Excerpts from The No-Nonsense Guide to Science

Posted March 16th, 2007 by Jerry Ravetz and filed in Epistemological therapy

[Editor’s note: In follow-up to the last post, and others commenting on Post-Normal Science, we are posting some excerpts from Jerry’s new book, The No-Nonsense Guide to Science. But, of course, you should really read the whole thing. It provides a concise history, and lots of examples. To top it off, it concludes with a set of questions rather than recommendations.]

The decline of the illusion of objectivity
Over the last half-century, science has experienced great transformations in its scale, size, power, destructiveness, and corporate control and social responsibility. There is lively debate over many policy issues concerning health and the environment, and over proposed innovations such as those in the GRAINN set. But until we get over the illusion of objectivity of science, as embodied in its supposed certainty and value-freedom, those debates will be hindered and distorted. So long as each side in a debate believes that it has all the simple and conclusive facts, it will demonise the other, and dialogue will not be achieved. We need not fall into some nihilistic philosophy of total subjectivity or power-games. That is not the only alternative to the lost illusion of perfect objectivity of science. To find a viable alternative we will need to examine why scientific objectivity is no longer common sense.

The process is already well underway. Towards the end of the last century, just too many things began to go wrong for science. First we discovered how mankind has been polluting the environment. And sometimes the pollution was worse when the science was the strongest. The first big pollution scare came in 1963 with Silent Spring, where the death of the songbirds was explained by their being poisoned with agricultural pesticides. Then we had the accidents in civil nuclear power. Of all industries this was the one most completely based on science. We might have expected that an industry created and run by scientists would not be vulnerable to sloppy workmanship and elementary blunders; but we were wrong. In both those cases, as in many others, the pattern was that even where science had defined the situation, something would unexpectedly go wrong, leading to an accident or disaster. Then science would be brought it for the attempt to understand the accident and to prevent its happening again. It was as if science was chasing after itself in the cleanup jobs, retrospectively correcting its own mistakes.

The public’s experience of values, priorities, choices and exclusions has come through debates on science in fields relating to health and the environment. For a very long time, supporters of ‘alternative energy’ have pointed to the vast disparity between the meagre funds doled out to them for research and development, and the huge sums still lavished on the moribund nuclear power industry. In medical research, patients’ groups have observed how the lion’s share of the resources, even those collected and allocated by charities, goes on that ‘basic’ research which someone hopes and claims will solve the problems of cause and cure of the disease. At the same time, research on the quality of treatments and of care is left on the margins. The reasons are plain: everyone hopes for a ‘magic bullet’ which will kill the pathogen that makes us sick. Also, that sort of research is also useful in building a career in the relevant research science. By contrast, treatment and care are the ‘soft’ sciences, in which there are no Nobel prizes. It doesn’t take much imagination to see how particular sets of values are built into the ruling criteria of quality in science.

Why science is now post-normal
In all these ways, the public are becoming aware that values influence both the shape of what we know, and the selection of what we might know. And this can happen because science can no longer promise to deliver certainty when we need it. The old illusion of objectivity is passing into history. We should not reject it completely, for there is a good core of truth there. Instead, we should explain why it works where it does, and then present a modified, enriched version of objectivity for those other cases. The need for understanding is urgent. In an ever increasing number of policy issues we find science where the uncertainties are gross and the value-commitments are dominant. Looking at issues like global climate change, gender-bending pollutants, the disposal of nuclear wastes, and species extinction, to say nothing of the GRAINN technologies like reproductive engineering, we have the shape of the new policy predicaments. In such issues, we can say that in total contrast the to objectivity we once thought we had, the facts are uncertain, values in dispute, stakes high, and decisions urgent. Indeed, whereas for generations we contrasted hard objective scientific knowledge with soft subjective values, now we have policy decisions that are hard in every way, for which our scientific knowledge is irremediably soft. Where do we go from here?

…. (Description of Post-Normal Science)
Post-Normal Science isn’t a theory; we do better to see it as an insight. The image of that rainbow-quadrant tells us something about our current predicament. There are hosts of urgent policy problems involving science, for which routine expertise is totally inadequate, and for which even the best professional knowledge and judgement are insufficient. This is when, as in the outer strip, either or both of systems uncertainties and decision stakes are large. But if all the trained people can’t tell us what to do, how are we ever to make good, correct decisions on these difficult and urgent issues?

There is no easy answer. It’s most likely that we will make many mistakes, perhaps some of them disastrous. But with the insights of Post-Normal Science we can avoid even worse ones, by refraining from putting our trust in methods that are irrelevant or misleading. In both of the traditional cases, there is an assumption that The Expert Knows Best. It might be the researcher or the professional, or even the technician. He has the training, and he can spout scientific technicalities that leave the layperson totally bemused. In the ideal model of the process, the expert person starts with the science, and then deduces what should be done in practice. This model assumes that the world of practice is sufficiently like the world of science, so that the deduction is accurate. For ‘applied science’, it works routinely; for ‘professional consultancy’, it needs some skill and judgement in interpretation. In those traditional cases, those without expert training would seem to have little to contribute to the process of inquiry or decision.

When we come to the situations where Post-Normal Science is appropriate, where uncertainties and value-loadings cannot be denied, that old model of scientific deduction is inappropriate. Instead we need dialogue. In this, everyone has something to learn from everyone else. Of course the experts will have a special command of technical issues. But others can know better how well, or how badly, the scientific categories fit in with the reality that they experience. Many policy debates hinge on ‘safe limits’. It doesn’t need a Ph.D. to be able to ask intelligent questions about safety tests, and whether they are truly realistic in relation to practice. Thus, we need to know whether the sample populations included (for example) children and pregnant women, or animals that breathe air close to the soil. We need to know whether the specifications for safe use are likely to be respected in real industrial or agricultural situations (in Third World locations, it is prudent to assume they are not). Epidemiological data can be subject to errors and omissions in their collection, and distortion and bias in the definition of their categories. Local people can spot such flaws more effectively than experts from a faraway centre. All such issues can be put by people who have independence and common-sense. They can also query whether lab tests, even if performed quite properly by ‘applied science’ turn out to be irrelevant or misleading if applied uncritically in a Post-Normal situation.

Instead of an ‘objectivity’ that requires a denial of uncertainty and of value-commitments, we should cultivate ‘integrity’. For our dialogue on policy issues, we just need participants to engage in a ‘negotiation in good faith’, each advancing their case on the basis of their own perspectives and commitments, but respecting the integrity of those with whom they disagree. Those with a less expert but broader perspective can ask the sorts of questions that never occur to those who are scientifically trained. For the experts work and think inside a paradigm of scientific problems that can be tidily solved, Policy issues are inherently messy, complex and unpredictable are outside their training. The question, “What about …?” can inject something totally new into the dialogue. It amounts to reminding us all of Murphy’s Law, something that is totally absent from scientific training, but totally necessary for survival in the real world.

Appreciating the vital role of those others in the dialogue, we call them the Extended Peer Community. For they are full participants in the process, learning and also teaching. And they bring with them what we might call ‘Extended Facts’. For scientists will necessarily and justifiably focus on the information that is certified by their quality-assurance programmes. This is usually publication in refereed journals; but it can also include data produced in-house by respected research agencies. All this is produced under the standardised, idealised conditions that are necessary for successful research. But the Extended Peer Community has other sources. In policy issues, investigative journalism is a key resource, as are documents that were not originally intended for public view. In addition, there is local knowledge, including the place, its inhabitants of all sorts and species, and its history, traditions and special values. All these ‘extended facts’ are vital to the policy processes. They are excluded from the perspective of the ‘normal’ experts and professionals; it is the post-normal extended peer community that introduces them as valid contributions to the debate.

As we consider the essential role of the extended peer community, our vision of post-normal science reminds us of a great variety of endeavours to adapt science to the needs of a modern democratic society. People have spoken of ‘critical science’, ‘citizens’ science’, ‘civic science’, ‘community research’, ‘action research’ and ‘open science’, as well as ‘environmental’, ‘ecological’ and ‘sustainability’ science. Each title has its own flavour, and its own authentic perspective on the whole problem. We offer ‘post-normal’ as one in that family. For us, it expresses two key insights. First, that these times are far from ‘normal’. Second, that ‘normal’, puzzle-solving science is now totally inadequate as a method and a perspective, for the great policy issues of our time. Uncertainty now rules political as well as environmental affairs. And the value-commitments of people, reflected in their lifestyle choices, will determine whether the human race makes it through to sustainability, or not.

Finally, by focusing on the science itself rather than on the political processes, our insight brings reassurance and legitimacy to two important sorts of participants. The scientists themselves can be liberated from the confusion and self-doubt resulting from their discovery that some scientific problems cannot be solved by ‘normal’ methods. The failure to produce conclusive information about pollution or climate change is not the fault of the science or the scientists themselves. It is because we live in a new age where science is necessary but not sufficient. And for the extended peer community, they are no longer relegated to second-class status, and their special knowledge is no longer dismissed as inferior or bogus. They are full partners in the dialogue, who have much to teach as well as to learn. Both sides benefit from the dispelling of the illusion of scientific objectivity. That is the way forward, as expressed in the title ‘post-normal’.

Extended Peer Communities have a vital role in exposing issues that the official establishments do not, or choose not to, notice. A famous case in point is the addictive properties of the diazapam tranquillisers. On their introduction in 1963, they were hailed as the new ‘magic bullets’, of the sort that our superstitious pharmacological culture seems to crave. There were plenty of voices of caution and concern about addiction and long-term effects, but they were ignored by prescribers and by regulators alike. Then in 1979 a popular British consumers’ TV programme, Esther Rantzen’s That’s Life, told the story of mass addiction, long-term and incurable, to the drugs. She did not need to understand the biochemistry of the drug. It was enough for her to pay attention to, and then verify, the reports that she was receiving from desperate victims. The scandal broke, sales declined immediately, and some nine years later the official U.K. Committee on Safety of Medicines issued guidelines for safe use of the drug.

Counterfactual opinions and the peril to the planet: A commentary on Paul Baer’s essay ‘the worth of an ice sheet’

Posted March 12th, 2007 by Jerry Ravetz and filed in A post-normal climate

Paul Baer has done great service in reminding us that Stern did not merely warn of possible catastrophe, but that he also effectively set a ‘safe limit’ for CO2. Thus both the environmental and the economics communities can feel satisfied.

It would appear that Stern’s relative optimism derives from a study that recorded a thousand runs of a ‘Monte Carlo’ computer simulation of the economic effects of different temperature increases. These effects are divided into three categories: market impacts, non-market impacts, and “catastrophic” impacts. Paul’s essay shows the results for the last of these three. A glance at the graph shows that in the distribution of possibilities, there’s nothing much to worry about until things hit 3 degrees C. Hence on Stern’s figure showing various possible impacts, on the really serious irreversible global threats (at the bottom) we don’t in practice get into the ‘warm’ orange zone until we are well past two degrees. At a mere two degrees, there might be some local nasties, like coral and glaciers disappearing and the Sahel drying up even more, but otherwise things are generally OK.

Stern’s policy conclusion is a reminder of the folkways of mainstream economists in the management of uncertainties. I have sketched a theoretical explanation of this tendency, in terms of the harmony between the socio-political functions and the methods of mainstream economics. [Ravetz 1994-5] In the study that Silvio Funtowicz and I did on the ‘magic number’ of 2% GDP produced by W.H. Nordhaus [Funtowicz & Ravetz 1994], we analysed his ingenious management of uncertainties (which had been presented quite transparently, enabling our critical scrutiny). These produced the ‘magic number’ of 2% of GDP, something big enough to give the author credibility in the debate, but small enough to keep complacency going for another decade.

In this present case we find that Nordhaus’ contribution again plays a crucial role. But here the stakes are much higher, and the issues of uncertainty more critical. The ‘effects’ study on which the whole simulation of catastrophic impacts in PAGE is based was organised by Nordhaus himself, and done nearly fifteen years ago, when the scientific debate on climate change, and public awareness of its consequences, were still in their very early stages. Even as information about opinions, it is scientifically obsolete.

It is very far indeed from being an established scientific fact. It would be disastrously naïve to make uncritical use of such an unsure data item in a policy argument. For that is the ‘multiplier’ that converts physical data to economic damage. With a different number put into the calculations, the dots on the graph would not lie so tamely near the zero axis, but could jump up and warn us of trouble ahead even at one extra degree of warming.

Thus this opinion-based coefficient is even more crucial in the calculation than the ‘social discount rate’ that expresses the value of what posterity has done for us, as assessed either by ourselves or (as Nordhaus prefers) by ‘the market’. [Nordhaus 2007, p. 21]

In the view of the recognised danger that the world climate system could soon tip over into an irreversible destructive process, is that single piece of obsolete evidence about counterfactual opinions sufficiently robust to function as a support for a conclusion that a little bit of global warming won’t hurt too much? What are the error-costs of accepting a two-degree safe limit? Have these been considered by Dr. Stern or his colleagues? Invoking error-costs does not require the radical perspective of Post-Normal Science, but only the elementary prudence that even Rational Actors are supposed to have. But of this consideration, we see nothing. The really serious flames on Dr. Stern’s graph all lie to the right of the critical two-degree line.

As a piece of politically oriented economic analysis, the Stern report is a magnificent success. It has certainly provided the imprimatur of Economics to the growing concerns about global climate change. But as Paul Baer discovered, tucked away inside there is a source of comfort for the ‘skeptics’ who still need to believe that our profit-oriented system can solve whatever global problems it confronts, and will do so in good time. Which aspect of Stern will be more important in the debate?


Clark, J., Burgess, J. & Harrison, C. M. (2000) “I struggled with this money business”: respondents’ perspectives on contingent valuation. Ecological Economics 33(1): 45-62.

Funtowicz, S.O. and J.R. Ravetz, 1994, The Worth of a Songbird: Ecological Economics as a Post-Normal Science, Ecological Economics, 10/3, pp 197-207.

Nordhaus, W., 2007, The Stern Review on the Economics of Climate Change, http://nordhaus.econ.yale.edu/SternReviewD2.pdf

Ravetz, J.R., 1994-5, Economics as an Elite Folk-Science: the Suppression of Uncertainty, The Journal of Post-Keynesian Economics, 17/2, pp165-184.