Saat sähköpostiisi kirjatilauksesi maksutiedot. Kirjat toimitetaan sinulle postitse mahdollisimman pian.
Saat sähköpostiisi kirjatilauksesi maksutiedot. Kirjat toimitetaan sinulle postitse mahdollisimman pian.
A lot is at stake in the often-heated debates over the best way to handle the pandemic. The world economy is in crisis and the lockdown is excessively expensive. How serious is the pandemic? What are the available options? Countries that have not succeeded in suppressing the virus have started to lift constraints. Governments listen to all kinds of experts. However, the opinions of experts even within a single discipline or field – such as epidemology – are deeply divided.
The paradox is this. On the one hand, we have much more knowledge, for example, about viruses and the diseases they cause than humanity had before the modern scientific breakthroughs. Many viral diseases have been successfully eradicated, suppressed, or rendered relatively harmless. In the early 21st century, a large number of people has been carefully trained to do scientific research on, among other things, viruses and the diseases they cause.
On the other hand, we also know that expert knowledge is uncertain, interpretive, and value-laden. Not only can experts draw completely opposite conclusions on substantive issues, but their perceptions can also change dramatically in a short period of time. This holds especially when there is uncertainty about the nature of the issue and about applicable categories.
Consider the case of the Finnish Institute for Health and Welfare (THL) and its prominent representatives. In late January, THL issued a press release stating that “the probability of cases in Finland is very low”. A month later, Mika Salminen, THL’s Director of Health Security, continued to believe that the risk of dying from the disease among those living permanently in Europe was low. He also considered Italy’s corona restrictions excessive.
Less than three weeks later, the estimates had turned to the other extreme. Now “measures to prevent the spread of the coronavirus will no longer save Finland from the corona epidemic”. Nothing can stop the virus from spreading. Based on these estimates, for example, the Minister of Social Affairs and Health, Aino-Kaisa Pekonen, estimated that about 35 percent of Finns could become infected. Even that would not suffice for reaching the herd immunity that the government seems to continue to pursue for example in its May proposal for a new law, despite the prevention rhetoric.
We humans reason on the basis of prototypes, analogies, metaphors, and stories. When a new situation comes before us, we have to decide quickly what it is all about. We need to find a suitable classification, relate the new situation to something familiar, and place the event into a story. For example: the disease caused by this coronavirus is similar to flu. Therefore, Covid-19 belongs to an abstract category and the prototype for that category is flu. The flu cannot be stopped, but its spreading can be slowed down and limited to some extent. Influenza viruses propagate in waves. The spread of many flu-type diseases is confined by the relatively extensive immunity achieved through infections. Against influenza, people can also be vaccinated.
We rely on abstract concepts and models as we try to assess the possibilities and probabilities of an open and complex world. The choice of prototype, comparisons, and story is also influenced by anticipations and values. Once the basic selections have been made, they become fixed quickly. Moreover, our perceptions of exemplary cases and the stories we adopt interact with our normative judgments. Studies show that after this initial selection, even a strong evidence is often not enough to turn experts’ heads. The figures and estimates are fitted to the story. For example, in this case, the corona mortality rate is fitted to the information about deaths caused by influenza epidemics. Contrary evidence is downplayed and gaps are filled with ideological stories.
At present, in Finland, both the government and many citizens believe in a THL-style story, which is based on “flu provides the relevant prototype” classication, and which at level of practical policies comes close to the implications of the herd immunity theory, even if only with some significant reservations. It is equally true that a large number of experts in Finland and elsewhere in the world have questioned this classification and its implications. Numerous citizens, perhaps the majority of Finns, have also come to a critical assessment. It follows from this situation that, whatever the truth, some of the lay citizens are inevitably more right than some of the experts. Does this mean relativism? Are all views equally good; does “anything go”?
The problem of truth
In order to ensure the possibility of learning and critique, society must adhere to the ideals of truth, hypothetical attitude, and reciprocal (self)critique. Moreover, in an open, democratic and non-dogmatic society, there must be room for both autonomous expert practices and critical civic debate. We know that to become an expert requires focussed work for long periods of time; while also enlighted citizens must familiarise themselves with matters of public interest.
However, these general characterisations do not themselves solve the problem of truth. Who is entitled to judge the goodness and truthfulness of different choices and views? The secularization of science and the expansion of education can, at best, mean that the basic skills of citizens increasingly include the ability to critically debate, weigh the evidence, and use critical methods of obtaining information. These skills do not belong exclusively to researchers or university-trained politicians, civil servants and journalists.
However, specialized knowledge and skills require years and even decades of education. The process involves various qualifications as defined by the scientific community. Such knowledge in this case may include, for example, a grasp of the classification of thousands of viruses and an understanding of their structures and functions, including how they may penetrate animal cells such as those of humans. By moving from the molecular, cellular, and tissue levels to humans and the population, it is possible to study how viruses spread and cause diseases, or how they can also be used for medical purposes. Non-scientists can of course learn content-specific knowledge and skills. There is no such thing as secret science. Science is public and anyone can become familiar with it.
Research skills include experience in research of a specific field and a variety of scientific methods. There may be some specialized methods in fields such as biology or medicine incuding some specific methods of collecting data. Yet the analysis of data often relies, among other things, on statistical methods utilized across fields of research. For example, a prestigious article on how the coronavirus may spread already 2-3 days before the onset of symptoms, could very well have been written by a statistician or a social scientist, except for the specific skills needed to test for the presence of the virus and, perhaps, for the knowledge on the specifics of the hospital context.
Controversies over the biggest and deepest questions in any field and related conceptual argumentation tend to be similar across various sciences — insofar as no one orthodoxy has been able to assume a dominant position and to the extent there is room for pluralism. The differences may be greater within the fields than between them, especially at the fundamental level.
For example, the methodology of mathematical statistical modeling is a subject of widespread controversy. Biological and social systems are complex, open to external influences, subject to qualitative changes, and their components are active (with the exception of viruses, which are not actually living beings). Mathematics, however, requires a closed world in which connections are fixed, at least at some level of abstraction.
This is one of the key reasons why the real-world applications of mathematical-statistical methods tend to be arbitrary. As one of my colleagues wrote when commenting on models about how viruses spread, for any set of data points, it is easy to find a mathematical pattern that fits.
The other side of the coin is that once a prototype and story have been fixed, it is always possible to find a mathematical-statistical model that more or less accords with them. It is also possible that for some actors, the mathematical-statistical model itself determines the narrative (e.g. a purpose-built model is used to understand a new previously unknown phenomenon).
In the model used by THL, the second wave follows automatically if R rises above one (R is the rate of infections, i.e. how many people one infected person will transmit the disease to). Like in several other countries, in Finland too the either intended or implied effect of the partial dismantling of restrictions is to raise R. In this way, one’s own activities are in fact contributing to the future anticipated by the model. At the same time, however, it is assumed that a new wave of the virus is inevitable. The adopted prototype, basic analogy, story, and model are mixed with each other and with the reality. In other words, anticipations are reflexive while the world has become reified.
The focus of critical debate in both the scientific community and in civil society concerns the fundamental choices of category and story. In which general category this virus and the disease it causes should be placed? What analogies and metaphors should we rely on? What is the best story or scenario for the development of the pandemic and its end? At this level, there are significant differences between experts; the role of specialized knowledge and skills is relatively limited.
Rational argumentation remains nonetheless possible also at this level, just as it is possible to produce additional scientific – also empirical – evidence for different positions. For example, models based on influenza as a prototype include the assumption that mortality from the disease is low, 0.1% of those infected, or lower. However, the mortality rates indicated by many studies and the World Health Organization (WHO) are much higher, even tens of times higher.
Also THL’s preliminary antibody testing in Finland supports higher figures. If the antibodies have developed so far only for relatively few people, the mortality rate will probably be about one percent. Thus, the pursuit of herd immunity would require being prepared to accept the deaths of 30-40,000 Finns and more than 200,000 admitted to intensive care (this would be equivalent to 360,000 deaths in the UK). The influenza story begins to appear as inadequate not only in terms of the variety of effects but also in terms of their moral acceptability.
Critical reasoning is open to all citizens. In addition, it is particularly easy for professional researchers to critically scrutinise evidence, the claims made and their logic, largely – though not entirely – regardless of the field. No specialists have monopoly on knowledge. Similarly, there is no one indisputable dogma in any discipline (not even in physics or chemistry), a corpus of knowledge, or a purely technical machine-like method that would dictate what objective knowledge is. It is true that the foundations of physics or chemistry can form a relatively indisputable core today, but the situation is changing rapidly as we go to the big questions and to the forefront of scientific progress. For example, there are radically different interpretations of quantum mechanics and cosmology. Often these stem from fundamental questions at the level of philosophy and worldview.
Such diversity does not justify all-denying nihilism or Protagorean relativism (Protagoras was a character in Plato’s dialogues). Rather, it is this diversity and openness that makes science so interesting. In an effort to promote the collective learning of humanity, many great questions open up to which there are a variety of tentatively plausible answers. One of the implications is that there is also room for creating something new. Of course, in the following phase new claims must be examined and new hypotheses tested. This requires a huge amount of often-tedious work.
At its simplest, expertise is about claiming that someone knows something well. The expression “someone knows” is open. Neither the university nor any research institute have a monopoly on defining knowledge on any given subject, not even when their practices are organized around the ideal of truth and in terms of hierarchies of knowledge and learning. Good science is pluralistic and accepts that science progresses best through controversy and debate between different positions.
No expert knowledge guarantees the correctness of relevant judgements. Expert education does not eliminate the interpretability of the world or ambiguities about our knowledge of it. Experts disagree and often systematically so. The expert expresses opinions and tells stories that are in important ways also ethical and political. Thus, genuine expertise must be demonstrated on a case-by-case basis – and each case has its own implications in terms of effects of power.
The Swedish approach based on the idea of herd immunity has meant more deaths and injuries than in most countries. Who takes responsibility for them? Many horrors have been committed throughout modern history in the name of scientific authority. The same must not happen again in the context of the corona crisis.
 Even within the empiricist and analytical traditions, it has been widely accepted that observations are theory-laden and that values affect research. For instance, the methodological falsificationism of Imre Lakatos, developed already more than a half-a-century ago, leaves a lot of room for all kinds of theory- and value-based reasons and biases that prevents one from falsifying a theory. Lakatos, Imre: “Falsification and the Methodology of Scientific Research Programmes”, in Lakatos, I. & Musgrave, A. (1970) Criticism and the Growth of Knowledge, Cambridge: Cambridge University Press, pp.91-196; for a related analytical and empiricist but insightful account, see Laudan, Larry (1984) Science and Values: The Aims of Science and Their Role in Scientific Debate, Berkeley, CA: University of California Press. For a deeper and more critical analysis of the involvement of science in the development and reproduction of the fundamental mythologems of modern, especially liberal-capitalist societies, see Patomäki, Heikki (2019) “Mythopoetic Imagination as a Source of Critique and Reconstruction: Alternative Storylines about Our Place in Cosmos”, Journal of Big History, 3:4, pp.77-97, available at https://jbh.journals.villanova.edu/article/view/2463.
 ”Uuden koronaviruksen aiheuttamia tautitapauksia vahvistettu reilut 200 – THL seuraa tilannetta” [More than 200 confirmed cases of the disease caused by the new coronavirus – THL monitors the situation], THL 20.1.2020, https://thl.fi/fi/-/uuden-koronaviruksen-aiheuttamia-tautitapauksia-vahvistettu-reilut-200-thl-seuraa-tilannetta?redirect=%2F.
 ”Näin THL:n koronalausunnot ovat muuttuneet – 20.1.2020: ’Tapausten todennäköisyys Suomessa on hyvin pieni’”, [This is how THL’s public statements on coronavirus have changed – 20.1.2020: ‘The probability of cases in Finland is very small’], Iltalehti 13.03.2020, https://www.iltalehti.fi/koronavirus/a/adef7f79-dfb9-4e17-9538-466e623568b7.
 However, both positions share the implication of “do nothing or as little as possible”. First, there was no danger and therefore nothing worth doing; soon, there was almost nothing that could be done because the virus will spread anyway.
 See note .
 Government proposal to Parliament for a temporary amendment to the Communicable Diseases Act HE 72/2020: “An easily contagious and, on average, mild viral infection such as Covid-19 causes in a non-resistant population a rapidly developing epidemic in which the daily number of new cases may initially increase exponentially.This increase will continue until a sufficient proportion of the population becomes infected, which in turn will reduce the number of cases, as there will no longer be enough susceptibility to sustain rapid spread.” In the same section, it is stated “there is a significant risk of prolongation”, apparently implying that the government wants to speed the epidemic up. https://finlex.fi/fi/esitykset/he/2020/20200072?search%5Btype%5D=pika&search%5Bpika%5D=tartuntatautilaki.
 See Lakoff, George & Johnson, Mark (1999) Philosophy in the Flesh. The Embodied Mind and Its Challenge to Western Thought, New York: Basic Books; Fauconnier, Gilles & Turner, Mark (2003) The Way We Think. Conceptual Blending and the Mind’s Hidden Complexities, New York: Basic Books; and Ricoeur, Paul (1984) Time and Narrative, vol. 1, trans.from French K.McLaughlin and D.Pellauer, Chicago: The University of Chicago Press.
 For example, in an interview, THL’s Director of Health Security Salminen reveals some of the values that have influenced his recommendations. He says, among other things, that “if you read more than an epidemiological part of the Hetemäki report, you will quickly see what the impact will be if the economy and foreign trade remain closed until the end of the year. Then suddenly we do not have the money to buy that vaccine when it comes.” The latter argument is absurd, and although the knowledge base of the first part is ambiguous as well (cf. https://www.eroonkoronasta.fi/), the quote reveals that Salminen believes that the most important thing right now is to open up the economy as quickly as possible. He also states, “I don’t like this isolation of the elderly”. The deaths of the elderly, on the other hand, do not seem to be a major concern. Opposition to state-tutelage and the priority of opening up the market economy point to (neo)liberal values. “Decision makers make their own assessments. According to Mika Salminen from THL, the isolation of the elderly appears as patronage, nor is he fully satisfied with Finland’s corona strategy in anyway”, Helsingin Sanomat 16.5., A12-A13, https://www.hs.fi/kotimaa/art-2000006509686.html.
 Experts do consider evidence, but not in an impartial manner. As Philip Tetlock expresses the problem succintly: “Whether we trace the problem to excessive skepticism toward dissonant data or insufficient skepticism toward consonant data, counterfactual beliefs often appear self-perpetuating, effectively insulated from disconfirming evidence by a protective belt of defensive maneuvers and further reinforced by an understandable disinclination to attribute confirming evidence to either methodological sloppiness or to partisan bias.” Tetlock, Philip (1999) “Theory-driven Reasoning about plausible pasts and probable futures in world politics: are we prisoners of our preconceptions”, American Journal of Political Science 43:2, p.345.
 In particular, if it is not certain whether infection creates long-lasting immunity, herd immunity becomes quickly an excessively uncertain goal (herd immunity means that a large part of a population has become immune to the infectious disease, providing indirect protection also to those who are not immune to the disease).
 I have discussed these issues more systematically in the context of social sciences in an article that dates back to the 1990s: Patomäki, Heikki (1994) “Pukekaamme keisareille kansalaisen vaatteet. Kriittisiä huomioita poliittisista asiantuntijakäytännöistä myöhäismodernissa yhteiskunnassa” [Should We Put Citizen’s Dress on the Emperors? Critical Notes on the Expert Practices in Latemodern Society], Kosmopolis,24:3, pp. 55-65. I have borrowed the title for this blog from this article.
 Eg. He, Xi, Lau, Eric H.Y. & al. (2020) “Temporal Dynamics in Viral Shedding and Transmissibility of COVID-19”, Nature Medicine 26:May, pp. 672–5.
 About the mostly positive relationship between rationality and pluralism, see Rescher, Nicholas (1996) Pluralism. Against the Demand for Consensus, Oxford: Clarendon Press.
 “Give me N data points, and I can give you a polygon (of degree N) that fits them all exactly. Whats the point/value/use? Fitting a smoother curve using some criterion of minimum ‘error’ is really no better.” Tony Lawson, email on the CSOG list on February 31, 2020. An illustrative example of how any definite ‘data’ can be rather arbitrarily fitted to a model or theory is the production function in neoclassical economics. Anwar Shaikh shows how a completely implausible data of the “humbug economy” is perfectly suited to the standard Cobb-Douglas production function. Shaikh, Anwar (1974) “Laws of Production and Laws of Algebra: The Humbug Production Function”, The Review of Economics and Statistics, 56:1, pp. 115-120.
 Anticipations can become self-fulfilling or self-denying. See Patomäki, Heikki (2018) “Reflexivity of Anticipations in Economics and Political Economy”, in R.Poli (ed.) Handbook of Anticipation. Theoretical and Applied Aspects of the Use of Future in Decision Making, Cham: Springer, first online December 2018, DOI: https://doi.org/10.1007/978-3-319-31737-3_16-1; print edition forthcoming in 2020.
 Reification is a complex idea and there is a wide literature on it, involving various controversies and debates. What suffices here is the Wikipedia definition: ”Reification (also known as concretism, hypostatization, or the fallacy of misplaced concreteness) is a fallacy of ambiguity, when an abstraction (abstract belief or hypothetical construct) is treated as if it were a concrete real event or physical entity. In other words, it is the error of treating something that is not concrete, such as an idea, as a concrete thing. A common case of reification is the confusion of a model with reality: ’the map is not the territory’.” https://en.wikipedia.org/wiki/Reification_(fallacy)
 As translated into English: “Preliminary results from a population survey by the National Institute for Health and Welfare show that very few have developed antibodies to the new coronavirus in the Helsinki and Uusimaa Hospital District (HUS)”. https://thl.fi/fi/-/uudenmaan-vaestossa-vain-harvalla-esiintyy-uuden-koronaviruksen-vasta-aineita.
 See discussions in my blogs such as https://patomaki.fi/en/2017/08/misuses-of-quantum-theory-in-our-real-evolutionary-cosmos-part-i/. On the philosophical and ideological implications of basic scientific theories, see Patomäki, Heikki. 2010. “After Critical Realism? The Relevance of Contemporary Science,” Journal of Critical Realism 9: 1, 59-8; and Patomäki, “Mythopoetic Imagination” [note 1].
 ”Sweden’s per capita coronavirus death toll is among the highest in the world — a sign its decision to avoid a lockdown may not be working”, Business Insider, 22 May 2020, https://www.businessinsider.com/sweden-coronavirus-per-capita-death-rate-among-highest-2020-5?r=US&IR=T.