Home > Uncategorized > Weekend read – Essentialism and traditionalism in academic research

Weekend read – Essentialism and traditionalism in academic research

from Ryan Kyger1and Blair Fix

Philosophy of science is about as useful to scientists as ornithology is to birds.

— attributed to Richard Feynman2

Most scientists don’t worry much about philosophy; they just get on with doing ‘science’. They run experiments, analyze data, and report results. And by so doing, they fall repeatedly into known philosophical pitfalls.

This essay is about two such pitfalls: essentialism and traditionalism.

‘Essentialism’ is the view that behind real-world objects lie ‘essences’ — a type of eternal category that you cannot observe directly but is nonetheless there. Racial categories are a common type of ‘essence’. To be racist is to attribute to different groups universal qualities that define them as people.3

Given the long history of racism, it’s clear that humans need little impetus to impose categories onto the world. Still, our instinct to categorize is not always bad. In fact, it’s a key part of science. Looking for patterns is how Dmitri Mendeleev created the periodic table. It’s how John Snow discovered that cholera was water-borne. And it’s how Johannes Kepler discovered the laws of planetary motion.

So if categorizing patterns can be helpful, what makes essentialism bad? To be essentialist, in our view, is to reify a category (or theory) into a ‘higher truth’. By so doing, you don’t use evidence to inform a theory. You use theory to interpret evidence … and you don’t consider that you could be wrong.

Like most human activities, ‘essentialism’ is a social affair. Yes, you can do it by yourself, but you’ll be called a ‘crank’. To be essentialist with prestige, you must be part of a tradition. You must think x because your teacher thought x. And because your teacher was prestigious, so are you. When we combine essentialism with traditionalism, we get a powerful recipe for killing science. We interpret the world through our preferred lens, and then reward ourselves for doing it.

In this essay, we’ll look at examples of essentialism and traditionalism in economics, biology, and statistics. But we’ll start with some Greek philosophy.

Plato’s spell

Plato of Athens was perhaps the first scholar to combine essentialism and traditionalism. Unsurprisingly, his goal was political.

Plato was born during the Athenian experiment with democracy — a period marked by turmoil, war, and famine. Perhaps because of this instability (and also because his family claimed royal blood), Plato disliked democracy. Instead, he was staunchly in favor of traditional hierarchical rule:

The greatest principle of all is that nobody … should be without a leader. … [Man] should teach his soul, by long habit, never to dream of acting independently, and to become utterly incapable of it.

— Plato of Athens, quoted by Karl Popper [3]

Given his reactionary politics, Plato was disturbed by the events that surrounded him. During his life, the aristocratic order was in flux. And so Plato searched for something constant on which to cling. He found this constant in his philosophy. Social change, Plato would theorize, was like entropy. Change was never progressive, but was instead an incessant force for corruption, decay and degeneration. Or at least, that’s Karl Popper’s reading of Plato.

In his book The Open Society and its Enemies, Popper lambastes Plato for both his politics and his philosophy [3]. As Popper sees it, Plato resolved his angst about social change by imposing onto the messy real world a higher plane of eternal truth. Plato called this higher plane the ‘Forms’ — a hidden realm in which real-world objects have a perfect and unchanging representation. Behind every real-world triangle, for instance, is the perfect ‘form’ of a triangle.

When applied to mathematics, this idea seems reasonable. An ideal triangle, we all know, is a three-sided shape whose internal angles sum to 180°. Although no real-world triangle has this property exactly, we can imagine one that does. This, Plato would say, is the ‘essence’ of a triangle.

Actually, it’s the definition. You see, in mathematics, we start with a definition and explore the consequences. An example: Euclid postulated that parallel lines never intersect. From this (and other definitions), he derived the rules of Euclidean geometry. From a definition came consequences. If you think like Plato, you’d say that Euclid discovered a higher plane of truth. But that’s a scientific fallacy. The problem is that there’s no guarantee that definitions (and their consequences) have anything to do with the real world.

Case in point: on the curved surface of the Earth, Euclidean geometry is flat out wrong (pun intended). On Earth, parallel lines can intersect (lines of longitude), which means that Euclid’s ‘higher plane of truth’ is invalid. Draw a triangle big enough and you’ll find that the angles sum to more than 180°.

Back to Plato. Karl Popper was unimpressed by Plato’s essentialism because he realized that it was a recipe for pseudoscience. According to Plato, ‘essences’ were accessible only through ‘intuition’. Popper ridiculed this idea, but was not the first to do so. Plato’s spell was broken during the Enlightenment when thinkers like John Locke, David Hume, and Immanuel Kant highlighted the importance of empirical knowledge [46]. To do science, they argued, you cannot simply impose ideas and definitions onto the world. Instead, you must use real-world observations to hold ideas in check.4

Of course, like essences, scientific models are idealizations of the real world. The key difference, though, is the attitude surrounding the idea. When science is done well, hypotheses are treated as provisional and incomplete. When new evidence comes along, a good scientist must remain open to revising or discarding their model. With Plato’s essences, it is the reverse. The essence is eternally true … the unquestionable insight of a great mind. Evidence is to be interpreted in light of the insight, never the reverse.

‘Essentialism’, as we see it, is the reification of a theory — a transformation from ‘provisional explanation’ to ‘timeless truth’. The change rarely happens overnight, but is instead reinforced by repetition. Over time, scientists tend to fall in love with their theories, buttressing them from contradictory evidence. Eventually a pet theory becomes a school of thought, passed down from teacher to student. If the tradition becomes ubiquitous, the theory becomes a ‘timeless truth’. Or so it appears to those under the spell.

In this essay, we look at three academic disciplines that are (at least in part) under the spell of essentialism and traditionalism. Obsessed with the idealized free market, the discipline of economics is the worst offender. But it is not the only one. Population biologists often interpret the world through the lens of an equilibrium model that bares little resemblance to reality. And in their haste for ‘rigor’, statisticians have enshrined subjective beliefs as received wisdom.

What unifies these practices, we argue, is the merger of essentialism and traditionalism. It is a potent combination for creating and perpetuating an ideology.

Essentialism and traditionalism in economics

Mainstream economics makes so many false claims that we could write a book debunking them. (Which is why Steve Keen did just that [7].) Although economics presents itself as a hard science, under the hood it is essentialist dogma, held in place by tradition.

Take, as an example, economists’ appeal to ‘naturalness’. According to neoclassical economics, there is a ‘natural’ rate of unemployment, and there are ‘natural’ monopolies. Even the distribution of income is supposedly ‘controlled by a natural law’ [8].

Now there is nothing wrong with appealing to natural law. Indeed, scientists do it all the time. But outside economics, the term has an unambiguous meaning: a ‘natural law’ is an empirical regularity with no known exception. The laws of thermodynamics are a prime example. Left alone, objects ‘naturally’ converge to thermodynamic equilibrium. Leave a hot coffee on the table and it will soon cool to room temperature. The outcome is the same today as it was yesterday. It is the same for you as it is for me. It is a ‘natural law’.

By documenting and explaining this empirical regularity, we are following the recipe laid out by Locke, Hume, and Kant. Observe the real world and try to explain consistent patterns. When economists appeal to ‘natural law’, however, they are doing something different. Take the so-called ‘natural’ rate of unemployment. If this rate were like the laws of thermodynamics, unemployment would gravitate towards a single value. Try as you might, it would be impossible to change unemployment from this ‘natural’ rate.

Needless to say, unemployment does not work this way. Instead, it fluctuates greatly, both in the short term, and over the long term. So when economists refer to the ‘natural’ rate of unemployment, they don’t mean an empirical regularity. They mean an essence. As Milton Friedman defined it, the ‘natural’ rate of unemployment is that which is “consistent with equilibrium in the structure of real wages” [9]. So whenever (and wherever) the labor market is in ‘equilibrium’, unemployment is at its ‘natural’ rate.

So how do you tell when the market is in ‘equilibrium’? Good question … nobody knows. That’s because market ‘equilibrium’ is not something economists observe. It is something economists imagine and then project onto the world. It is an essence.

To convince yourself that this true, pick any economics textbook and search for the part where the authors measure market ‘equilibrium’. Find the section where they construct the ‘laws’ of supply and demand from empirical observations. Look for where they measure demand curves, supply curves, marginal utility curves, and marginal cost curves. Seriously, look for these measurements. You will not find them.5

You won’t find them because they are unobservable. These concepts are essences. The equilibrium-seeking free market is an idea that economists project onto the world, and then use to interpret events. Anything that fits the vision is ‘proof’ of the essence. Anything that seems contradictory is dismissed as a ‘distortion’.

And that brings us to economics education. The core content in Econ 101 has changed little over the last half century (if not longer). And that’s not because the ‘knowledge’ is secure. It’s because the content of Econ 101 is a tradition. The point of Econ 101 is to indoctrinate the next generation in the ‘essence’ of economics. This powerful combination of essentialism and traditionalism has made economics a “highly paid pseudoscience” [10].

Essentialism and traditionalism in population biology

Compared to economics, the foundations of evolutionary biology are on sound footing. Still, we feel that elements of biology appeal to essentialism. We’ll use population biology as an example.

Population biologists study gene frequency (or more properly, genotype frequency) within a group of organisms. Among humans, for instance, most people have brown(ish) eyes, while about 10% of people have blue eyes. The goal of population biology is to explain this proportion and to understand how and why it changes with time.

The foundational hypothesis in evolutionary biology is that organisms evolve. Curiously, then, many population biologists use a model of genotype frequency that excludes evolution. The model, known as the Hardy-Weinberg principle, outlines the conditions where the genotype frequency of a population will stay in equilibrium, thus the population is said to be in ‘genetic equilibrium’. To satisfy the model, a population must reproduce sexually, be infinitely large, mate randomly, produce the same number of offspring per parent, not mutate, not migrate, and not be subject to natural selection [11,12]. In other words, the modeled population must look nothing like what we find in the real world.6

Now, this unreality is not necessarily a problem if we are clear that we are doing a mathematical thought experiment. The problem, though, is that population biologists often use the Hardy-Weinberg model to interpret reality. They’ll run statistical tests to see if the Hardy-Weinberg model provides a ‘good fit’ to empirical data. If it does, they conclude that the population is in genetic equilibrium.

Can you spot the problem? Like the equilibrium seeking market, the Hardy-Weinberg principle is an ‘essence’. You cannot directly observe that a population is in genetic equilibrium any more than you can observe that a market is in equilibrium. And like the neoclassical model of the market, the assumptions behind the Hardy-Weinberg principle are systematically violated in the real world. So on the face of it, the model ought never be used.

Here, though, population biologists take a cue from economist Milton Friedman. In his essay ‘The Methodology of Positive Economics’, Friedman argues that you cannot test a theory by comparing its assumptions to reality [13]. Instead, you must judge the assumptions by the predictions they give. If the predictions are sound, says Friedman, so too are the assumptions. (For why this is a bad idea, see George Blackford’s essay ‘On the Pseudo-Scientific Nature of Friedman’s as if Methodology’ [14].)

Here’s how population biologists apply the Friedman trick. They take a model whose assumptions are known to be false in the real world and subject it to a statistical test. They obtain one of two possible results. If the test yields a value that is below a specified threshold, a population is said to be in ‘genetic equilibrium’. Conversely, if the test yields a value above a certain threshold, then a population is said to be in ‘genetic disequilibrium’. Population biologists believe either outcome to be reasonable. But this belief ignores the false assumptions of the model, and results in a failure to reject the model itself.

To reduce this reasoning to its most absurd, imagine a hypothesis that claims: ‘if average human height is greater than 0, height is in disequilibrium’. Now, suppose we employ a ‘special procedure’ to test this hypothesis. The procedure yields two possible results:

  1. Null result: the average human height is equal to 0. Conclusion: height is in equilibrium.
  2. Alternative result: the average human height is greater than 0. Conclusion: height is in disequilibrium.

With either result, we ‘demonstrate’ something about human height. Or rather, by applying a model that we know to be false, we fool ourselves into thinking so.

Like economists’ faith in the equilibrium-seeking free market, many population biologists have come to treat the Hardy-Weinberg principle as an essential truth. This belief then gets passed to from teacher to student as a matter of ‘tradition’. Why use the model? Because your prestigious teacher did.

To be fair to population biologists, the appeal to tradition has never been as great as in economics. And today, a growing number of biologists use non-equilibrium models that do not depend on any of the Hardy-Weinberg assumptions [15]. That said, the enduring appeal of the Hardy-Weinberg model speaks to the ideological potency of essentialism and traditionalism.

Essentialism and traditionalism in statistics

There is an old saying that mathematics brought rigor to economics, but also mortis.7 We might say the same thing of statistics.

Now, on the face of it, this accusation seems unfair, since statistics is mathematics. But the fact is that statistics was developed as mathematical tool for scientists — a tool to help judge a hypothesis. Above all else, scientists want to know if their hypothesis is ‘correct’. The problem, though, is that making this judgment is inherently subjective. The evidence for (or against) a hypothesis is always contingent and incomplete. And so scientists must make a judgment call.

The purpose of statistics is to put numbers to this judgment call by quantifying uncertainty. It’s a useful exercise, but not one that removes subjectivity. Suppose that I find there is a 90% probability that a hypothesis is correct. I still need to make a judgment call about how to proceed. In other words, statistics can aid decisions, but cannot make them for us.

Unfortunately, in many corners of science, statistical tools have become reified as the thing they were never designed to be: a decision-making algorithm. Scientists apply the tools of (standard) statistics as though they were an essential truth, a ritualistic algorithm for judging a hypothesis.

Let’s have a look at the ritual. Suppose we have a coin, and we want to know if it is ‘balanced’, meaning the ‘innate’ probability of heads or tails is 50:50. We’ve put scare quotes around the word ‘innate’ here because it is an ‘essence’. You cannot observe the probability of heads or tails for a single toss. It is a mathematical abstraction that is forever beyond our grasp. In the real world, all that we can see is the long-run behavior of the coin.

In standard (‘frequentist’) statistics, we assume that the long-run frequency of the coin gives insight into its ‘innate’ probability of heads or tails. Here’s how the algorithm works. First, assume that the coin is ‘balanced’. Second, calculate the probability that a balanced coin would give the observed frequency (or greater) of heads. Third, choose a ‘critical value’ below which you reject your hypothesis that the coin is balanced.

If you’ve every taken an introductory stats course, you know this algorithm by heart. Now here’s the problem. The algorithm seems to remove the subjective element to evaluating a hypothesis. And yet it does not. Notice that after we compute our statistic (the p-value), we are still left with uncertainty. Suppose, for instance, that we tossed a coin several thousand times and got slightly more heads than tails. Suppose that the probability of a balanced coin giving this proportion of heads (or greater) is about 1 in 100. Given this information, we must still decide between two scenarios:

  1. The coin is balanced, but we have witnessed an improbable outcome.
  2. The coin is unbalanced, and we have witnessed a probable outcome.

The choice is a subjective one. To be fair, most statisticians will admit as much, noting that the choice for a ‘critical threshold’ (below which we reject the null hypothesis) is arbitrary. They will also admit that in many real-world scenarios, the assumptions behind the calculation of p-values are violated, meaning the value is meaningless.

Unfortunately, when null-hypothesis tests get applied by scientists (especially social scientists) these problems are forgotten. Instead, scientists appeal to tradition. Never mind that the threshold for ‘statistical significance’ is arbitrary. The traditional value is 5%. If your p-value is less than this magic value, your results are ‘significant’.

With this tradition in hand, we get a seemingly objective procedure for discovering the ‘truth’. But in reality, it is an essence — a series of “ad hoc algorithms that maintain the facade of scientific objectivity” [17]. These algorithms have had a devastating effect on science, since they basically give a recipe for how to get a ‘significant’ result:

  1. Play with your data until you get a p-value less than 5%.
  2. Publish.
  3. Get cited.
  4. Get tenure.
  5. (Never check if your results are valid.)

Fortunately, there is a growing movement to reform hypothesis testing. One option is to pre-register experiments to remove researchers’ ability to game statistics. Another option is to lower the ‘traditional’ level of statistical significance.

While we welcome both changes, we note that they do not solve the fundamental problem, which is that judging a hypothesis is always subjective. For that reason, we favor a transition to Bayesian statistics. We won’t dive into the details here, but in short, Bayesian statistics is up front about the subjective element of judging a hypothesis. In fact, when you use the Bayesian method, this subjectivity gets baked into the calculations (in what Bayesian’s call a ‘prior probability’).

Despite what we see as the clear advantages of Bayesian statistics, most students are still taught the ‘frequentist’ approach. Why? Because that is the tradition, which is taught as an essential truth.

Totems of Essentialism

In his satirical essay ‘Life Among the Econ’, Axel Leijonhufvud describes economics as if it were a ‘primitive’ society. The ‘Econ’, he observes, are a curious tribe with odd rituals and mysterious ‘totems’ to which they worship. The most important ‘totem’ consists of “two carved sticks joined together in the middle somewhat in the form of a pair of scissors” [18]. Leijonhufvud is, of course, describing the intersecting supply and demand curves with ‘market equilibrium’ at their center.

We think that describing this model as a ‘totem’ is appropriate. The totem is not meant to describe reality. It is meant to define it. The ‘Econ’ do not test the totem of the equilibrium-seeking free market. They use it as a ritual to justify social behavior. When ‘reality’ gets in the way, Leijonhufvud observes, one of two things may happen:

Either he [an Econ] will accuse the member performing the ceremony of having failed to follow ritual in some detail or other, or else defend the man’s claim that the gold is there by arguing that the digging for it has not gone deep enough.

— Axel Leijonhufvud [18]

In other words, the totem is ‘true’, the evidence be damned.

While the economic model of the free market is the most brazen totem, there are many others in modern science — models that have been elevated to a ‘higher truth’. We’ve highlighted two such models here: the Hardy-Weinberg model of genetic equilibrium, and the frequentist method of statistical hypothesis testing.

Curiously, these three totems have a similar appearance, as show below. All three are pleasingly symmetric, drawing the eye to the center.

Figure 1: Essentialist totems in economics, biology and statistics. Clockwise from top left: the neoclassical model of the equilibrium-seeking market, the Hardy-Weinberg model of genetic equilibrium, and the normal distribution — the ‘equilibrium’ behavior of infinitely many random samples.

On the face of it, this resemblance is odd, since the three models deal with unrelated topics. To the Platonist, it may seem that scientist have unearthed an ‘essential form’ to reality. What seems more likely to us, however, is that we have unearthed an aesthetic preference.

Many scientists believe that a good theory ought to be ‘beautiful’. But why should the laws of nature respect human aesthetics? If they always did, it would be astonishing. But as physicist Sabine Hossenfelder shows in her book Lost in Math, the appeal to aesthetics leads scientists astray more often than it leads them to the truth [19].

Appealing to aesthetics, then, is a bad way to do science. But it is a great way to ingrain an idea in the human psyche. Each year, millions of students are shown the central totem of economics — “two carved sticks joined together in the middle somewhat in the form of a pair of scissors”. The totem is pleasingly simple and symmetric — so much so that few students will ever forget it.

And that is the point.

Never mind that the totem of the equilibrium-seeking free market has no contact with reality. What matters is that the totem be memorable … easily imprinted on the psyche, easily imposed onto the world, and easily passed down to the next generation: an eternal truth to be promulgated without question.

When it comes to essentialist totems, economics is the low-hanging fruit. But as we’ve tried to demonstrate, essentialism and traditionalism thrive elsewhere in science. It is an old problem that cuts to the core of how humans think. As Plato’s enduring spell shows, all too often we find ideas more seductive than facts.


[Cover image: Raphael’s depiction of Plato, surrounded by a Lissajous curve.]

  1. Ryan Kyger is an independent researcher who cares deeply about the integrity of scientific research.↩
  2. Like so many famous quotes, there’s no evidence that Richard Feynman uttered these words. In 1991, Willis Harman attributed the ornithology phrase to an anonymous scientist. But the sentiment seems to have been borrowed from an earlier (1974) remark about aesthetics:

    … aesthetics is to artists what ornithology is to birds.


  3. On the link between essentialism and racism Laurie Wastell writes:

    Sadly, millions of years of evolution have made humans very good at being tribal; we have an in-group and an out-group, and we are all too adept at convincing ourselves that the out-group is inherently evil, dangerous or other. Essentialist thinking facilitates this hugely because it encourages us to see people as representing an abstract idea associated with their group rather than as an individual human …

    On that front, researchers have found that essentialist attitudes about race correlate strongly with explicit prejudice [1,2]. Our guess is that essentialism goes beyond explicit racism, and is actually a key part of all hierarchical class systems. When one class rules another, the ruling class is inevitably endowed with an imaginary set of superior traits. And the lower class is endowed with an imaginary set of inferior traits.↩

  4. Summarizing this Enlightenment skepticism of ‘pure reason’, Karl Popper writes:

    … pure speculation or reason, whenever it ventures into a field in which it cannot possibly be checked by experience, is liable to get involved in contradictions or ‘antinomies’ and to produce what [Kant] unambiguously described as ‘mere fancies’; ‘nonsense’; ‘illusions’; ‘a sterile dogmatism’; and ‘a superficial pretension to the knowledge of everything’. [3]


  5. For an accessible introduction to the problems with the neoclassical theory of free markets, we recommend Jonathan Nitzan’s video Neoclassical Political Economy: Skating on Thin Ice.↩
  6. It’s worth noting the question that led to the Hardy-Weinberg model. Simple intuition suggests that dominant alleles (like those for brown eyes) should drive to extinction recessive alleles (like those for blue eyes). If this intuition is correct, recessive alleles should never persist in a population. And yet in the real world they do. Why? The Hardy-Weinberg model demonstrates that under certain circumstances, your intuition is incorrect: recessive alleles can persist indefinitely.↩
  7. The rigor-mortis quotation is attributed, at various times, to both the ecological economist Kenneth Boulding and to the economic historian Robert Heilbroner. We can find no written record for Boulding’s statement. Heilbroner, on the other hand, said the following in 1979: “the prestige accorded to mathematics in economics has given it rigor, but, alas, also mortis” [16].↩


[1] Mandalaywala TM, Amodio DM, Rhodes M. Essentialism promotes racial prejudice by increasing endorsement of social hierarchies. Social Psychological and Personality Science 2018; 9: 461–9.

[2] Chen JM, Ratliff KA. Psychological essentialism predicts intergroup bias. Social Cognition 2018; 36: 301–23.

[3] Popper KR. The open society and its enemies. vol. 119. Princeton University Press; 2020.

[4] Locke J. An essay concerning human understanding. Kay & Troutman; 1847.

[5] Hume D. An enquiry concerning human understanding. Routledge; 2016.

[6] Kant I. Critique of pure reason. 1781. Modern Classical Philosophers, Cambridge, MA: Houghton Mifflin 1908: 370–456.

[7] Keen S. Debunking economics: The naked emperor of the social sciences. New York: Zed Books; 2001.

[8] Clark JB. The distribution of wealth. New York: Macmillan; 1899.

[9] Friedman M. The role of monetary policy. In:. Essential readings in economics, Springer; 1995, pp. 215–31.

[10] Levinovitz AJ. The new astrology. Aeon Magazine 2016.

[11] Edwards A. GH hardy (1908) and Hardy–Weinberg equilibrium. Genetics 2008; 179: 1143–50.

[12] Abramovs N, Brass A, Tassabehji M. Hardy-weinberg equilibrium in the large scale genomic sequencing era. Frontiers in Genetics 2020; 11: 210.

[13] Friedman M. Essays in positive economics. Chicago: University of Chicago Press; 1953.

[14] Blackford G. On the pseudo-scientific nature of friedman’s as if methodology. Availible at: Http://Www Rweconomicscom/BPA 2016.

[15] Brandvain Y, Wright SI. The limits of natural selection in a nonequilibrium world. Trends in Genetics 2016; 32: 201–10.

[16] Heilbroner RL. Modern economics as a chapter in the history of economic thought. History of Political Economy 1979; 11: 192–8.

[17] Diamond GA, Kaul S. Prior convictions: Bayesian approaches to the analysis and interpretation of clinical megatrials. Journal of the American College of Cardiology 2004; 43: 1929–39.

[18] Leijonhufvud A. Life among the econ. Economic Inquiry 1973; 11: 327–37.

[19] Hossenfelder S. Lost in math: How beauty leads physics astray. Hachette UK; 2018.

  1. Ikonoclast
    July 2, 2021 at 11:25 pm

    Excellent essay! This is a vital arena of thought. If people will indulge me, I will post a section from a text I am writing. Plato gets a mention re essentialism. I also write about models and their necessary incompleteness. A proof is developed that models must always be incomplete albeit the proof depends an the a priori assumption that the cosmos is “priority monist” in nature: meaning that the whole precedes the parts. However, this assumption (of priority monism) needs to be elaborated upon by our theories, and observations of the evolution and emergence.

    A priori assumptions are unavoidable in philosophy and hence in the philosophy of science. We need to be aware of our a priori assumptions and how they condition our conclusions. Most pseduo-science is done when a priori assumptions are deliberately hidden or worse when they are completely unconscious to the theorist himself or herself.

    Chapter 1

    Section 1.5 – The Incompleteness of Science

    It must be conceded that, despite the great progress in physics, a mathematical unification of general relativity (GR) and quantum field theory (QFT) has not been achieved to date. Such a unification might yet be developed or it might be precluded due to some ultimate limitation of human intelligence, or of mathematics (mathematical modelling) or of the development of technically feasible instruments. All modelling, including mathematical modelling, involves the process of abstracting essential elements from reality and making simplifying assumptions. A working model, including a mathematical system as a working model (which links the quantities involved in static or dynamic occurrences into abstractly modeled relationships via equations), can function as a set of general and linking explanations or as a set of specific pathways and algorithms for the calculation/prediction of real processes occurred, occurring or yet to occur.

    The incompleteness of science is very likely to prove intractable. Indeed, a proper consideration of Complex System Monism, as a form of historical or priority monism, demonstrates that mathematical and scientific incompleteness will be intrinsic and unavoidable, if the initial thesis of priority monism (of the cosmos) is correct. Under an assumption of thorough-going priority system monism, an explanation or model of reality, as a set of language statements or mathematical equations, can never be complete. In addition to being abstracted and simplified, an explanation or model of reality (of “all existence”) or of a sub-system thereof, must itself (the model that is) perforce be a smaller sub-set system (an emergent subset generated and mediated by a conscious human agent) of monistic reality itself (“all-existence”). In emergence, the new formal statement adds a “radical novelty” to all-existence (the cosmos). All-existence now has a new theory about itself which theory is a new, emerged part of all-existence. The explanation or model cannot have any existence separate and unconnected from the posited monistic system otherwise the claimed monistic system would not be monistic.

    The above must be true under the a priori assumption of priority monism IFF (if and only if) the a priori assumption itself is true. A theory model is (or becomes in the emergent sense) a novel subset of the monistic system. A sub-system model of a system never fully replicates or models the entire system. The model must always be incomplete. The difficult and seemingly paradoxical issue of a new subset supervening upon or being emergent from an existing set, where it did not exist previously, should be found to have a complex system emergent-evolutionary explanation and perhaps be capable of a theoretical mathematical set solution, but this is speculation on my part and well beyond my mathematical capabilities. There is also the crucial ontological issue, in this chain of reasoning, of inescapably positing that a formal system (a theory in words or a set of equations in mathematical symbols) is a subset of a real system. A sub-set of a real system is, by logical deduction, a real system also. Hence, I am saying logical deduction from our a priori assumption of complex system monism suggests that any formal system must also be a real system (as data instantiated in real-system patterns) and is thus a special sub-set type of real systems. This seeming paradoxical claim will be addressed in later chapters.

    To sum up here, a clear characteristic of a monistic cosmos system, which manifests characteristics of emergence and evolution, including the emergence of minds and then of mind-made models as subsets, will be that it demonstrates only partial reducibility to modelling and/or explanation. There will be an unavoidable incompleteness in all mathematical, scientific and philosophical theories. This consideration appears as an extension, in the reverse direction, of Hume’s observation of the infinite regress problem for the explanation of causes. As well as the infinite regress problem we may also detect, in the other direction, an “infinite emergence” problem. There would appear to be no theoretical upper or final limit to emergent novelties in the cosmos except possibly upon the heat death or other ending of the cosmos itself. However, there may be limits to possible categories of emergence although not limits to potential examples of emergence within the possible categories. We do not expect the evolution of magical unicorns or emergence of telekinesis, at least not in this universe. Pursuing the idea of “infinite emergence” too far at this juncture would take us well into the arena of speculative metaphysics rather than remaining in the zone of a more empirically conditioned metaphysics. To sound a cautionary note about models, we should never falsely idealize a model by viewing it as containing some essential form or essence of reality. That was Plato’s mistake. The essential form and essence of reality is the entirety of reality itself, not any humanly generated sub-set idea, model or equation of it.

    The ongoing and likely intractable incompleteness of science can be raised as an objection to the use of the physics relational system model as an a priori justification for metaphysical monism and for the adoption of a position of “monist existent-ism” over idealism, physicalism or dualism. The a priori justification perhaps could be critiqued as a kind of circular justification. Clearly, it is not an attempt at a circular proof, which would be a blatant fallacy, simply because an a priori justification is not, and does not claim to be, a proof. Philosophically speaking, the use of the physics relational-system model as a priori justification for complex system monist metaphysics, possessing as it does extensive empirical support, and being a simplest-possible explanation, is still far less over-reaching than the various dogmatic assumptions regarding the nature of any hypothesised Absolute beyond the observable cosmos.

    Indeed, the imputed nature of an Absolute, and thus the form of speculative metaphysics which must follow from that assumption, will vary greatly according to the specific doctrine adopted. Adherence to a physics, relational-system Occam’s razor and to a “meta-physics”, across and just beyond physics proper, does not demonstrate the same degree of disconcerting open-ended mutability and sectarian multiplication of doctrines as a priori justifications. Advances in science may be referred back to continuously and utilised progressively to update a “near-empirical meta-physics”. Science, and empiricism in general, tend to a consistent and pragmatically useable, if ultimately incomplete, representation of reality. This, to make a consequentialist judgement, is to be preferred to hard dogmatics. Finally, it must be admitted that, by reason of its combination of great instrumental power with incomplete knowledge, modern science does demonstrate serious and emergent dangers. Human generated climate change is one clear and crucial example of the dangers of applied scientific instrumental reason interacting with extant human evolved nature and human socioeconomics in their encounter with immense biosphere system complexity, the apparent realities of emergence and the issue of “radical novelty”. The scope for unforeseen consequences is vast.

  2. July 3, 2021 at 1:21 pm

    At Note 7 Fix say “The rigor-mortis quotation is attributed, at various times, to both the ecological economist Kenneth Boulding and to the economic historian Robert Heilbroner. We can find no written record for Boulding’s statement. Heilbroner, on the other hand, said the following in 1979: “the prestige accorded to mathematics in economics has given it rigor, but, alas, also mortis”.

    I suspect that Boulding said much the same thing in different words, as when, concluding the chapter on mathematics in “Economics as a Science” (1970, McGraw-Hill), he wrote “mathematics in any of its applied fields is a wonderful servant but a very bad master”.

    Where he was first right and then (very significantly here) wrong, is where he says “At the mathematical level of abstraction there is very little dispute about the meaning of symbols. For instance, x2 [x squared] means something multiplied by itself in any language, and it means nothing else” (ibid, p.98).

    That is indeed what economists believe, forgetting that (in Pythagorean geometry) the two numbers are right angles to each other, so the one can represent quantities or “real” numbers and the other motions or “imaginary” numbers. Clock numbers again can be unambiguously divided into quarter-hours, despite circular measure being incommensurable with linear measure. To theorise radio communication, mathematics and logic have had to move on since Descartes’ “flat earth” coordinate geometry and “either/or” logic.

    Fix likewise has gone wrong by following Popper’s anti-historical interpretation of Plato, who before Aristotle had invented family tree logic could still see four distinct political functions, each repeatedly mapped by a triangular process. Plato was right so far as he went, but the problem with Aristocracy was at the logical level. Marx realised that and used Hegel’s dialectical logic to represent processes, where repeating ones are formally representable by Plato’s triangle. Developing ones need the fourth function to represent second-order (e.g. technological) change. Applied to economic control, too much of that is resulting in chaos.

  3. July 4, 2021 at 1:30 am

    Thanks for the article. Clear and useful.

  4. Ken Zimmerman
    July 5, 2021 at 9:43 am

    “When it comes to essentialist totems, economics is the low-hanging fruit. But as we’ve tried to demonstrate, essentialism and traditionalism thrive elsewhere in science. It is an old problem that cuts to the core of how humans think. As Plato’s enduring spell shows, all too often we find ideas more seductive than facts.”

    “Plato called this higher plane the ‘Forms’ — a hidden realm in which real-world objects have a perfect and unchanging representation. Behind every real-world triangle, for instance, is the perfect ‘form’ of a triangle.”

    Two problems I see here. First, basing the conclusion on ‘this is how humans think’ is clearly an essentialist and traditional foundation.

    Second, what is this ‘real-world’ you keep bringing up? At best its a place holder for what ‘makes sense’ to some groups of humans based on their shared historical experiences. Which is variable both between groups and among historical contexts. People invent reality. And people of varying cultures and histories may invent different realities. Another reason to call bunk (or at least a waste of effort) on Plato. But also a warning to Plato critics to be cautious not to create an ‘essence’ with the real-world.

    • July 5, 2021 at 10:23 am

      Ken, you are missing the point of what for a long time I had never come across the academic label: second order change, whereby changing the real world changes what everyone sees.

      • Ken Zimmerman
        July 5, 2021 at 11:30 am

        Dave, which real-world are you wanting to change? There are lots from which you can choose, if you make the effort to identify them. But you are correct that changing ‘a” real-world may change how some people live and ‘see’ the world. Changing a racist world may change racists.

      • July 5, 2021 at 12:50 pm

        Ken, you may find this more helpful than your own attempt at self-defence. However, I accept that though printing a book changes the world, others only CAN then “see” it.


        “A mistake, done by Newton and Leibniz both, has resulted in changing the course of history of science in wrong direction. To solve a differential equation, which is so important in applications, is really a challenge because of that initial mistake. According to Newton and Leibniz, second order derivative of a function is the first derivative of the first derivative of the function. This means that a second derivative is an iterated limit. Similarly higher order derivatives are simply iterated limits of higher order. This is the main reason that to solve an arbitrary differential equation is a [mistake?]”.

        In terms of the arabic number notation this seems to be saying it is a mistake to treat the ‘1’ in ’14’ as a unit, for it actually means ‘ten’; likewise with higher integrals or larger numbers.

      • July 5, 2021 at 5:31 pm

        Reading the first of the WEA books, on “The Economic Curriculum: towards a Radical Reformulation”, Roncaglio’s chapter about including History of EconomicThought just gave me thought about how the above logical mistake (which I’ve often previously discussed in terms of using counting or linear instead of complex numbers) may be seen directly in the concept of ‘a market economy’. In section 4 Rocaglio says:

        “The market here is a point in time and space where demand and supply meet: its archetype is the market fair, and in more recent times the stock exchange or, more precisely, the old-fashioned continental exchanges based on call markets, even more than the continuous dealing Anglo-Saxon exchanges which constitute the rule in contemporary economies. (In the classical approach, as pointed out above, the market is a web of commodity flows, recurring period after period, which link up all sectors of the economy)”.

        What does he mean by a “call market”? It seems to me he is talking about new shares being sold in a call for credit, as was required in the early development of railways. This is not a web of continuous commodity flows but occasional monetary flows (conspicuous by their absence from classical economics) which are commodifying shares of credit provision.

        Hoping for profits, the original market fair exchanging commodities and tools, indeed, has developed into firms marketing them, corporate firms marketing firms, financiers marketing the credit needed to buy them, and banks creating nominal credit “out of thin air”. Thinking of the form of this as an arabic number structure, it is clearly a fallacy to imagine the millions column should increase at the same rate as the units column from which it is made up, and that enforcing growth in the units will ever be able to make it so.

        I would be interested to hear historian Robert Locke’s thoughts about the “old-fashioned continental exchanges” here.

      • Ken Zimmerman
        July 6, 2021 at 7:16 am

        Dave, reality doesn’t precede humans; it’s created by humans. Based on imagination and experience. And it’s modified the same way. A few years ago anthropologists began considering an ‘ontological turn’ about the foundation of Anthropology, culture. One of the conclusions is that while working to avoid ethnocentrism (evaluating other cultures in terms of one’s own) anthropologists committed an ontological error. They assumed that while modes of expression and customs may vary, that beneath them all humans live in the same world. But they do not. Cultures in many instances are not commensurate. They mark out different worlds. The debates you describe are part of one of these worlds. But do fit within the others.

        One of the examples I use when I do this as a talk is early Christianity. It receives lots of comments. Early Christianity dissolved all existing categories. Substituting ‘life in Christ’ for all. No male-female, races, workers-bosses, rich-poor, etc. This helps us understand why Christianity was nearly extinguished by 1000 CE. Mostly at the hands of many who identified themselves as Christians. This has happened many times with incommensurate cultures. It also invites us to to try understand how the losing cultures survive.

      • July 6, 2021 at 2:33 pm

        Ken, you are in the wrong blog. This is the blog of the Real World Economic Review, not one about the solipsism of Ken Zimmerman’s imaginary Humean brain.

      • Ken Zimmerman
        July 7, 2021 at 7:27 am

        We’re focused on real world. Something over and about which humans have struggled for at least 10,000 years. And perhaps much longer. You claiming that struggle does not exit is simply not at all convincing.

      • July 7, 2021 at 2:14 pm

        I’ve never claimed that the struggle does not exist. Christianity is all about why it is worth continuing it! What I have claimed is that the reality which is the brain (and not what it is imagining) has four parts, so that what one imagines depends on which subsystem of three parts of it you are using. For the sake of other readers, this from Paul Ormerod’s chapter 8 in that book on “Economic Curriculum Reform”:

        “Gradually, students who doubt the validity of [the mainstream] assumptions fall by the wayside and abandon economics. By the post-graduate stage, only the true believers remain.

        “This by itself would not necessarily be a problem. Like any scientific theory, the model of economic rationality makes assumptions which are approximations to reality. It is ultimately an empirical question as to whether, in a given situation, the assumptions offer a reasonable approximation. But somewhere along the line, a transmutation occurs, and the believers come to imagine that the model IS the reality. If the world appears different, it is the world which must be changed and not the theory. Preposterous though it may sound, it is reflected in practice in, for example, the advice given by teams of economists who proliferate in regulatory bodies.

        “Mainstream economics is [like Ken] not a completely empty box, and it does contain some powerful insights. However, it cannot be stressed too strongly that it is a way of thinking about the world rather than a series of scientifically validated propositions”.

        Which the differences in WAYS of thinking and the physiological explanation of of them are; likewise the fact that children learn language before wisdom. (See Hemenway, ibid, Ch.8).

        The world-image transformation occurs when one’s way of thinking is “transmuted” by switching from one way of thinking to another, focussed on the observation which was “muted” in the Logical Positivist way of thinking, so that far-seeing and up-to-date observation has become sub-conscious interpretation of obsolete and possibly false propositions. This has changed the meaning and therefore practice of “empiricism”; likewise the meaning of “democracy” (with “further-seeing” pluralism replaced by today’s Humean “winner-takes all” demagogy).

      • Ken Zimmerman
        July 7, 2021 at 6:10 pm

        Idealists (in all its variations) are just one part of the struggle.

  5. July 5, 2021 at 1:09 pm

    Blair wrote: “This essay is about two such pitfalls: essentialism and traditionalism”.

    I think the “essentialism” mistake is about the differential one. On “traditionalism”, I’ve always loved this quote from G K Chesterton’s “Orthodoxy”:

    “Tradition may be defined as an extension of the franchise. Tradition means giving votes to the most obscure of all classes, our ancestors. It is the democracy of the dead. All democrats object to men [this was 1908] being disqualified by the accident of birth; tradition objects to their being disqualified by the accident of death. Democracy tells us not to neglect a good man’s opinion, even if he is our groom; tradition asks us not to neglect a good man’s opinion, even if he is our father”.

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