post-normal science graph
Picture Source: Shaping Science Policy

Jan Mickelson interviewed Dr. Calvin Beisner, who is the founder of the Cornwall Alliance for the Stewardship of Creation, Friday on WHO Radio.  Dr. Beisner has been a guest on Caffeinated Thoughts Radio in the past, featured in the recent documentary Blue and is a keynote speaker at the Caffeinated Thoughts Briefing on Saturday.

Dr. Beisner discussed a phrase called “post-normal science.”  This phrase is a concept developed by Silvio Funtowicz and Jerome Ravetz it attempts to characterize a method of inquiry that is “appropriate” for contemporary conditions.  It is further explained this way:

We can understand ‘Post-Normal Science’ by means of a diagram, where the axes are ‘systems uncertainties’ and ‘decision stakes’. When both are low, we have ‘applied science’, the routine puzzle-solving like the ‘normal science’ described by Thomas Samuel Kuhn in his book The Structure of Scientific Revolutions. When either is medium, we have ‘professional consultancy’ for which the examples are the surgeon or the senior engineer. Although their work is based on science, they must always cope with uncertainties, and their mistakes can be costly or lethal. It had once been believed that environmental and general policy problems could be managed at this level, but the great issues of global warming and diverse forms of pollution show that framing and implementing policies must frequently be done before all the facts are in. Thus many problems occur in the high-stakes, high-uncertainty region of the diagram, a condition referred to as ‘post-normal.’

Mike Hulme, the founder of the Tyndale Centre for Climate Change Research, in an article written in The Guardian in 2007 that climate change must exist in the realm of post-normal science.

The other important characteristic of scientific knowledge – its openness to change as it rubs up against society – is rather harder to handle. Philosophers and practitioners of science have identified this particular mode of scientific activity as one that occurs where the stakes are high, uncertainties large and decisions urgent, and where values are embedded in the way science is done and spoken.

It has been labelled “post-normal” science. Climate change seems to fall in this category. Disputes in post-normal science focus as often on the process of science – who gets funded, who evaluates quality, who has the ear of policy – as on the facts of science.

So this book from Singer and Avery can be understood in a different way: as a challenge to the process of climate change science, or to the values they believe to be implicit in the science, rather than as a direct challenge to scientific knowledge.

In this reading, Singer and Avery are using apparently scientific arguments – about 1,500 year cycles, about the loss of species, about sea-level rise – to further their deeper (yet unexpressed) values and beliefs. Too often with climate change, genuine and necessary debates about these wider social values – do we have confidence in technology; do we believe in collective action over private enterprise; do we believe we carry obligations to people invisible to us in geography and time? – masquerade as disputes about scientific truth and error.

We need this perspective of post-normal science if we are going to make sense of books such as Singer and Avery’s. Or indeed, if we are to make sense of polar opposites such as James Lovelock’s recent contribution The Revenge of Gaia, in which he extends climate science to reach the conclusion that the collapse of civilisation is no more than a couple of generations away.

The danger of a “normal” reading of science is that it assumes science can first find truth, then speak truth to power, and that truth-based policy will then follow. Singer has this view of science, as do some of his more outspoken campaigning critics such as Mark Lynas. That is why their exchanges often reduce to ones about scientific truth rather than about values, perspectives and political preferences. If the battle of science is won, then the war of values will be won.

If only climate change were such a phenomenon and if only science held such an ascendancy over our personal, social and political life and decisions. In fact, in order to make progress about how we manage climate change we have to take science off centre stage.

Beisner, in this interview, points out that on the subjects of climate change and evolution we have seen an epistemological shift among members of the scientific community.  Which is why climate change naysayers are dismissed and the theory of intelligent design, even though it also follows the scientific method, is dismissed as “psuedo-science” by those who disagree.

You can listen to Mickelson’s interview of Beisner below:

You can also listen to Jan’s full show below:

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  1. Big oil loves Beisner, so they give him lots of money to try to muddy the water. According to Beisner, all the recent record hurricanes and tornadoes and everything else are not their fault. It’s God punishing us because of gay rights. Not using fossil fuels is an insult to God.

  2. All the hurricanes and tornadoes recently are over forty percent below average from weather in the seventies and eighties. Being a gay atheist is no evidence of knowledge.

  3. To summarise this post, fundamentalist Theologian wishes that science would tell him what he wants to believe, and fantasises that some day it will.

    Delusional, much?

    Almost as delusional as the belief that Intelligent Design Creationism follows the scientific method (ID’s approach to the scientific method is about the same as Cargo Cults’ approach to logistics — a superficial emulation that completely misses the underlying point), or that Climate Change, which is supported by nountains of research, and accepted by something like 99% of climate scientists is somehow “uncertain” and “disputed” “‘Post-Normal’ Science” (“Post-sticking-your-fingers-in-your-ears-and-shouting-la-la-la-la-la-I-can’t-hear-you Science” would be a more apt description).

    I would suggest that E. Calvin Beisner go back to teaching Historical Theology, a subject which (unlike science) he actually knows something about.

  4. The tragic flaw of AGW is its cult-like belief in the validity of modelling.

    MODELS are not reality. If your model demonstrates that something is happening, there is a really really high chance that you messed it up. (I make models.)

    The more variables involved in what you are modelling, the higher the chance your model is worthless as a depiction of a real world system.

    If you look at CLIMATE… it is so over-determined, with so many variables involved, how can you possibly model it? We can’t even predict the weather 7 days from now.

    The whole problem with AGW is it gives a trace greenhouse gas so much power over the climate. More power even than the sun as a variable. Somehow the sun gets considered a constant – yet we know the sun has weather as well.

    The earth’s climate is a self-regulating system.

    1. The utility of modelling is a “cult-like belief” that encompasses the entirety of science, economics, architecture and engineering, political science, and probably dozens of other disciplines and professions besides.

      Let us rather talk about the “cult-like belief” that if it involves complex mathematics which you personally don’t understand, you have a valid reason for rejecting it.

      1. See there you go.

        You think that modelling is about mathematics.

        Actually, no it isn’t.

        What modelling is about is taking external elements and reproducing them in a different medium as a way to “shrink” a large system to try to understand it.

        A very famous wargame designer, who spent his life making models (his name is Trevor Dupuy) once said “If you fall back on math you’re kidding yourself. You have to fall back on history.”

        It’s when you take the historical perspective that you sometimes see how broken models can be.

        Classic example. The Hamlet Evaluation System in Vietnam. They rated villages (hamlets) on scales for loyalty, ranging from A to E. When they fed the data into the computer, guess what? It told them they had already won the war. Now if you stayed solely inside the mathematics you would have been forced to accept that conclusion. That they had won Vietnam. And anyone saying otherwise would of course be a “denier”.

      2. ONE completely unscientific model several decades ago was wrong, so ALL models (including rigorous scientific ones) are suspect? Appallingly BAD argument.

        When the models of nearly every climate scientist on the planet is telling you that YOU are wrong, and the only people supporting you are people like a theologian with a background in Scottish history and a balmy birther British lord, then it is time to start entertaining the possibility that you might in fact be WRONG.

      3. Bro… The Hamlet Evaluation System was implemented as US policy in Vietnam, based on research from places like the Rand Corporation.

        The point is, it’s a warning about models.

        The models aren’t telling me that I am wrong. The models are giving a result, but people are confusing the models with reality. They aren’t taking the models with a grain of salt, which they should.

        Let me repeat: modelling is an ARTFORM. It is NOT a science. It is not empirical – even if the information that goes into a model can be empirical.

        Let me say that again for emphasis: MODELLING IS AN ART.

        Let’s be clear in another way. If you have a model railroad, it’s a great way to learn about managing a railyard. But if your cat knocks over the rail cars, you’re a fool if yiou assume that giant cats are out there in the real world and will knock over real railcars.

      4. Last I checked, neither the US government nor Rand Corporation were scientific organisations — folksily implying some spurious kindred spirit between us does not change that cold, hard fact.

        All modelling involves a *degree* of subjectivity, certainly — but that degree varies ***MASSIVELY***. The way to ensure that this does not bias the results is scientific peer review.

        Again, when the models of nearly every climate scientist on the planet is
        telling you that YOU are wrong, and the only people supporting you are
        people like a historian-turned-theologian and a balmy birther British
        lord, then it is time to start entertaining the possibility that you
        might in fact be WRONG.

        Many scientific and professional disciplines REQUIRE modelling, as there is no way to test their hypotheses directly in a lab — climate science is one, but so is Cosmology (ever try to replicate the Big Bang in a lab?), designing buildings to withstand earthquakes, designing nuclear weapons (due to limitations on testing). Rejecting all modelling, and particularly rigorous scientific modelling, out of hand is therefore just plain IGNORANT.

      5. Guess what?

        Not even scientific peer review can change an artform into a science.

        Next thing. I have no issue with modelling. I’m just not myopic (classic failing of scientists). As a modeller, I understand the limitations of it.

      6. Guess what? Calling climate science research “an artform” DOES NOT stop it from being valid science.

        Guess what? By accepting the opinions of a historian-turned-theologian and a balmy birther British lord, over the expert opinions of the vast majority of experts in that field, you are not just being “myopic” but WILLFULLY BLIND!

        Guess what? Large areas of science requires modelling. This does not stop these fields from being rigorously scientific.

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