The Structure and Theory of Theories

This content is being cross-posted to Synthetic Daisies. This post represents a first-pass approximation (and is perhaps a confounded, naive theory in itself). Hope you find it educational at the very least. Also, check out Carnival of Evolution #70 (the game of evolution), now live at Synthetic Daisies. Carnival of Evolution is a monthly blogroll that I have been hosting once a year for the last 3 years. Lots of interesting science-related readings there.

Are all theories equal? In an age where creationism is making its way into the school curriculum (under the guise of intelligent design) and forms of denialism and conspiracy theory are becoming mainstream, this is an important question. While classic philosophy of science and logical positivist approaches simply assume that the best theories evolve through the scientific process, living in an era of postmodernism, multiculturalism, and the democratization of information, demands that we think about this in a new way.

Sense-making as Layers of Information

By taking cues from theoretical artificial intelligence and contemporary examples, we can revise the theory of theories. Indeed, we live in interesting times. But what is a theory —  and why do people like to say it’s “just a theory” when they disagree with the prevailing model? One popular view of theory is that of “sense-making” [1]: that is, theories allow us to synthesize empirical observations into a mental model that allows us to generalize without becoming overwhelmed by complexity or starting from scratch every time we need to make a predictive statement.


The process of making sense of the world by building theories. Keep this in mind as we discuss the differences between naive and informed theories. COURTESY: Figure 2 in [1b].

Yet sense-making is not the whole story, particularly when theories compete for acceptance [2]. Are all theories equal, or are some theories more rigorous than others? This question is in much the same vein as the critique of “absolute facts” in postmodern theory. To make sense of this, I propose that there are actually two kinds of theory: naive theories and informed theories. Naive theories rely on common sense, and can often do very well as heuristic guides to the world. However, they tend to fall apart when presented with counter-intuitive phenomena. This is where informed theory becomes important. Informed theories are not synonymous with scientific theories — in fact, some ancient beliefs and folk theories can fall into this category alongside formal scientific theories. We will see the reasons this nominal equivalence (and non-equivalence of more naive theories) as we go through the next few paragraphs.

Naive and informed theories can be distinguished by their degree of “common sense”. Normally, common sense is a value judgement. In this case, however, common sense involves a lack of information. Naive theories tend to be intuitive rather than counterintuitive. Naive theories are constructed only from immediate observations and abductive reasoning between these observations. Naive theoretical synthesis can be thought of as a series of “if-and-then” statements. For example, if A and B are observed, and they can be linked through co-occurrence or some other criterion, then they are judged to be plausible outcomes.

The role of abductive theories in organizations. COURTESY: Free Management Library.

Informed theories, on the other hand, utilize deduction and can be divided into working theories (e.g. heuristics) and deep theories that explain, predict, and control. Working theories tend to utilize inductive logic, whereas deep theories tend to rely upon deductive logic. Since deep theories are inductive, they tend to be multi-layered constructs with mechanisms and premises based on implicit assumptions [3]. As a deductive construct, a deep informed theory can lead to inference. Inference gives us a powerful way to predict outcomes that are not so intuitive. The inference of common ancestors in phylogenetic theory allows us to reconstruct common ancestors to extant species that may look nothing like an “average” or a “cross” between these descendants.

A contingency table showing the types and examples of naive and informed theories.










Cults, Philosophies based on simple principles


Pop-psychology and pop-science




Conspiracy theories


Scientific theories

Naive and informed theories can also be distinguished by their degree of complexity. As they are based on uninformed intuition, naive theories are self-evident and self-complete, perhaps too much so. Fundamentalist religious belief and denialist-based political philosophies are based on simple sets of principles and are said by some to be tightly self-referential [4]. This inflexible self-referential capacity these theories rely on common sense over social complexity. Conspiracy theories and denialist tendencies are deeper versions of naive theories [5], but unlike their informed counterparts, do not get by on objective data, and are particularly resistant to updating [6]. By contrast, formal theories are based on abstractions and possess incompleteness-tolerance. This is often by necessity, as we cannot observe every instance of every associated process we would like to understand.

Sometimes the deepest naive theories lead to conspiracies. I have it on the highest authority.

Theory of Ontological Theories?

This leads us to an interesting set of questions. One, are the informed theories that currently exist in many fields of inquiry inevitable outcomes? Second, why are some fields more theoretical than others, and why are theory and data more integrated in some fields but not others? This is a question of historical contingency vs. field-specific structure. Is the state of theory in different areas of science due to historical context or a consequence of the natural laws they purport to make sense of? To answer these three questions, we will not briefly examine five examples from various academic disciplines. Underlying many of these approaches to informed theory is an assumption: theories are a search for ontological truths rather than the product of interactions among privileged experts. This is where informed theories hold an advantage — they can change gradually with regard to new data and hypotheses while also remaining relevant. This is an ideal in any case, so let us get to the examples:

1) Economics has an interesting relationship to theory. Formal macroeconomic theory involves two schools of thought: freshwater and saltwater. The former group favors the theories of the free-market, while the latter group adhere to Keynesian principles. However, there are also adherents of political economy, who favor models of performativity over formal mathematical models. Since the financial crisis of 2008, there has been a rise of interest in alternative economic theories and associated models, perhaps serving as an example of how theories change and are supplanted over time. And, of course, a common naive theory of economics is based on confounding micro- (or household) and macro- (or national-scale) economics.

2) Physics is though of as the gold standard of scientific theory. For example, “Einstein” is synonymous with “theory” and “genius”. The successes of deep, informed theories such as relativity and quantum mechanics is well-known. Aside from explanation and prediction of physics theory are logical consistency and grand unification as an enterprise that can often be separated from experimentation. As the gold standard of scientific theory, physics also provides a theoretical conduit to other disciplines, sometimes without modification. We will discuss this further in point #5.


This book [7] is a statement on self-anointed “bad” theories. The statement is: although string theory is structurally elegant, it is not functionally elegant like quantum gravity. But does that make quantum gravity a superior theory?

3) In neuroscience and cell biology, theories are as often deemed superfluous and inherently incomplete in lieu of ever more data. This is partially due to our level of understanding relative to the complex nature of these fields. Yet many naive and informed social theories exist, despite the complexity of the social world. So what is the difference? It could be a matter of neuroscientists and cell biologists not being oriented towards theoretical thinking. This may explain why computation neuroscience and systems biology exist as fields quite independent of their biological counterparts.

4) Theoretical constructs associated with evolution by natural selection are the consensus in evolutionary biology. This wasn’t always the case, however, as 19th century German embryologists and 18th century adherents to Lamarkian theory had competing ideas of how animal diversity was produced and perpetuated. However, Darwinian notions of evolution by natural selection did the best job at synthesizing previous knowledge about natural history with a formal mechanism for descent with modification. In popular culture, there has always been a resistance to Darwinian evolution. Usually, these divine creation-inspired naive theories are embraced as a contrarian counterbalance to deep, informed theory advocated by scientific authorities. In this case, theories have a social component, as Social Darwinism (a social co-option of Darwinian evolution) was popular in the 19th and early 20th centuries.

5) Because informed theories can explain invariants of the natural world, they often cross academic disciplines. Sometimes these crosses are direct. Evolutionary Psychology is one such example. Evolutionary theory can explain biological evolution, and as we are the products of evolution, the same theory should explain the evolution of the human mind. A simple analogical transfer, but much harder to yield the same results. But sometimes theories cross into domains not because of their suitability for the problem at hand, but because they are mathematically rigorous and/or have great predictive power in their original domain. The “quantum mind” is one such example of this. Is “quantum mind” theory any better or more powerful than a naive theory about how the mind works? It is unclear. However, this co-option suggests that even the most reputable informed theories can be cultural artifacts. A real caveat emptor.

Roger Penrose [8] will tell us about everything, in the spirit of physics and mathematics.

Properties of the Theory of Theories

The inherent dualisms of the theory of theories stems from deeper cognitive divisions between matter-of-fact and abstract thinking. As cultural constructs, matter-of-fact theories are much more amenable to narrative structures that permeate folklore and pseudo-science. This does not mean that abstract theories are “better” or any more “scientific” than matter-of-fact formulations. In fact, abstract theories are more susceptible to cultural blends [9] or symbolic confabulation [10], as these short-cuts aid us in conceptual understanding.

Scientific theories tend to be abstract, informed ones, but scientific theories that are more well-known by the general public have many features of naive theories. Examples of this include Newtonian physics and the Big Bang. There is a certain intuitive satisfaction from these two theories that are not offered by, say, quantum theory or Darwinian evolution [11]. This satisfaction arises from consistency with one’s immediate sensory surroundings and/or existing cultural myths. Interestingly, naive (and mythical) versions of quantum theory and Darwinian evolution have arisen alongside the more formal theory. These faux-theories use their informed theory counterparts as a narrative template to explain everything from the spiritual basis of the mind (Chopra’s Nonlocality) to social inequalities (Spencer’s Social Darwinism).

But what about beauty in theory? Again, this could arguably be a feature of naive theorizing. Whether it is the over-application of parsimony or an over-reliance on elegance and beauty [7], informed theories require a degree of initial convolution before such features can be incorporated into the theory. In other words, these things should not be goals in and of themselves. Rather, deep, informed theories should be robust enough to be improved upon incrementally without having to be being completely replaced [12]. The beauty of parsimony and symmetry should only considered to be a nice side-benefit. There is also a significant role for mental and statistical models in theory-building, but for the sake of relative simplicity I am intentionally leaving this discussion aside for now.


Tides go in, tides go out. When it’s God’s will, it’s a short and neat proposition. When it’s more complicated, then it’s scientific inquiry. COURTESY: Geekosystem and High Power Rocketry blogs.

In a future post, I will move from the notion of a theory of theories to the need for an analysis of analyses. Much like the theory of theories, a deep reconsideration of analysis is also needed. This has been driven by the scientific replication crisis, the proliferation of data (e.g. infographics) on the internet, and the rise of big data (e.g. very large datasets, once again enabled by the internet).


[1] Here are a few references on the cognition of sense-making, particularly as it related to theory construction:

a) Klein, G., Moon, B. and Hoffman, R.F.   Making sense of sensemaking I: alternative perspectives. IEEE Intelligent Systems, 21(4), 70–73 (2006).

b) Pirolli, P., & Card, S.   The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. Proceedings of the International Conference on Intelligence Analysis (2005).

[2] Here are some references that will help you understand the “hows” and “whys” of theory competition, with particular relevance to what I am calling deep, informed theories:

a) Steiner, E.   Methodology of Theory-building. Educology research Associates, Sydney (1988).

b) Kuhn, T.   The structure of scientific revolutions. University of Chicago Press (1962).

c) Arbesman, S.   The Half-life of Facts. Current Press (2012).

[3] sometimes, naive theorists will accuse deep, informed theorists of being “stupid” or “irrelevant”. This is because the theories generated do not conform to the expectations and understandings of the naive theorist.

Paul Krugman calls one such instance “the myth of the progressive economist”: Krugman, P.   Stupidity in Economic Discourse 2. The Conscience of a Liberal blog, April 1 (2014).

[4] Religious fundamentalist and  denialist groups also seem to theorize in a deep naive manner, using a tightly self-referential set of theoretical propositions. In these cases, however, common sense is replaced with a intersubjective (e.g. you have to be part of the group to understand) self-evidence. The associated logical extremes tend to astound people not in the “know”.

a) Example from religious fundamentalism: Koerth-Baker, M.   What do Christian fundamentalists have against set theory? BoingBoing, August 7 (2012) AND Simon, S.   Special Report: Taxpayers fund creationism in the classroom. Politico Pro, March 24 (2014).

For a discussion of Nominalism (basic math) vs. Platonism (higher math) in Mathematics, please see: Franklin, J.   The Mathematical World. Aeon Magazine, April 7 (2014).

b) Example from climate change denialism: Cook, J. and Lewandowsky, S.   Recursive Fury: facts and misrepresentations. Skeptical Science blog, March 21 (2013).

[5] for one such example, please see: Roberts, D.   Conservative hostility to science predates climate science., August 12 (2013).

For a more comprehensive background on naive theories (in this case, the development of naive theories of physics among children) please see the following:

a) Reiner, M., Slotta, J.D., Chi, M.T.H., and Resnick, L.B.   Naive Physics Reasoning: a commitment to substance-based conceptions. Cognition and Instruction, 18(1), 1-34 (2000).

b) Vosniadou, S.   On the Nature of Naive Physics. In “Reconsidering Conceptual Change: issues in theory and practice”, M. Limon and L. Mason, eds., Pgs. 61-76, Kluwer Press (2002).

For the continued naive popularity of the extramission theory of vision, please see the following:

c) Winer, G. A., Cottrell, J. E., Gregg, V., Fournier, J. S., & Bica, L. A. (2002). Fundamentally misunderstanding visual perception: Adults’ beliefs in visual emissions. American Psychologist, 57, 417-424.

[6] sometimes, theories that are denialist in tone are constructed to preserve certain desired outcomes from data that actually suggest otherwise. In other words, a narrative takes precedence over a more objective understanding. Charles Seife calls this a form of “proofiness“.

For more, please see: Seife, C. Proofiness: how you’re being fooled by numbers. Penguin Books (2011).

[7] Smolin, L.   The Trouble with Physics. Houghton-Mifflin (2006).

[8] Penrose, R., Shimony, A., Cartwright., N., and Hawking, S.   The large, the small, and the human mind. Cambridge University Press (1997).

[9] Fauconnier, G.   Methods and Generalizations. In “Cognitive Linguistics: foundations, scope, and methodology“. T. Janssen and G. Redeker, eds, 95-128. Mouton DeGruyter (1999).

[10] Confounds are a psychological concept that identifies when ideas and deep informed theories are confused or otherwise condensed for purposes of superficial understanding or misinterpretation. In the case of creationists, such intentional confounds are often used to generate doubt and confusion of subtle and complex concepts.

a) Role of confabulation in cognition (a theory): Hecht-Nielsen, R.   Confabulation Theory. Scholarpedia, 2(3), 1763 (2007).

b) Example of intentional confounding from anti-evolutionism: Moran, L.A.   A creationist tries to understand genetic load. Sandwalk blog, April 1 (2014).

[11] By “conforming to intuitive satisfaction”, I mean that Newtonian physics explains the physics of things we interact with on an everyday basis, and the Big Bang is consistent with the idea of divine creation (or creation from a singular point). This is not to say that these theories were developed because of these features, but perhaps explains their widespread popular appeal.

[12] Wholesale replacement of old deep, informed theories is explained in detail here: Kuhn, T.   Structure of Scientific Revolutions. University of Chicago Press (1962).