[E]volutionary economics is a work in progress…. The term “evolutionary economics” has been used to denote a wide range of economic research and writing…. [T]he authors, believe that the value of a broad theoretical perspective, such as that of evolutionary economics, should be judged in terms of the strength and quality of the understanding of empirical phenomena and the illumination of policy questions provided by research oriented by that perspective. We believe that the research done over the last thirty years oriented by evolutionary economic theory has amply demonstrated the value of that theory, and we want to increase the number of scholars who appreciate that. (Nelson et. al. 2018)
(….) At the root of the difference between evolutionary economics and economics of the sort presented in today’s standard textbooks is the conviction of evolutionary economists that continuing change, largely driven by innovation, is a central characteristic of modern capitalist economies, and that this fact ought to be built into the core of basic economic theory. Economies are always changing, new elements are always being introduced and old ones disappearing. Of course economic activities and economic sectors differ in the pace and character of change. In many parts of the economy innovation is rapid and continuing, and the context for economic action taking is almost always shifting and providing new opportunities and challenges. And while in some activities and sectors the rate of innovation is more limited, attempts at doing something new are going on almost everywhere in the economy, and so too change that can make obsolete old ways of doing things. Neoclassical theory, which is a significant influence on how most professionally trained economists think, represses this. (Nelson et. al. 2018)
There are four chief obstacles to grasping truth, which hinder every man, however learned, and scarcely allow anyone to win a clear title to knowledge; namely, submission to faulty and unworthy authority, influence of custom, popular prejudice, and concealment of our own ignornance accompanied by an ostentatious display of our knowledge.
— Roger Bacon cited in Stanislav Andreski, Social Sciences as Sorcery
[W]hat we have to deal with in the study of society and culture, indicates its purely intellectual difficulties, and shows how much easier are physics, chemistry or even biology. Even this, however, is not the whole story: for imagine how sorry would be the plight of the natural scientist if the objects of his inquiry were in a habit of reacting to what he says about them: if the substances could read or hear what the chemist writes or says about them, and were likely to jump out of their containers and burn him if they did not like what they saw on the blackboard or in his notebook. And imagine the difficulty of testing the validity of chemical formulae if, by repeating them long enough or persuasively enough, the chemist could induce the substances to behave in accordance with them — with the danger, however, that they might decide to spite him by doing exactly the opposite. Under such circumstances our chemist would not only have a hard time trying to discover firm regularities in his objects’ behaviour but would have to be very guarded in what he said lest the substances take offense and attack him. His task would be even more hopeless if the chemicals could see through his tactics, organize themselves to guard their secrets, and devise counter-measures to his maneouvres — which would be parallel to what the student of human affairs has to face. (Andreski 1973, 20-21, in Social Sciences as Sorcery)
There is no reason to deny the existence of phenomena known to us only through introspection; and a number of philosophers have pointed out the impossibility of carrying out Carnap’s programme (accepted as a dogma by the behaviourists) of translating all statements about mental states into what he calls the physicalist language. I would go even further and agrue that physics itself cannot be expressed in the physicalist langauge alone because it is an empirical science only insofar as it includes an assertion that its theories are corroborated by the evidence of the senses; and we can assign no meaning to the latter term without entailing a concept of self…. Thus you cannot give an account of the evidential foundations of physics without hearing and uttering ‘I’. And what kind of meaning can you attach to this word without using the knowledge obtained through introspection; and without postulating the existence of other minds within which processes are taking place which are similar to those which you alone can observe? (Andreski 1973, 21-22, in Social Sciences as Sorcery)
At this point let me say a few words about the often debated question whether any of the social sciences is a ‘real’ science. As often happens with such debates the arguments for as well as against omit the obvious truth that the answer to this question will depend on what we mean by science. If we mean exact science like physics or chemistry, then neither economics nor psychology nor sociology nor any other kind of research into human conduct is a science [, which obviously includes economics]. But if we agree to affix this honorific label to any kind of systematic study which aims at providing careful descriptions, substantiated explanations and factually supported generalizations, then we can say that the above mentioned branches of learning are sciences — although the propriety of this appellation will depend on whether we decide on the basis of aspirations or actual performance, and whether we look at the average or at the highest achievements. (Andreski 1973, 22-23, in Social Sciences as Sorcery)
Though formidable enough, the methodological difficulties appear trivial in comparison with the fundamental obstacles to the development of an exact science of soceity which puts it on an entirely differnt plane from the natural sciences: namely the fact that human beings react to what is said about them. More than that of his colleagues in the natural sciences, the position of an ‘expert’ in the study of human behaviour resembles that of a sorcerer who can make the crops come up or the rain fall by uttering an incantation. And because the facts with which he deals are seldom veifiable, his customers are able to demand to be told what they like to hear, and will punish the court physicians for failing to cure them. Moreover, as people want to achieve their ends by influencing others, they will always try to cajole, bully or bribe the witch-doctor into using his powers for their benefit and uttering the needed incantation … or at least telling them something pleasing. And why should he resist threats and tempations when in his specialty it is so difficult to prove or disprove anything, that he can with impunity indulge his fancy, pander to his listeners’ loves and hates or even peddle conscious lies. His dilemma, however, stems from the difficulty of retracing his steps; because very soon he passes the point of no return after which it becomes too painful to confess that he has been taking advantage of the public’s gullibility. So, to allay his gnawing doubts, anxieties and guilt, he is compelled to take the line of least resistance by spinning more and more intricate webs of fiction and falsehood, while paying ever more ardent lip-service to the ideas of objectivity and the pursuit of truth. (Andreski 1973, 24, in Social Sciences as Sorcery)
So to examine the validity of the claim that these are highly useful branches of knowledge, let us ask what their contribution to mankind’s welfare is supposed to be. To judge by the cues from training courses and textbooks, the practical usefulness of psychology consists of helping people to find their niche in society, to adapt themselves to it painlessly, and to dwell therein contentedly and in harmony with their companions. [We can ask the same question about economics.] So, we should find that in countries, regions, institutions or sectors where services or psychologists [and economists] are widely used, families are more enduring, bonds between spouses, siblings, parents and children stronger and warmer, relations between colleagues more harmonious, the treatment of recipients of aid better, vandals, criminals and drug addicts fewer, than in places or groups which do not avail themselves of the psychologists’ skills. On this basis we could infer that the blessed country of harmony and peace is of course the United States; and that it ought to have been becoming more and more so during the last quarter of the century in step with the growth in numbers of sociologists, psychologists [, economists] and political scientists. (Andreski 1973, 26, in Social Sciences as Sorcery)
The self-fulfilling prophecy constitutes only one (and fairly narrow) manifestation of the much more general disposition of human beings to be influenced by what is said about them and their environment. On the individual plane everybody knows that one can make a person discontented by deploring the circumstances under which he lives, encourage his endeavour by praise, or discourage it by sarcasm…. [I]f we show that the idea that ‘honesty is the best policy’ is groundless we remove an important incentive to honesty. (Andreski 1973, 31, in Social Sciences as Sorcery)
Even such purely academic theories as interpretations of human nature have profound practical consequences if disseminated widely enough. If we impress upon people that science has discovered that human beings are motivated only by the desire for material advantage, they will tend to live up to this expectation, and we shall have undermined their readiness to moved by impersonal ideals. By propagating the opposite view we might succeed in producing a larger number of idealists, but also help cynical exploiters to find easy victims. This specific issue, incidentally, is of immense actual importance, because it seems that the moral disorientation and fanatic nihilism which afflict modern youth have been stimulated by the popular brands of sociology and psychology [and economics] with their bias for overlooking the more inspiring achievements and focusing on the dismal average or even the subnormal. When, fraudulently basking in the glory of the exact sciences, the psychologists [, theoretical economists, etc.,] refuse to study anything but the most mechanical forms of behavior — often so mechanical that even rats have no chance to show their higher faculties — and then present their mostly trivial findings as the true picture of the human mind, they prompt people to regard themselves and others as automata, devoid of responsibility or worth, which can hardly remain without effect upon the tenor of social life. (Andreski 1973, 33-34, in Social Sciences as Sorcery)
Abstrusiveness need not impair a doctrine’s aptness for inducing or fortifying certain attitudes, as it may in fact help to inspire awe and obedience by ‘blinding people with science’. (Andreski 1973, 35)
If the rank and file come to be convinced that the leaders are crooks, cowards or fools, their actions will differ radically from what would be, were they convinced that the leaders are dedicated men of great courage and intelligence. Conversely, the leaders’ behaviour will to some extent depend on the popular image of their office, which will determine whether the latter carries with it the dignity which they are expected to live up to, or whether they will have no reputation to preserve. (Andreski 1973, 36, in Social Sciences as Sorcery)
The difficulty of verifying assertions about human relations gives wide scope to ulterior motives, and provides immunity for the purveyors of false information. (Andreski 1973, 38, in Social Sciences as Sorcery)
If you listen to the practitioners of social and economic research talking informally, you will easily find that not only are they very well aware of the aforementioned [social status and economic gain] pressures, but also that they fully take them into account in making plans and arrangements about what to study, to write, or to say. This, however, happens on the everyday bread-and-butter level, while neither their pronouncements ex cathedra nor their publications ever mention that these pressures might make a difference to the trustworthiness of the results of social research, and to the prospects of its ever attaining the level of objectivity and reliability of the natural sciences. (Andreski 1973, 39, in Social Sciences as Sorcery)
To summarize: the propensity of human objects of inquiry to react to what is said about them creates three kinds of obstacles to the development of the social sciences. The first is of a methodological nature and consists of the difficulties surrounding the task of verifying propositions which can influence the happenings which they purport merely to describe or analyse. The second kind of impediment stems from the presures upon the direction of the inquiry and the dissemination of its results, motivated firstly by the awareness that what is said might influence what will happen; and secondly by the desire … to hear what pleases them. The disarray wrought by the operation of the two aforementioned factors prduces the third kind of impairment in the shape of ample opportunities for getting away with falsehoods and crypto-propaganda. (Andreski 1973, 39-40, in Social Sciences as Sorcery)
Once an activity becomes a profession — this is, a way of making a living — the dedicated amateurs tend to fall into second place, greatly outnumbered by the practitioners guided primarily (if not soley) by the normal motives of the market place — which commonly boil down to the desire to get the most at the least cost to themselves. In other words, as soon as it becomes apparent that there is money in it, the saleability of goods rather than their intrinsic excellence becomes the dominant criterion. (Andreski 1973, 43, in Social Sciences as Sorcery) [i.e., literature-only economics; see Payson 2017.]
If everything is wonderfully dovetailed and adjusted, then we should leave things alone. More insidiously than nineteenth century organicism, functionalism propagates a conservative ideology in the name of science; while, for those things its practitioners do not like, they have the aforementioned epithet ‘dysfunctional’, which enables them to insinuate a condemnation without openly saying so, and to enlist the authority of science for their ideologies or personal preferences. For if somebody says that something is good or bad, he might be asked: for what?, or for whom?, or why? So he might be obliged to take off the mask of objective omniscience and to reveal, firstly, his values and, secondly, the reasons for his assumptions about the likely consequences of various arrangements or courses of action; whereas by using ‘functional’ and ‘dysfunctional’ instead of ‘good’ and ‘bad’, a functionalist can hide behind a façade of objectivity and invoke the magic of science to back his crypto-propagandist insinuations. (Andreski 1973, 57-58, Social Science as Sorcery)
The article to which I referred in my letter supplied one or more of the innumerable instances of that ever-popular kind of explanation which consists of a tautological rephrasing which tells us nothing that we did not understand before. An explanation which Moliere ridiculed three hundred years ago in one of his plays, where one of the characters answers the question about why opium makes people sleep by saying that it is because of its soporific power. In historiography and social sciences this kind of explanation crops up again and again. Thus, to take an example of a great scholar who luckily did not confine himself to this, Werner Sombart attributed the development of capitalism to the spread of ‘the spirit of capitalism’, without telling us how we could find out that this spirit was spreading except by observing activities which add up to the process known as the development of capitalism. (Andreski 1973, 68, in Social Science as Sorcery)
The attraction of jargon and obfuscating convolutions can be fully explained by the normal striving of humans for emoluments and prestige at the least cost to themselves, the cost in question consisting of the mental effort and the danger of ‘sticking one’s neck out’ or ‘putting one’s foot in it’. In addition to eliminating such risks, as well as the need to learn much, nebulous verbosity opens a road to the most prestigious academic posts to people of small intelligence whose limitations would stand naked if they had to state what they have to say clearly and succinctly. Actually, the relationship between the character of a jargon-mongerer and the amount of his verbiage can be expressed in the formula below, which can be applied in the following manner. The first step is to assign intuitively estimated scores for an author’s ambition, designated by A, and to knowledge, designated by K (which must always be greater then 0, as nobody knows exactly nothing). A must also be positive because, if somebody’s literary ambition is nil, they he writes nothing, and there is nothing to apply our equation to. V stands for verbose jargon. Our equation is
Why — I? Because when the knowledge matches the ambition there is no verbiage. When knowledge exceeds the ambition V becomes negative; and negative verbiage amounts to conciseness. However, since there is a limit to conciseness, V can never become less than — I; whereas there is not limit to verbiage, and so V increases indefinitely as ambition grows, while knowledge vanishes. (Andreski 1973, 82-83, Social Science as Sorcery)
Our formula cannot, of cours be treated as exact until measurable indices are devised for the variables, and then checked against empirical data. I do believe, however, that it is approximately true, and I invite readers to try it on the authors they read as well as on their colleagues, teachers or students. Its predictive and explanatory power is roughly the same as that of most theorems of mathematical economics. The many different kinds of people, ranging from an undergraduate who is trying to scrape through a dissertation without having learned anything, to a scholar with a fairly extensive knowledge but devoured by a craving for greatness. (Andreski 1973, 83, Social Science as Sorcery)
If you happen to be a student, you can apply the same test to your teachers who claim that what they are teaching you rests upon incontrovertible scientific foundations. See what they know about the natural sciences and mathematics and their philosophical foundations. Naturally, you cannot expect them to have a specialist knowledge of these fields; but if they are completely ignorant of these things, do not take seriously grandiloquent claims of the ultra-scientific character of their teachings. Furthermore, do not be impressed unduly by titles or positions. (Andreski 1973, 86, in Social Science as Sorcery)
As has often been said, measurement is the beginning of science (if we mean thereby exact science) because our ability to predict the behaviour of a phenomenon must remain very restricted until we can measure it. It does not follow, however, that no knowledge whatsoever is possible without measurement, nor that such knowledge cannot be worth having — which is precisely the conclusion which … many sociologists [and economists] have adopted in the mistaken belief that only thereby can they maintain the scientific character of their discipline. But the true scientific spirit consists of trying to obtain the nearest approximation to truth which is possible under the circumstances, and it is puerile to demand either perfect exactitude or nothing. those who refuse to deal with important and interesting problems simply because the relevant factors cannot be measured, condemn the social sciences to sterility, because we cannot get very far with the study of measurable variables if these depend on, and are closely interwoven with, immensurable factors of whose nature and operation we know nothing. A weakness of this kind diminishes the usefulness of economic theory … because it excludes from its universe of discourse immensurable but causally crucial factors … such as the balance of political power … or simply relegating them to the category of those things which are treated as ‘being equal’. (Andreski 1973, 123, in Social Science as Sorcery)
To substantiate their claims, the advocates of an exclusive concentration on quantification ought to demonstrate either that [political] corruption can be measured, or that it is a factor of no significance. The fist, … cannot be done, while to maintain that corrupt practices play no important part in social causation one must be either a hypocrite or a starry-eyed dreamer. (Andreski 1973, 124, in Social Science as Sorcery)
Even if the diagnosis offered on the foregoing pages is only partially correct, we have no grounds for expecting any great leap forward in the study of society which would replicate the rapid advances of the natural sciences. True, it is quite easy to conceive remedies against many of the ills stemming from the purely intellectual difficulties, which would work in a more perfect world. we could, for instance, insist that the economists should openly state the limitations and empirical reliability of their models, be prepared to take cultural (or, if you like, psychological and sociological [and the humanities, and literature, and religious studies, etc.]) factors into account, and desist from proffering advice on the basis of one-sided and coarsely materialistic statistics. We could demand that the psychologists should acquire some general culture, and acquaint themselves with the subtler products of the human mind before setting themselves up as experts on human nature. We could compel the sociologists to learn about history and philosophy, and the historians about the social sciences. Above all, we need a kind of intellectual puritanism which would regard money as a clear (even necessary) evil, and any manipulation of it as essentially polluting. Not that any great advantage would accrue if social scientists imitated monks and took vows of poverty; but, nonetheless, no steady advance will be possible without an ethical code which would forcefully condemn mercenary trimming as intellectual prostitution, and counter the natural human tendency not only to flatter and obey, but even to genuinely to adore those who control money or wield coercive power. The snag is that it is difficult to visualize who could enforce such requirements, and how. The difficulty here is the same as with finding the best form of government: we can readily agree with Plato that the best system would be that where the wisest and kindest rule, but nobody has so far been able to discover a practicable method for brining about such a state of affairs. (Andreski 1973, 231-232, in Social Science as Sorcery)
Some years before the First World War, a Parisian periodical asked some of the most prominent French figures in the various branches of what we would now call social sciences, and which were known at the time in France as les sciences morales, about what they regarded as the most essential method in their field. While other respondents sent back learned methodological disquisitions, Georges Sorel replied in one word: honesty. This lapidary answer has lost none of its relevance; but it is difficult to find any reasons for hoping that we shall ever have a society where absolute frankness would be the best policy for self-advancement. (Andreski 1973, 231-232, in Social Science as Sorcery)
Despite these irremovable obstacles, my own view on the prospects for the social sciences might be described as a desperate optimism. I say desperate because I do not see how our civilization could survive without important advances in our understanding of man and society. Having invented so many wonderous gadgets [e.g., nuclear weapons] which can be employed for its benefit only through the utmost use of reason, mankind has long ago passed the point of no return in this respect. No matter how valuable might be many ingredients of the old religious and moral traditions, the problem of how to reconcile human physical and spiritual needs with the environment created by technology, and how to assure mankind’s very survival, will not be solved by going back to the good old ways or dogmas. Consequently, I have no doubt that if the social sciences fall into a total and irremediable decadence, this will be a part of the general collapse of civilization, likely to be followed by an extinction of our species. No matter therefore how heavy are the odds against us, we should persist in trying to do our best, because the alternative is resignation in the face of an imminent catastrophe. (Andreski 1973, 232, in Social Science as Sorcery)
Provided some freedom of expression remains, we have reason to hope that no branch of learning will come to a complete standstill even when its main trunk succumbs to decay; because even during the ages of deepest ignorance and superstition, indomitable spirits with a natural bent for rational inquiry continued to crop up and add a brick or two to edifice of knowledge. What made their cerebrations more effective in the long run than the efforts of the vastly more numerous priests and mystagogues was the fact that the products of rational thought are cumulative, whereas mystic visions, fads, stunts and phantasmagorias not only add up to nothing, but even cancel one another out and merely sway minds to and fro, hither and thither. (Andreski 1973, 232-233, in Social Science as Sorcery)
This was a paper hard to read. It does not mean that the paper was badly written. The difficulty of the task that the author sought enforced him to write this difficult paper. After struggling a week in reading the paper, I am rather sympathetic with Delorme. In a sense, he was unfortunate, because he came to be interested in complexity problems by encountering two problems: (1) road safety problem and (2) the Regime of Interactions between the State and the Economy (RISE). I say “unfortunate,” because these are not good problems with which to start the general discussion on complexity in economics, as I will explain later. Of course, one cannot choose the first problems one encounters and we cannot blame the author on this point, but in my opinion the good starting problems are crucial to further development of the argument of complexity in economics.
Let us take the example of the beginning of modern physics. Do not think of Newton. It is a final accomplishment of the first phase of modern physics. There will be no many people who object that modern physics started by two (almost simultaneous) discoveries: (1) Kepler’s laws of orbital movements and (2) Galileo’s law of falling bodies and others. The case of Galilei can be explained by a gradual rise of the spirit of experiments. Kepler’s case is more interesting. One of crucial data for him was Tycho Brahe’s observations. He improved the accuracy of observation about 1 digit. Before Brahe for more than one thousand years, accuracy of astronomical observations was about 1 tenth of a degree (i.e. 6 minutes in angular unit system). Brahe improved this up to an accuracy of 1/2 minute to 1 minute. With this data, Kepler was confident that 8 minutes of error he detected in Copernican system was clear evidence that refutes Copernican and Ptolemaic systems. Kepler declared that these 8 minutes revolutionize whole astronomy. After many years of trials and errors, he came to discover that Mars follows an elliptic orbit. Newton’s great achievement was only possible because he knew these two results (of Galilei and Kepler). For example, Newton’s law of gravitation was not a simple result of induction or abduction. The law of square-inverse was a result of halflogical deduction from Kepler’s third law.
I cite this example, because this explains in which conditions a science can emerge. In the same vein, the economics of complexity (or more correctly economics) can be a good science when we find this good starting point. (Science should not be interpreted in a conventional meaning. I mean by science as a generic term for a good framework and system of knowledge). For example, imagine that solar system was composed of two binary stars and earth is orbiting with a substantial relative weight. It is easy to see that this system has to be solved as three-body problem and it would be very difficult for a Kepler to find any law of orbital movement. Then the history of modern physics would have been very different. This simple example shows us that any science is conditioned by complexity problems, or by tractable and intractable problem of the subject matter or objects we want to study.
The lesson we should draw form the history of modern physics is a science is most likely to start from more tractable problems and evolve to a state that can incorporate more complex and intractable phenomena. I am afraid that Delorme is forgetting this precious lesson. Isn’t he imagining that an economic science (and social science in general) can be well constructed if we gain a good philosophy and methodology of complex phenomena?
I do not object that many (or most) of economic phenomena are deeply complex ones. What I propose as a different approach is to climb the complexity hill by taking a more easy route or track than to attack directly the summit of complexity. Finding this track should be the main part of research program but I could not find any such arguments in Delorme’s paper. (Yoshinori Shiozawa, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 10/10/2017.)
1) My paper can be viewed as an exercise in problem solving in a context of empirical intractability in social science. It was triggered by the empirical discovery of complex phenomena raising questions that are not amenable to available tools of analysis, i.e., are intractable. Then the problem is to devise a model and tools of analysis enabling to cope with these questions. Then, unless someone comes with a complex system analysis or whatever tool that solves the problem at stake, a thing I would welcome, I can’t think of any other way to proceed than focusing on the very cognitive process of knowledge creation and portraying it as a reflective, open-ended, problem-first cognitive behavioral endeavour. It is an approach giving primacy both to looking and discovering rather than to assuming and deducing, and to complexity addressed in its own right rather than to complex systems in which complexity is often viewed tautologically as the behavior of complex systems. The outcome is a new tool of analysis named Deep Complexity in short. I believe that the availability of this tool provides a means to take more seriously the limitations of knowledge in a discipline like economics in which inconclusive and non demonstrative developments are not scarce when sizeable issues are involved.
2) Yoshinori Shiozawa raises the question of where to start from, from tractable problems or from the intractable? He advocates the former and suggests to “evolve to a state that can incorporate more complex and intractable phenomena”. But then, with what tools of analysis for intractable phenomena? And I would have never addressed intractability if I had not bumped into unresolved empirical obtacles. Non commutative complementarity is at work here: starting with the tractable in a discipline dominated by non conclusive and non demonstrative debates doesn’t create any incentive to explore thoroughly the intractable. It is even quite intimidating for those who engage in it. This sociology of the profession excludes de facto intractability from legitimate investigation. Then starting from the possibility of intractability incorporates establishing a dividing line and entails a procedural theorizing in which classical analysis can be developed for tractable problems when they are identified, otherwise the deep complexity tool is appropriate, before a substantive theorizing can be initiated. It is a counterintuitive process: complexification comes first, before a further necessary simplification or reduction. (Robert Delorme, (WEA Conference), 11/30/2017.)
In my first comment in this paper, I have promised to argue the track I propose. I could not satisfy my promise. Please read my second post for the general comments in discussion forum. I have given a short description on the working of an economy that can be as big as world economy. It explains how an economy works. The working of economy (not economics) is simple but general equilibrium theory disfigured it. The track I propose for economics is to start form these simple observations
As I have wrote in my first post, modern science started from Galileo Galilei’s physics and Johaness Kepler’s astronomy. We should not imagine that we can solve a really difficult problem (Delorme’s deep complexity) in a simple way. It is not a wise way to try to attack deep complexity unless we have succeeded to develop a sufficient apparatus by which to treat it. (Yoshinori Shiozawa, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 11/30/2017.)
Dear Dr Shiozawa, it seems that we are not addressing the same objects of inquiry. Yours seems to stand at an abstract level of modern science in general. Mine is much less ambitious: it is grounded in research on how to deal with particular, empirically experienced problems in real economic and social life, that appear intractable, and subject to scientific practice. Deep Complexity is the tool that is manufactured to address this particular problem. It may have wider implications in social science. but that is another story. (Robert Delorme, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 11/30/2017.)
You are attacking concrete social problems. I am rather a general theorist. That may be the reason of our differences of stance toward your problem.
Our situation reminds me the history of medicine. This is one of the oldest science and yet as the organism is highly complex system, many therapies remained symptomatic. Even though, they were to some extent useful and practical. I do not deny this fact. However, modern medicine is now changing its features, because biophysical theories and discoveries are changing medical research. Researchers are investigating the molecular level mechanism why a disease emerges. Using this knowledge, they can now design drugs at the molecular level. Without having a real science, this is not possible.
[Note Shiozawa’s implicit claim that previous medical science was not real science, but became real with the advent of molecular biology. No doubt molecular biology has opened up new domains of knowledge, but of course it is simply ludicrous to claim medicine wasn’t real science prior to molecular biology, as many perfectly valid scientific discoveries prior to and/or discovered without molecular biology are available to prove this assertion simply false. As Delorme states plainly below, this is scientism, not to mention an abysmal attempt to use revisionist history for purely rhetorical purposes. For more examples of Shiozawa’s scientism and sophistry see Semantic Negligence and for a description of literature-only economics see Payson 2017. For a good description of the kind of scientism Shiozawa is parroting see Pilkington 2016. To use one of Shiozawa’s favorite authors for go-to appeals to authority (unfortunately his memory doesn’t serve him well as Andreski contradicts his claim on RWER), see Stanislav Andreski’s Social Sciences as Sorcery (1973, 22-23).]
Economics is still in the age of pre-Copernican stage. It would be hard to find a truth mechanism why one of your examples occurs. I understand your intention, if you want say by the word of “deep complexity” a set of problems that are still beyond our ability of cognition or analysis. We may take a method very different from the regular science and probably similar to symptomatology and diagnostics. If you have argue in this way, it would have made a great contribution to our forum on complexities in economics. This is what I wanted to argue as the third aspect of complexity, i.e. complexity that conditions the development of economics as science.
To accumulate symptomatic and diagnostic knowledge in economics is quite important but most neglected part of the present day economics. (Yoshinori Shiozawa, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 12/1/2017, italics added.)
It is interesting to learn that, as an economist and social scientist, I must be in a “pre-Copernican” stage. Although what this means is not totally clear to me, I take it as revealing that our presuppositions about scientific practice differ. You claim to know what is the most appropriate way of investigating the subject I address, and that this way is the methods and tools of natural science. I claim to have devised a way which works, without knowing if it is the most appropriate, a thing whose decidability would seem to be quite problematic. And the way I have devised meets the conditions of a reflective epistemology of scientific practice, in natural science as well as in social science. Your presupposition is that the application of the methods of natural science is the yardstick for social science. This is scientism.
My presupposition is that there may be a difference between them, and that one cannot think of an appropriate method in social science without having first investigated and formulated the problem that is presented by the subject. As a “general theorist”, your position is enjoyable. May I recall what Keynes told Harrod: “Do not be reluctant to soil your hands”. I am ready to welcome any effective alternative provided it works on the object of inquiry that is at stake. It is sad that you don’t bring such an alternative. As Herb Simon wrote, ”You can’t beat something with nothing”. I borrow from your own sentence that “if you had argued this way, it would have made a great contribution to our forum…” (Robert Delorme, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 12/1/2017, italics added.)
Biological evolution is, as has often been noted, both fact and theory. It is a fact that all extant organisms came to exist in their current forms through a process of descent with modification from ancestral forms. The overwhelming evidence for this empirical claim was recognized relatively soon after Darwin published On the Origin of Species in 1859, and support for it has grown to the point where it is as well established as any historical claim might be. In this sense, biological evolution is no more a theory than it is a “theory” that Napoleon Bonaparte commanded the French army in the late eighteenth century. Of course, the details of how extant and extinct organisms are related to one another, and of what descended from what and when, are still being worked out, and will probably never be known in their entirety. The same is true of the details of Napoleon’s life and military campaigns. However, this lack of complete knowledge certainly does not alter the fundamental nature of the claims made, either by historians or by evolutionary biologists. (Pigliucci et al. 2006: 1)
On the other hand, evolutionary biology is also a rich patchwork of theories seeking to explain the patterns observed in the changes in populations of organisms over time. These theories range in scope form “natural selection,” which is evoked extensively at many different levels, to finer-grained explanations involving particular mechanisms (e.g., reproductive isolation induced by geographic barriers leading to speciation events). (Pigliucci et al. 2006: 1)
(….) There are a number of different ways in which these questions have been addressed, and a number of different accounts of these areas of evolutionary biology. These different accounts, we will maintain, are not always compatible, either with one another or with other accepted practices in evolutionary biology. (Pigliucci et al. 2006: 1)
(….) Because we will be making some potentially controversial claims throughout this volume, it is crucial for the reader to understand two basic ideas underlying most of what we say, as well as exactly what we think are some implications of our views for the general theory of evolutionary quantitative genetics, which we discuss repeatedly in critical fashion. (Pigliucci et al. 2006: 2)
(….) The first central idea we wish to put forth as part of the framework of this book will be readily familiar to biologists, although some of its consequences may not be. The idea can be expressed by the use of a metaphor proposed by Bill Shipley (2000) …. the shadow theater popular in Southeast Asia. In one form, the wayang golek of Bali and other parts of Indonesia, three-dimensional wooden puppets are used to project two-dimensional shadows on a screen, where the action is presented to the spectator. Shipley’s idea is that quantitative biologists find themselves very much in the position of wayang golek’s spectators: we have access to only the “statistical shadows” projected by a set of underlying causal factors. Unlike the wayang golek’s patrons, however, biologists want to peek around the screen and infer the position of the light source as well as the actual three-dimensional shapes of the puppets. This, of course, is the familiar problem of the relationship between causation and correlation, and, as any undergraduate science major soon learns, correlation is not causation (although a popular joke among scientists is that the two are nevertheless often correlated). (Pigliucci et al. 2006: 2)
The loose relationship between causation and correlation has two consequences that are crucial…. On the one hand, there is the problem that, strictly speaking, it makes no sense to attempt to infer mechanisms directly from patterns…. On the other hand, as Shipley elegantly show in his book, there is an alternative route that gets (most of) the job done, albeit in a more cicuitous route and painful way. What one can do is to produce a series of alternative hypotheses about the causal pathways underlying a given set of observations; these hypotheses can then be used to “project” the expected statistical shadows, which can be compared with the observed one. If the projected and actual shadows do not match, one can discard the corresponding causal hypothesis and move on to the next one; if the two shadows do match (within statistical margins of error, of course), then one had identified at least one causal explanation compatible with the observations. As any philosopher or scientist worth her salt knows, of course, this cannot be the end of the process, for more than one causal model may be compatible with the observations, which means that one needs additional observations or refinements of the causal models to be able to discard more wrong explanations and continue to narrow the field. A crucial point here is that the causal models to be tested against the observed statistical shadow can be suggested by the observations themselves, especially if coupled with further knowledge about the system under study (such as details of the ecology, developmental biology, genetics, or past evolutionary history of the populations in question). But the statistical shadows cannot be used as direct supporting evidence for any particular causal model. (Pigliucci et al. 2006: 4)
The second central idea … has been best articulated by John Dupré (1993), and it deals with the proper way to think about reductionism. The term “reductionism” has a complex history, and it evokes strong feelings in both scientists and philosophers (often, though not always, with scientists hailing reductionism as fundamental to the success of science and some philosophers dismissing it as a hopeless epistemic dream). Dupré introduces a useful distinction that acknowledges the power of reductionism in science while at the same time sharply curtailing its scope. His idea is summarized … as two possible scenarios: In one case, reductionism allows one to explain and predict higher-level phenomena (say, development in living organisms) entirely in terms of lower-level processes (say, genetic switches throughout development). In the most extreme case, one can also infer the details of the lower-level processes from the higher-level patterns produced (something we have just seen is highly unlikely in the case of any complex biological phenomenon because of Shipley’s “statistical shadow” effect). This form of “greedy” reductionism … is bound to fail in most (though not all) cases for two reasons. The first is that the relationships between levels of manifestation of reality (e.g., genetic machinery vs. development, or population genetics vs. evolutionary pathways) are many-to-many (again, as pointed out above in our discussion of the shadow theater). The second is the genuine existence of “emergent properties” (i.e., properties of higher-level phenomena that arise from the nonadditive interaction among lower-level processes). It is, for example, currently impossible to predict the physicochemical properties of water from the simple properties of individual atoms of hydrogen and oxygen, or, for that matter, from the properties of H20 molecules and the smattering of necessary impurities. (Pigliucci et al. 2006: 4-5)
Mechanical metaphors have appealed to many philosophers who sought materialist explanations of life. The definitive work on this subject is T. S. Hall’s Ideas of Life and Matter (1969). Descartes, though a dualist, thought of animal bodies as automata that obeyed mechanical rules. Julien de la Mettrie applied stricter mechanistic principles to humans in L’Homme machine (1748). Clockwork and heat engine models were popular during the Industrial Revolution. Lamarck proposed hydraulic processes as causes of variation. In the late nineteenth century, the embryologists Wilhelm His and Wilhelm Roux theorized about developmental mechanics. However, as biochemical and then molecular biological information expanded, popular machine models were refuted, but it is not surprising that computers should have filled the gap. Algorithms that systematically provide instructions for a progressive sequence of events seem to be suitable analogues for epigenetic procedures. (Reid 2007: 263)
A common error in applying this analogy is the belief that the genetic code, or at least the total complement of an organism’s DNA contains the program for its own differential expression. In the computer age it is easy to fall into that metaphysical trap. However, in the computer age we should also know that algorithms are the creations of programmers. As Charles Babbage (1838) and Robert Chambers (1844) tried to tell us, the analogy is more relevant to creationism than evolutionism. At the risk of offending the sophisticates who have indulged me so far, I want to state the problems in the most simple terms. To me, that is a major goal of theoretical biology, rather than the conversion of life to mathematics. (Reid 2007: 263)
— Robert G.B. Reid (2007, 263) Biological Emergences: Evolution by Natural Experiment. The Vienna Series in Theoretical Biology.
If the emergentist-materialist ontology underlying biology (and, as a matter of fact, all the factual sciences) is correct, the bios constitutes a distinct ontic level the entities in which are characterized by emergent properties. The properties of biotic systems are then not (ontologically) reducible to the properties of their components, although we may be able to partially explain and predict them from the properties of their components… The belief that one has reduced a system by exhibiting [for instance] its components, which is indeed nothing but physical and chemical, is insufficient: physics and chemistry do not account for the structure, in particular the organization, of biosystems and their emergent properties (Mahner and Bunge 1997: 197) (Robert 2004: 132)
— Jason Scott Robert (2004, 132) Embryology, Epigenesis, and Evolution: Taking Development Seriously
The science of biology enters the twenty-first century in turmoil, in a state of conceptual disarray, although at first glance this is far from apparent. When has biology ever been in a more powerful position to study living systems? The sequencing juggernaut has still to reach full steam, and it is constantly spewing forth all manner of powerful new approaches to biological systems, many of which were previously unimaginable: a revolutionized medicine that reaches beyond diagnosis and cure of disease into defining states of the organism in general; revolutionary agricultural technology built on genomic understanding and manipulation of animals and plants; the age-old foundation of biology, taxonomy, made rock solid, greatly extended, and become far more useful in its new genomic setting; a microbial ecology that is finally able to contribute to our understanding of the biosphere; and the list goes on. (Woese 2005: 99)
All this is an expression of the power inherent in the methodology of molecular biology, especially the sequencing of genomes. Methodology is one thing, however, and understanding and direction another. The fact is that the understanding of biology emerging from the mass of data that flows from the genome sequencing machines brings into question the classical concepts of organism, lineage, and evolution as the same time it gainsays the molecular perspective that spawned the enterprise. The fact is that the molecular perspective, which so successfully guided and shaped twentieth-century biology, has effectively run its course (as all paradigms do) and no longer provides a focus, a vision of the biology of the future, with the result that biology is wandering will-nilly into that future. This is a prescription for revolution–conceptual revolution. One can be confident that the new paradigm will soon emerge to guide biology in this new century…. Molecular biology has ceased to be a genuine paradigm, and it is now only a body of (very powerful) technique…. The time has come to shift biology’s focus from trying to understand organisms solely by dissecting them into their parts to trying to understand the fundamental nature of biological organization, of biological form. (Woese 2005: 99-100)
We should all take seriously an assessment of biology made by the physicist David Bohm over 30 years ago (and universally ignored):
“It does seem odd … that just when physics is … moving away from mechanism, biology and psychology are moving closer to it. If the trend continues … scientists will be regarding living and intelligent beings as mechanical, while they suppose that inanimate matter is to complex and subtle to fit into the limited categories of mechanism.” [D. Bohm, “Some Remarks on the Notion of Order,” in C. H. Waddington, ed., Towards a Theoretical Biology: 2 Sketches. (Edinburgh: Edinburgh Press 1969), p. 18-40.]
The organism is not a machine! Machines are not made of parts that continually turn over and renew; the cell is. A machine is stable because its parts are strongly built and function reliably. The cell is stable for an entirely different reason: It is homeostatic. Perturbed, the cell automatically seeks to reconstitute its inherent pattern. Homeostasis and homeorhesis are basic to all living things, but not machines.
If not a machine, then what is the cell?
— Carl R. Woese (2005, 100) on Evolving Biological Organization
(….) When one has worked one’s entire career within the framework of a powerful paradigm, it is almost impossible to look at that paradigm as anything but the proper, if not the only possible, perspective one can have on (in this case) biology. Yet despite its great accomplishments, molecular biology is far from the “perfect paradigm” most biologists take it to be. This child of reductionist materialism has nearly driven the biology out of biology. Molecular biology’s reductionism is fundamentalist, unwavering, and procrustean. It strips the organism from its environment, shears it of its history (evolution), and shreds it into parts. A sense of the whole, of the whole cell, of the whole multicellular organism, of the biosphere, of the emergent quality of biological organization, all have been lost or sidelined. (Woese 2005: 101)
Our thinking is fettered by classical evolutionary notions as well. The deepest and most subtle of these is the concept of variation and selection. How we view the evolution of cellular design or organization is heavily colored by how we view variation and selection. From Darwin’s day onward, evolutionists have debated the nature of the concept, and particularly whether evolutionary change is gradual, salutatory, or of some other nature. However, another aspect of the concept concerns us here more. In the terms I prefer, it is the nature of the phase (or propensity) space in which evolution operates. Looked at one way, variation and selection are all there is to evolution: The evolutionary phase space is wide open, and all manner of things are possible. From this “anything goes” perspective, a given biological form (pattern) has no meaning outside of itself, and the route by which it arises is one out of an enormous number of possible paths, which makes the evolution completely idiosyncratic and, thus, uninteresting (molecular biology holds this position: the molecular biologist sees evolution as merely a series of meaningless historical accidents). (Woese 2005: 101)
The alternative viewpoint is that the evolutionary propensity space is highly constrained, being more like a mountainous terrain than a wide open prairie: Only certain paths are possible, and they lead to particular (a relatively small set of) outcomes. Generic biological form preexists in the same sense that form in the inanimate world does. It is not the case that “anything goes” in the world of biological evolution. In other words, biological form (pattern) is important: It has meaning beyond itself; a deeper, more general significance. Understanding of biology lies, then, in understanding the evolution and nature of biological form (pattern). Explaining biological form by variation and selection hand-waving argumentation is far from sufficient: The motor does not explain where the car goes. (Woese 2005: 101-102)
This is the age of the evolution of Evolution. All thoughts that the Evolutionist works with, all theories and generalizations, have themselves evolved and are now being evolved. Even were his theory perfected, its first lesson would be that it was itself but a phase of the Evolution of other opinion, no more fixed than a species, no more final than the theory which it displaced.
— Henry Drummond, 1883
Charles Darwin described The Origin of Species as “one long argument” for evolution by natural selection. Subsequently Ernst Mayr applied the expression to the continuing debate over Darwin’s ideas. My explanation of why the debate lingers is that although Darwin was right about the reality of evolution, his causal theory was fundamentally wrong, and its errors have been compounded by neo-Darwinism. In 1985 my book Evolutionary Theory: The Unfinished Synthesis was published. In it I discussed Darwinian problems that have never been solved, and the difficulties suffered historically by holistic approaches to evolutionary theory. The most important of these holistic treatments was “emergent evolution,” which enjoyed a brief moment of popularity about 80 years ago before being eclipsed when natural selection was mathematically formalized by theoretical population geneticists. I saw that the concept of biological emergence could provide a matrix for a reconstructed evolutionary theory that might displace selectionism. At that time, I naively thought that there was a momentum in favor of such a revision, and that there were enough open-minded, structuralistic evolutionists to displace the selectionist paradigm within a decade or so. Faint hope! (Robert G. B. Reid. Biological Emergences: Evolution by Natural Experiment (Vienna Series in Theoretical Biology) (Kindle Locations 31-37). Kindle Edition.)
Instead, the conventional “Modern Synthesis” produced extremer forms of selectionism. Although some theoreticians were dealing effectively with parts of the problem, I decided I should try again, from a more general biological perspective. This book is the result. (Reid 2007, Preface)
The main thrust of the book is an exploration of evolutionary innovation, after a critique of selectionism as a mechanistic explanation of evolution. Yet it is impossible to ignore the fact that the major periods of biological history were dominated by dynamic equilibria where selection theory does apply. But emergentism and selectionism cannot be synthesized within an evolutionary theory. A “biological synthesis” is necessary to contain the history of life. I hope that selectionists who feel that I have defiled their discipline might find some comfort in knowing that their calculations and predictions are relevant for most of the 3.5 billion years that living organisms have inhabited the Earth, and that they forgive me for arguing that those calculations and predictions have little to do with evolution. (Reid 2007, Preface)
Evolution is about change, especially complexifying change, not stasis. There are ways in which novel organisms can emerge with properties that are not only self-sufficient but more than enough to ensure their status as the founders of kingdoms, phyla, or orders. And they have enough generative potential to allow them to diversify into a multiplicity of new families, genera, and species. Some of these innovations are all-or-none saltations. Some of them emerge at thresholds in lines of gradual and continuous evolutionary change. Some of them are largely autonomous, coming from within the organism; some are largely imposed by the environment. Their adaptiveness comes with their generation, and their adaptability may guarantee success regardless of circumstances. Thus, the filtering, sorting, or eliminating functions of natural selection are theoretically redundant. (Reid 2007, Preface)
Therefore, evolutionary theory should focus on the natural, experimental generation of evolutionary changes, and should ask how they lead to greater complexity of living organisms. Such progressive innovations are often sudden, and have new properties arising from new internal and external relationships. They are emergent. In this book I place such evolutionary changes in causal arenas that I liken to a three-ring circus. For the sake of bringing order to many causes, I deal with the rings one at a time, while noting that the performances in each ring interact with each other in crucial ways. One ring contains symbioses and other kinds of biological association. In another, physiology and behavior perform. The third ring contains of developmental or epigenetic evolution. (Reid 2007, Preface)
After exploring the generative causes of evolution, I devote several chapters to subtheories that might arise from them, and consider how they might be integrated into a thesis of emergent evolution. In the last chapter I propose a biological synthesis. (Reid 2007, Preface)
~ ~ ~
Introduction — Re-Invention of Natural Selection
I regard it as unfortunate that the theory of natural selection was first developed as an explanation for evolutionary change. It is much more important as an explanation for the maintenance of adaptation. — George Williams, 1966
Natural selection cannot explain the origin of new variants and adaptations, only their spread. — John Endler, 1986
We could, if we wished, simply replace the term natural selection with dynamic stabilization…. — Brian Goodwin, 1994
Nobody is going to re-invent natural selection…. — Nigel Hawkes, 1997
Ever since Charles Darwin published The Origin of Species, it has been widely believed that natural selection is the primary cause of evolution. However, while George Williams and John Endler take the trouble to distinguish between the causes of variation and what natural selection does with them; the latter is what matters to them. In contrast, Brian Goodwin does not regard natural selection as a major evolutionary force, but as a process that results in stable organisms, populations, and ecosystems. He would prefer to understand how evolutionary novelties are generated, a question that frustrated Darwin for all of his career. (Reid 2007)
During the twentieth century, Darwin’s followers eventually learned how chromosomal recombination and gene mutation could provide variation as fuel for natural selection. They also re-invented Darwinian evolutionary theory as neo-Darwinism by formalizing natural selection mathematically. Then they redefined it as differential survival and reproduction, which entrenched it as the universal cause of evolution. Nigel Hawkes’s remark that natural selection cannot be re-invented demonstrates its continued perception as an incorruptible principle. But is it even a minor cause of evolution? (Reid 2007)
Natural selection supposedly builds order from purely random accidents of nature by preserving the fit and discarding the unfit. On the face of it, that makes more than enough sense to justify its importance. Additionally, it avoids any suggestion that a supernatural creative hand has ever been at work. But it need not be the only mechanistic option. And the current concept of natural selection, which already has a history of re-invention, is not immune to further change. Indeed, if its present interpretation as the fundamental mechanism of evolution were successfully challenged, some of the controversies now swirling around the modern paradigm might be resolved. (Reid 2007)
A Paradigm in Crisis?
Just what is the evolutionary paradigm that might be in crisis? It is sometimes called “the Modern Synthesis.” Fundamentally it comes down to a body of knowledge, interpretation, supposition, and extrapolation, integrated with the belief that natural selection is the all-sufficient cause of evolution—if it is assumed that variation is caused by gene mutations. The paradigm has built a strong relationship between ecology and evolution, and has stimulated a huge amount of research into population biology. It has also been the perennial survivor of crises that have ebbed and flowed in the tide of evolutionary ideas. Yet signs of discord are visible in the strong polarization of those who see the whole organism as a necessary component of evolution and those who want to reduce all of biology to the genes. Since neo-Darwinists are also hypersensitive to creationism, they treat any criticism of the current paradigm as a breach of the scientific worldview that will admit the fundamentalist hordes. Consequently, questions about how selection theory can claim to be the all-sufficient explanation of evolution go unanswered or ignored. Could most gene mutations be neutral, essentially invisible to natural selection, their distribution simply adrift? Did evolution follow a pattern of punctuated equilibrium, with sudden changes separated by long periods of stasis? Were all evolutionary innovations gene-determined? Are they all adaptive? Is complexity built by the accumulation of minor, selectively advantageous mutations? Are variations completely random, or can they be directed in some way? Is the generation of novelty not more important than its subsequent selection? (Reid 2007)
Long before Darwin, hunters, farmers, and naturalists were familiar with the process that he came to call “natural selection.” And they had not always associated it with evolution. It is recognized in the Bible, a Special Creation text. Lamarck had thought that evolution resulted from a universal progressive force of nature, not from natural selection. Organisms responded to adaptational needs demanded by their environments. The concept of adaptation led Lamarck’s rival, Georges Cuvier, to argue the opposite. If existing organisms were already perfectly adapted, change would be detrimental, and evolution impossible. Nevertheless, Cuvier knew that biogeography and the fossil record had been radically altered by natural catastrophes. These Darwin treated as minor aberrations during the long history of Earth. He wanted biological and geographical change to be gradual, so that natural selection would have time to make appropriate improvements. The process of re-inventing the events themselves to fit the putative mechanism of change was now under way. (Reid 2007)
Gradualism had already been brought to the fore when geologists realized that what was first interpreted as the effects of the sudden Biblical flood was instead the result of prolonged glaciation. Therefore, Darwin readily fell in with Charles Lyell’s belief that geological change had been uniformly slow. Now, more than a century later, catastrophism has been resurrected by confirmation of the K-T (Cretaceous-Tertiary) bolide impact that ended the Cretaceous and the dinosaurs. Such disasters are also linked to such putative events as the Cambrian “Big Bang of Biology,” when all of the major animal phyla seem to have appeared almost simultaneously.’ The luck of the draw has returned to evolutionary theory. Being in the right place at the right time during a cataclysm might have been the most important condition of survival and subsequent evolution. (Reid 2007)
Beyond the fringe of Darwinism, there are heretics who believe the neo-Lamarckist tenet that the environment directly shapes the organism in a way that can be passed on from one generation to the next. They argue that changes imposed by the environment, and by the behavior of the organism, are causally prior to natural selection. Nor is neo-Lamarckism the only alternative. Some evolutionary biologists, for example, think that the establishment of unique symbioses between different organisms constituted major evolutionary novelties. Developmental evolutionists are reviewing the concept that evolution was not gradual but saltatory (i.e., advancing in leaps to greater complexity). However, while they emphasize the generation of evolutionary novelty, they accommodate natural selection as the complementary and essential causal mechanism. (Reid 2007)
Notes on isms
Before proceeding further, I want to explain how I arbitrarily, but I hope consistently, use the names that refer to evolutionary movements and their originators. “Darwinian” and “Lamarckian” refer to any idea or interpretation that Darwin and Lamarck originated or strongly adhered to. Darwinism is the paradigm that rose from Darwinian concepts, and Lamarckism is the movement that followed Lamarck. They therefore include ideas that Darwin and Lamarck may not have thought of nor emphasized, but which were inspired by them and consistent with their thinking. Lamarck published La philosophie zoologique in 1809, and Lamarckism lasted for about 80 years until neo-Lamarckism developed. Darwinism occupied the time frame between the publication of The Origin of Species (1859) and the development of neo-Darwinism. The latter came in two waves. The first was led by August Weismann, who was out to purify evolutionary theory of Darwinian vacillation. The second wave, which arose in theoretical population genetics in the 1920s, quantified and redefined the basic tenets of Darwinism. Selectionism is the belief that natural selection is the primary cause of evolution. Its influence permeates the Modern Synthesis, which was originally intended to bring together all aspects of biology that bear upon evolution by natural selection. Niles Eldredge (1995) uses the expression “ultra-Darwinian” to signify an extremist position that makes natural selection an active causal evolutionary force. For grammatical consistency, I prefer “ultra-Darwinist,” which was used in the same sense by Pierre-Paul Grasse in 1973. (Reid 2007)
The Need for a More Comprehensive Theory
I have already hinted that the selectionist paradigm is either insufficient to explain evolution or simply dead wrong. Obviously, I want to find something better. Neo-Darwinists themselves concede that while directional selection can cause adaptational change, most natural selection is not innovative. Instead, it establishes equilibrium by removing extreme forms and preserving the status quo. John Endler, the neo-Darwinist quoted in one of this chapter’s epigraphs, is in good company when he says that novelty has to appear before natural selection can operate on it. But he is silent on how novelty comes into being, and how it affects the internal organization of the organism—questions much closer to the fundamental process of evolution. He is not being evasive; the issue is just irrelevant to the neo-Darwinist thesis. (Reid 2007)
Darwin knew that nature had to produce variations before natural selection could act, so he eventually co-opted Lamarckian mechanisms to make his theory more comprehensive. The problem had been caught by other evolutionists almost as soon as The Origin of Species was first published. Sir Charles Lyell saw it clearly in 1860, before he even became an evolutionist:
If we take the three attributes of the deity of the Hindoo Triad, the Creator, Brahmah, the preserver or sustainer, Vishnu, & the destroyer, Siva, Natural Selection will be a combination of the two last but without the first, or the creative power, we cannot conceive the others having any function.
Consider also the titles of two books: St. George Jackson Mivart’s On the Genesis of Species (1872) and Edward Cope’s Origin of the Fittest (1887). Their play on Darwin’s title emphasized the need for a complementary theory of how new biological phenomena came into being. Soon, William Bateson’s Materials for the Study of Variation Treated with Especial Regard to Discontinuity in the Origin of Species (1894) was to distinguish between the emergent origin of novel variations and the action of natural selection. (Reid 2007)
The present work resumes the perennial quest for explanations of evolutionary genesis and will demonstrate that the stock answer—point mutations and recombinations of the genes, acted upon by natural selection—does not suffice. There are many circumstances under which novelties emerge, and I allocate them to arenas of evolutionary causation that include association (symbiotic, cellular, sexual, and social), functional biology (physiology and behavior), and development and epigenetics. Think of them as three linked circus rings of evolutionary performance, under the “big top” of the environment. Natural selection is the conservative ringmaster who ensures that tried-and-true traditional acts come on time and again. It is the underlying syndrome that imposes dynamic stability—its hypostasis (a word that has the additional and appropriate meaning of “significant constancy”). (Reid 2007)
Selection as Hypostasis
The stasis that natural selection enforces is not unchanging inertia. Rather, it is a state of adaptational and neutral flux that involves alterations in the numerical proportions of particular alleles and types of organism, and even minor extinctions. It does not produce major progressive changes in organismal complexity. Instead, it tends to lead to adaptational specialization. Natural selection may not only thwart progress toward greater complexity, it may result in what Darwin called retrogression, whereby complex and adaptable organisms revert to simplified conditions of specialization. This is common among parasites, but not unique to them. For example, our need for ascorbic acid-vitamin C-results from the regression of a synthesis pathway that was functional in our mammalian ancestors. (Reid 2007)
On the positive side, it may be argued that dynamic stability, at any level of organization, ensures that the foundations from which novelties emerge are solid enough to support them on the rare occasions when they escape its hypostasis. A world devoid of the agents of natural selection might be populated with kludges-gimcrack organisms of the kind that might have been designed by Heath Robinson, Rube Goldberg, or Tim Burton. The enigmatic “bizarre and dream-like” Hallucigenia of the Burgess Shale springs to mind.’ Even so, if physical and embryonic factors constrain some of the extremest forms before they mature and reproduce, the benefits of natural selection are redundant. Novelty that is first and foremost integrative (i.e., allows the organism to operate better as a whole) has a quality that is resistant to the slings and arrows of selective fortune. (Reid 2007)
Natural selection has to do with relative differences in survival and reproduction and the numerical distribution of existent variations that have already evolved. In this form it requires no serious re-invention. But selectionism goes on to infer that natural selection creates complex novelty by saving adaptive features that can be further built upon. Such qualities need no saving by metaphorical forces. Having the fundamental property of persistence that characterizes life, they can look after themselves. As Ludwig von Bertalanffy remarked in 1967, “favored survival of `better’ precursors of life presupposes self-maintaining, complex, open systems which may compete; therefore natural selection cannot account for the origin of those symptoms.” These qualities were in the nature of the organisms that first emerged from non-living origins, and they are prior to any action of natural selection. Compared to them, ecological competitiveness is a trivial consequence. (Reid 2007)
But to many neo-Darwinists the only “real” evolution is just that: adaptation—the selection of random genetic changes that better fit the present environment. Adaptation is appealingly simple, and many good little examples crop up all the time. However, adaptation only reinforces the prevailing circumstances, and represents but a fragment of the big picture of evolution. Too often, genetically fixed adaptation is confused with adaptability—the self-modification of an individual organism that allows responsiveness to internal and external change. The logical burden of selectionism is compounded by the universally popular metaphor of selection pressure, which under some conditions of existence is supposed to force appropriate organismic responses to pop out spontaneously. How can a metaphor, however heuristic, be a biological cause? As a metaphor, it is at best is an inductive guide that must be used with caution. (Reid 2007)
Even although metaphors cannot be causes, their persuasive powers have given natural selection and selection pressure perennial dominance of evolutionary theory. It is hard enough to sideline them, so as to get to generative causes, far less to convince anyone that they are obstructive. Darwin went so far as to make this admission:
In the literal sense of the word, no doubt, natural selection is a false term…. It has been said that I speak of natural selection as an active power or Deity…. Everyone knows what is meant and is implied by such metaphorical expressions; and they are almost necessary for brevity…. With a little familiarity such superficial objections will be forgotten. [Darwin 1872, p. 60.]
Alas, in every subsequent generation of evolutionists, familiarity has bred contempt as well as forgetfulness for such “superficial” objections. (Reid 2007)
Are All Changes Adaptive?
Here is one of my not-so-superficial objections. The persuasiveness of the selection metaphor gets extra clout from its link with the vague but pervasive concept of adaptiveness, which can supposedly be both created and preserved by natural selection. For example, a book review insists that a particular piece of pedagogy be “required reading for non-Darwinist `evolutionists’ who are trying to make sense of the world without the relentless imperatives of natural selection and the adaptive trends it produces.” (Reid 2007)
Adaptiveness, as a quality of life that is “useful,” or competitively advantageous, can always be applied in ways that seem to make sense. Even where adaptiveness seems absent, there is confidence that adequate research will discover it. If equated with integrativeness, adaptiveness is even a necessity of existence. The other day, one of my students said to me: “If it exists, it must have been selected.” This has a pleasing parsimony and finality, just like “If it exists it must have been created.” But it infers that anything that exists must not only be adaptive but also must owe its existence to natural selection. I responded: “It doesn’t follow that selection caused its existence, and it might be truer to say ‘to be selected it must first exist.”‘ A more complete answer would have addressed the meaning of existence, but I avoid ontology during my physiology course office hours. (Reid 2007)
“Adaptive,” unassuming and uncontroversial as it seems, has become a “power word” that resists analysis while enforcing acceptance. Some selectionists compound their logical burden by defining adaptiveness in terms of allelic fitness. But there are sexually attractive features that expose their possessors to predation, and there are “Trojan genes” that increase reproductive success but reduce physiological adaptability. They may be the fittest in terms of their temporarily dominant numbers, but detrimental in terms of ultimate persistence. (Reid 2007)
It is more logical to start with the qualities of evolutionary changes. They may be detrimental or neutral. They may be generally advantageous (because they confer adaptability), or they may be locally advantageous, depending on ecological circumstances. Natural selection is a consequence of advantageous or “adaptive” qualities. Therefore, examination of the origin and nature of adaptive novelty comes closer to the fundamental evolutionary problem. It is, however, legitimate to add that once the novel adaptive feature comes into being, any variant that is more advantageous than other variants survives differentially—if under competition. Most biologists are Darwinists to that extent, but evolutionary novelty is still missing from the causal equation. Thus, with the reservation that some neutral or redundant qualities often persist in Darwin’s “struggle for existence,” selection theory seems to offer a reasonable way to look at what occurs after novelty has been generated—that is, after evolution has happened. (Reid 2007)
“Oh,” cry my student inquisitors, “but the novelty to which you refer would be meaningless if it were not for correlated and necessary novelties that natural selection had already preserved and maintained.” So again I reiterate first principles: Self-sustaining integrity, an ability to reproduce biologically, and hence evolvability were inherent qualities of the first living organisms, and were prior to differential survival and reproduction. They were not, even by the lights of extreme neo-Darwinists, created by natural selection. And their persistence is fundamental to their nature. To call such features adaptive, for the purpose of implying they were caused by natural selection, is sophistry as well as circumlocution. Sadly, many biologists find it persuasive. Ludwig von Bertalanffy (1952) lamented:
Like a Tibetan prayer wheel, Selection Theory murmurs untiringly: ‘everything is useful,’ but as to what actually happened and which lines evolution has actually followed, selection theory says nothing, for the evolution is the product of ‘chance,’ and therein obeys no ‘law. [Bertalanffy 1952, p. 92.]
In The Variation of Animals in Nature (1936), G. C. Robson and O. W. Richards examined all the major known examples of evolution by natural selection, concluding that none were sufficient to account for any significant taxonomic characters. Despite the subsequent political success of ecological genetics, some adherents to the Modern Synthesis are still puzzled by the fact that the defining characteristics of higher taxa seem to be adaptively neutral. For example, adult echinoderms such as sea urchins are radially symmetrical, i.e., they are round-bodied like sea anemones and jellyfish, and lack a head that might point them in a particular direction. This shape would seem to be less adaptive than the bilateral symmetry of most active marine animals, which are elongated and have heads at the front that seem to know where they want to go. Another puzzler: How is the six-leg body plan of insects, which existed before the acquisition of wings, more or less adaptive than that of eight-legged spiders or ten-legged legged lobsters? The distinguished neo-Darwinists Dobzhansky, Ayala, Stebbins, and Valentine (1977) write:
This view is a radical deviation from the theory that evolutionary changes are governed by natural selection. What is involved here is nothing less than one of the major unresolved problems of evolutionary biology. 
The problem exists only for selectionists, and so they happily settle for the first plausible selection pressure that occurs to them. But it could very well be that insect and echinoderm and jellyfish body plans were simply novel complexities that were consistent with organismal integrity—they worked. There is no logical need for an arbiter to judge them adaptive after the fact.
Some innovations result from coincidental interactions between formerly independent systems. Natural selection can take no credit for their origin, their co-existence, or their interaction. And some emergent novelties often involve redundant features that persisted despite the culling hand of nature. Indeed, life depends on redundancy to make evolutionary experiments. Initially selectionism strenuously denies the existence of such events. When faced with the inevitable, it downplays their importance in favor of selective adjustments necessary to make them more viable. Behavior is yet another function that emphasizes the importance of the whole organism, in contrast to whole populations. Consistent changes in behavior alter the impact of the environment on the organism, and affect physiology and development. In other words, the actions of plants or animals determine what are useful adaptations and what are not. This cannot even be conceived from the abstract population gene pools that neo-Darwinists emphasize.
If some evolutionists find it easier to understand the fate of evolutionary novelty through the circumlocution of metaphorical forces, so be it. But when they invent such creative forces to explain the origin of evolutionary change, they do no better than Special Creationists or the proponents of Intelligent Design. Thus, the latter find selectionists an easy target. Neo-Darwinist explanations, being predictive in demographic terms, are certainly “more scientific” than those of the creationists. But if those explanations are irrelevant to the fundamentals of evolution, their scientific predictiveness is of no account.
What we really need to discover is how novelties are generated, how they integrate with what already exists, and how new, more complex whole organisms can be greater than the sums of their parts. Evolutionists who might agree that these are desirable goals are only hindered by cant about the “relentless imperatives of natural selection and the adaptive trends it produces.”
Reduction is a good, logical tool for solving organismal problems by going down to their molecular structure, or to physical properties. But reductionism is a philosophical stance that embraces the belief that physical or chemical explanations are somehow superior to biological ones. Molecular biologists are inclined to reduce the complexity of life to its simplest structures, and there abandon the quest. “Selfish genes” in their “gene pools” are taken to be more important than organisms. To compound the confusion, higher emergent functions such as intelligence and conscious altruism are simplistically defined in such a way as to make them apply to the lower levels. This is reminiscent of William Livant’s (1998) “cure for baldness”: You simply shrink the head to the degree necessary for the remaining hair to cover the entire pate—the brain has to be shrunk as well, of course. This “semantic reductionism” is rife in today’s ultra-Darwinism, a shrunken mindset that regards evolution as no more than the differential reproduction of genes.
Although reducing wholes to their parts can make them more understandable, fascination with the parts makes it too easy to forget that they are only subunits with no functional independence, whether in or out of the organism. It is their interactions with higher levels of organization that are important. Nevertheless, populations of individuals are commonly reduced to gene pools, meaning the totality of genes of the interbreeding organisms. Originating as a mathematical convenience, the gene pool acquired a life of its own, imbued with a higher reality than the organism. Because genes mutated to form different alleles that could be subjected to natural selection, it was the gene pool of the whole population that evolved. This argument was protected by polemic that decried any reference to the whole organism as essentialistic. Then came the notion that genes have a selfish nature. Even later, advances in molecular biology, and propaganda for the human genome project, have allowed the mistaken belief that there must be a gene for everything, and once the genes and their protein products have been identified that’s all we need to know. Instead, the completion of the genome project has clearly informed us that knowing the genes in their entirety tells us little about evolution. Yet biology still inhabits a genocentric universe, and most of its intellectual energy and material resources are sucked in by the black hole of reductionism at its center.
(….) Epigenetic Algorithms
Mechanical metaphors have appealed to many philosophers who sought materialist explanations of life. The definitive work on this subject is T. S. Hall’s Ideas of Life and Matter (1969). Descartes, though a dualist, thought of animal bodies as automata that obeyed mechanical rules. Julien de la Mettrie applied stricter mechanistic principles to humans in LʼHomme machine (1748). Clockwork and heat engine models were popular during the Industrial Revolution. Lamarck proposed hydraulic processes as causes of variation. In the late nineteenth century, the embryologists Wilhelm His and Wilhelm Roux theorized about developmental mechanics. However, as biochemical and then molecular biological information expanded, popular machine models were refuted, but it is not surprising that computers should have filled the gap. Algorithms that systematically provide instructions for a progressive sequence of events seem to be suitable analogues for epigenetic procedures.
A common error in applying this analogy is the belief that the genetic code, or at least the total complement of an organism’s DNA contains the program for its own differential expression. In the computer age it is easy to fall into that metaphysical trap. However, in the computer age we should also know that algorithms are the creations of programmers. As Charles Babbage (1838) and Robert Chambers (1844) tried to tell us, the analogy is more relevant to creationism than evolutionism. At the risk of offending the sophisticates who have indulged me so far, I want to state the problems in the most simple terms. To me, that is a major goal of theoretical biology, rather than the conversion of life to mathematics. (Robert G. B. Reid. Biological Emergences: Evolution by Natural Experiment (Vienna Series in Theoretical Biology) (p. 263). Kindle Edition.)
Many years ago, when I was attending a session at an economics conference, I heard a presentation by a professor about the relationship between economic growth and technology change. In his presentation he purported to show a high correlation between the number of new patients (registered with the US Patent and Trademark Office) and economic growth. This enabled him to conclude that there was a causal relationship between technological change (as reflected by patent counts) and economic growth. This finding, by the way, is the kind that is very often hailed by organizations that offer research grants to economic professors and to other scientists. This is because findings serve as evidence for the “social benefits of R&D” which these organizations can, and often do, use to drum up political support for their organizations. It is also highly appealing to many people—admittedly, myself included—who love science and loving thinking about how beneficial scientific and technological advancement can be when it is properly and responsibly managed. So I realized that the paper being presented would be music to many people’s ears, and that it would help him receive praise, perhaps a publication, and perhaps even grant money, for his research. (Payson 2017, 3)
Given my own background on the topic … I had a question about his stated findings, which I politely asked during the question-and-answer session. In asking my question I mentioned that I was familiar with a well-known change in patent laws that occurred at the beginning of the time span that he was analyzing. As many who are familiar with patents know, the vast majority of patents that are issued have no real value and are not in fact used by the company that holds the patent. What generally occurs is that a company acquires a very valuable patent and also createes dozens of other patents that are “close” (in their subject matter) to that valuable one. The reason for their doing this is to protect their valuable patent so that no company can produce a similar patent that competes with theirs. The change in patent laws, which I just referred to, had made it easier for companies to acquire similar patents to ones that already existed, which essentially created a need for companies issuing important patents to “surround” their main patent by more of these other unused “protective patents.” (Payson 2017, 3)
So, in my question to the presenter, I asked whether it might simply be possible that the increase in registered patents that his study observed was attributable to that change in patent laws, which was apparently occurring at the same time that GDP was growing fairly well. GDP was growing at that time due to a general upturn in the economy in which employment was on the rise and inflaction had been brought under control. In other words, perhaps it was simpl a coincidental that both patent counts and real GDP were rising during the same period, but there was no causal relationship between the two. I asked him, essentially, if he thought that such a coincidence might be an alternative explanation for why patents and GDP were rising at the same time. (Payson 2017, 3-4)
The presenter’s reaction, especially in terms of his facial expression, reflected a typical response that I must have seen hundreds of times in my 35 years as an economist. Upon hearing my question he condescendingly smiled from ear-to-ear, while constraining himself from laughing, and he replied in an artificially diplomatic and sarcastic tone, “Oh I know all that [about the patent law change.] But … that’s not my story“—the story that he wanted to tell—and he was thoroughly amused that someone in the audience would be naïve enough to actually think about whether his findings were scientifically valid. Scientific validity of one’s findings is not only rarely discussed during paper presentations at economics conferences, but when it is, it is, more often than not, a source of amusement by the presenters of the papers and their audiences than an actual concern that might lead to improving people’s work. (Payson 2017, 4)
The Profession’s Genuine Arrogance toward Concerns about Scientific Integrity
(….) [M]any academic economists respond with smug, arrogant dismissial or laughter when the topic of scientific integrity or professional ethics is brought before them. It might be surprising to those who are less familiar with the profession that such arrogance and frivolity is as observable as much among some of the most prominent economics professors as among those who are not prominent. In the documentary Inside Job, one can observe this kind of arrogance directly among high-ranking professors as they were being interviewed. (Payson 2017, 4)
As another example, Deirdre McCloskey, a former member of the board of directors of the American Economic Association (AEA) (which consists only of highly ranked professors), has told of how she was there when the board broke into laughter when a letter was read aloud at one of their meetings. The letter was someone who was simply asking whether the AEA would consider adopting a code of ethics for economists. (Payson 2017, 4)
Many economics professors do not laugh or make arrogant statements, but express conceit in an entirely different way, such as feeling sorry for those who are even thinking about scientific integrity or professional ethics—thinking to themselves how pathetically stupid, naïve, or childishly innocent those people must be. There is, in fact a substantial literature on the more scholarly problem of arrogance in the academic economics profession. This literature was written entirely by “insiders”—highly prominent professors themselves, some even Nobel laureates. (Payson 2017, 4-5)
(….) In the absence of the commitment to contributing to useful knowledge, the behavior of the work of academic economists have been dominated by two other major forces: (1) the mathematical games that are played for the sake of getting published and acquiring grant money, and (2) cronyism within the profession, which, in combination with the mathematical game playing, has dominated the reward system and incentive system of the profession. (Payson 2017, 10)
[T]o examine the validity of the claim that these are highly useful branches of knowledge [e.g., economics], let us ask what their contribution to mankind’s welfare is supposed to be. To judge by the cues from training courses and textbooks, the practical usefulness … consists of helping people to find their niche in society, to adapt themselves to it painlessly, and to dwell therein contentedly and in harmony with their companions. (Andreski 1973, 26, in Social Sciences as Sorcery)
Literature-Only Discourse and the Pretense of Scientific Merit
Regardless of all the various arguments made against most theoretical economics, “defenders of the faith” will continue to espouse the party line. That is, they will say that, regardless of the bad and unproductive habits of theoretical economics, good things—namely, genuine and extremely valuable discoveries in economic theory—do fall out of the chaos. They will continue to argue that these valuable discoveries, even though they may be rare, ultimately justify the chaos and the inefficiencies of the system. To get past this convenient, blind faith, I will argue that it is possible for us to identify what characteristics of most top-ranked, theoretical literature actually do prevent it from contributing to valuable knowledge. In this way, we may be able to filter it out from this point on, without removing any of the top-ranked literature that is truly valuable. (Payson 2017, 51)
Defining the Filter
Let us consider a subset of all published papers in economics that meet all of the following three criteria. If it meets any one of the criteria, the paper may still be considered as an acceptable contribution to useful knowledge. (Payson 2017, 51)
Criterion 1: The paper uses a model that has no “real application.” Along these lines, if the paper presents a model for the purpose of being persuasive on a particular policy position, but presents no real evidence in support of that position (and is only a model that essentially “rediscovers its assumptions”) then it would still meet this criterion of having no real application. (Payson 2017, 51)
Criterion 2: The paper relies on assumptions or data that cannot be verified, or the situation exists in which alternative assumptions or data can be reasonably found that would yield entirely different, conflicting results (as in the McCloskey’s A-Prime, C-Prime Theorem). (Payson 2017, 51-52)
Criterion 3: The methodology of the paper would only be understood, valued, and genuinely studied by a very small group of other economists with advanced expertise in that highly specific topic. (Payson 2017, 52)
Let us call a paper that meets all of these criteria a “literature-only paper”—its purpose is only for the career advancement of the author and for the production of literature to be read and actually understood by a very small audience. Similarly, let us call the work done by economists to produce literature-only papers “literature-only work” or “literature-only discourse.” To be clear, this chapter does not discuss top-ranked literature in general—only literature-only papers that meet all (every one) of the above-mentioned criteria. (Payson 2017, 52)
(….) The only thing that truly constitutes “scientific merit”—indeed, the only thing that really matters in science—is an honest and successful effort to learn how the world actually works—not an effort to create impressive systems of mathematical equations that only very smart and very educated people can proudly decipher. Many graduate students in economics, especially those with little interest or experience in natural science, are ignorant of this. They then go on to become economics professors where they remain ignorant, and pass on their ignorance to their graduate students, the cycle repeats with each generation. (Payson 2017, 52)
In response to this accusation, many theoretical economists will argue that, from looking at the work itself, we have no basis for distinguishing between valid, scientific economic theory, and invalid, unscientific economic theory. Nevertheless, I would like to propose a very simple test could enable us to make this distinction: We look at the assumptions made in the analysis, and ask, “Can an alternative set of equally defensible assumptions be made that will lead to very different conclusions?” If the answer is “Yes,” then conclusions of the research in question have no degree of certainty—implying that the research has not contributed to our understanding of how the real world works. If those conclusions are then used to provide a false understanding of how the real world works, then this is simply a deception, which may be harmful in various respects. (Payson 2017, 52-53)
Let us call economic theory that falls under this category “unscientific economic theory” to bring home the point that science plays no role in justifying the existence of such self-serving conceptual games…. So why has the problem not been solved? The answer is that this solution or anything like it, cannot be heard by unscientific theoretical economists—it falls on deaf ears. (Payson 2017, 53)
Selling New Terminology and Supposedly New Concepts
(….) In many cases new terminology is offered in literature-only discourse as the basis for a new theoretical model that appears to capture an important concept. In general, the important concept is already known and understood under different names. Nevertheless, when a prominent theoretical economist presents a new term that they promote as a “new concept,” and at the same time present a very elaborate and sophisticated model to supposedly “explain” the concept in mathematical terms, it may appear, especially to naïve observers, that their research has truly discovered something important. Many may have trouble distinguishing in their own minds the value of the new terminology from the value of the arbitrary assumptions that were used to create a sophisticated model to explain it. (Payson 2017, 60)