
But one need not look to Nazism or Communism as the only culprits in elevating ideology over evidence. In the U.S. extreme libertarianism — the insistence that any government regulation is a counterproductive impediment to free enterprise — has produced its own brand of science denial. In the latter part of the 20th century, the aerosol industry created its own “research council” of scientists casting doubt on the well-established link between CFC’s (chloro-fluorocarbons) and depletion of Earth’s ozone layer. Despite their still ongoing efforts, which will be documented in a later blog post, the scientific evidence led in the 1990’s to a worldwide ban on CFC production that has, by now, successfully slowed the ozone layer depletion. S. Fred Singer, once Chief Scientist at the U.S. Department of Transportation, was one of the most prominent of the deniers of ozone layer depletion, and also of acid rain. Singer now chairs the Heartland Institute’s Science and Environmental Policy Project, which endeavors to deny climate research and discredit the Environmental Protection Agency. Who better than a scientist to become a talented expert in exploiting the science denier’s toolbox?
But seriously, industries at risk due to scientific research, have long worked to attract prominent scientists with political clout to their side. They offer lucrative research grants where competition for federal funds is daunting. They attract well-established, influential academicians with political axes to grind, to serve as highly paid chief research scientists. Examples include: Geneticist C.C. Little, member of National Academy of Sciences, who headed the Tobacco Industry Research Committee, 1954-1979; Physicist Frederick Seitz, former President of the National Academy and of Rockefeller University, who was hired by R.J. Reynolds in 1979; CalTech physicist Steven Koonin, later Undersecretary for Science at the U.S. Department of Energy, who was hired as Chief Scientist by BP (British Petroleum) in 2004.
3) Discount predictions you don’t like as resulting from flawed models:
- Question the usefulness of models that don’t yet include all conceivable effects
- Cherry-pick data and ignore uncertainties to claim misleading model “failures”
- Rather than arguing to improve models and benchmark them against more extensive, newly acquired data, lobby for reduced research funding for these activities
- Demand definitive evidence that serious predicted ill effects are already seen, by which time it’s too late to prevent them
Item (3) is in widespread use for climate change denial, since much of the policy discussions must be centered on effects predicted for the future. And those effects are predicted by models that deal with a dauntingly complicated global system with many sensitivities and feedback mechanisms. Nonetheless, the deviance of the deniers is well illustrated by the first plot below, which has become (without the explanatory annotations) a poster child for climate science denial. It purports to compare recent climate model predictions (red curve) of global temperature rise to experimental data, revealing large discrepancies “the climate change conspiracists don’t want you to see!”
But the choice of data and the graphical presentation are deliberately misleading, in a number of ways highlighted in the annotations on this version of the plot. Most egregiously, the model predictions are for Earth’s surface temperatures, whereas the data included are for atmospheric temperatures extending up to 50,000 feet above Earth’s surface. This is important because the understanding of global warming is that greenhouse gases trap the Sun’s reflected heat in the lower part of the atmosphere (the troposphere), while the measurements extend into the stratosphere, where various mechanisms are known to lead to cooling, rather than warming. The plot below it contains the peer-reviewed version of the comparison of the same set of model predictions to the relevant data, averaging surface temperatures measured above both land and sea over the Earth’s entire surface. This comparison shows the agreement the climate deniers don’t want you to see!
4) Misrepresent the predictions of a theory in order to “debunk” it:
- Confuse the adjustable parameters of a theory with its “predictions”
- Highlight incomplete or incorrect specific experiments to cast doubt on a theory
- Declare ongoing, as yet inconclusive, tests of a theory as definitive “nails in its coffin”
- Trivialize the theory’s successful predictions as resulting from “fudge factors,” even though large quantities of data may be explained with few parameters
Exploitation of item (4) is especially prominent among creationist deniers of Big Bang cosmology. For example, they claim that Big Bang theory is a failure because it doesn’t predict the values or nature of Dark Matter or Dark Energy. But this is an objection to the scope of the theory, not to its validity. Physical theories often have parameters whose values are deduced by fitting data. The inability to predict values of these parameters is not a failure of the theory, but may be indicative of a higher theory that is not yet known. Dark Matter and Dark Energy may be considered as parameters in the standard cosmological model used to translate concepts of Big Bang theory into fits to the distribution of matter and Cosmic Microwave Background (CMB) radiation throughout the visible portion of our universe. The Standard Model of particle physics is not “invalidated” by the fact that predictions of its parameter values are beyond its scope, and motivate the ongoing search for the higher theory to which that Standard Model appears to be an excellent effective approximation. The same is true for Big Bang cosmology and Dark Matter and Dark Energy.
Creationists are furthermore fond of claiming that Big Bang theory has made no quantitative predictions subsequently validated by observation. This claim is flat-out wrong, and it reflects a misleading interpretation of what a prediction is. In order to provide a quantitative account for the abundance of hydrogen and helium isotopes in the universe, following the formation of light nuclei shortly after the Big Bang, applications of the theory extracted a value for the ratio of photon density to baryon (primarily neutron and proton) density in the wake of the Big Bang. That value was subsequently confirmed completely independently by later treatments of the observed CMB data, providing a critical validation of the theory’s internal consistency. Furthermore, the theory was used to predict the blackbody form of the energy spectrum of CMB photons and the existence of small fluctuations in the apparent CMB temperature depending on the direction from which one observed the photons on Earth — predictions later borne out quantitatively by experiment.
As an example of declaring premature nails in coffins, creationists also claim that Big Bang theory is “dead” because the predicted “CMB shadow of the Big Bang” is missing. In Big Bang cosmology, the CMB photons are attributed to light last scattered from matter at the so-called “recombination epoch” some 400,000 years after the Big Bang, when electrons and nuclei combined to form neutral atoms. The “shadow” referred to here is the so-called Sunyaev-Zel’dovich effect, whereby CMB photons originating beyond a galaxy cluster may scatter on their path toward Earth from ionized electrons in the cluster gas, and thereby experience a tiny shift in frequency from the pure blackbody spectrum. The predicted effect is tiny, and present experimental upper limits on its magnitude are completely consistent with other features of the CMB. Searches for the effect are ongoing. The measurements do NOT support creationists’ preferred claim of a nearby source of the CMB.
When deniers base arguments on such technical issues, it becomes very difficult for a lay audience to know whom to believe. For help in making that distinction, one needs also to consider the next few items in the science denier’s toolbox.