The Dickens‑Flynn model is an attempt by William Dickens and James Flynn (2001) to explain how environment and genes can interact to account both for environmentally driven increases in raw intelligence scores over time (the Flynn effect) and for genetically driven and stable individual intelligence differences within the human population (Spearman’s g). On first glance there is much that appears promising about the Dickens‑Flynn model, for it does directly address the observable tension between the Flynn effect and g, something that many explanations for the Flynn effect fail to do. And yet further inspection also reveals that the model is troubling in a rather conspicuous way—it sports the overall mechanics of a Rube Goldberg machine.
Perhaps the first thing to recognize about the Dickens‑Flynn model is the degree to which leverage plays the key role. For instance in the authors’ general outline of the model, small genetic advantages are described as being amplified through the means of a natural attraction to environmental surroundings that serve to enhance those advantages. Environmental influences on population-wide intelligence characteristics are said to be boosted through such factors as social multipliers and rolling triggers. And finally, genetic and environmental forces are depicted as mutually propelling each other by means of an hypothesized assortment of reciprocal feedback mechanisms. What might strike the reader is how stridently mathematical this model is, especially in its employment of such concepts as multipliers, triggers and feedback loops: instead of associating these terms to real-world examples or empirical descriptions, Dickens and Flynn more frequently cast them into the role of free variable, serving to balance out and drive their equations where required. Plus this tendency towards calculational necessity can be heard also in the authors’ replies to the model’s critics, where arguments against the plausibility of social multipliers and circular feedback mechanisms are frequently met by Dickens and Flynn with an appeal to such notions as simultaneous equations, estimated network effects and functional form.
None of this is to say that the Dickens‑Flynn model is inherently wrong or essentially inconsistent. It remains perfectly conceivable that the model’s many mechanisms and various factors can be fitted—with a little more mathematical tweaking perhaps—to the observable characteristics of human intelligence behavior. But even if this were so, parsing through such ideas as social multipliers, rolling triggers and reciprocal feedback mechanisms, one is left with the distinct impression that the Dickens‑Flynn model can in no way be described as simple or straightforward, and this of course in stark contrast to the phenomenon which the model is intended to explain, a phenomenon which can be captured in very few words (human raw intelligence scores increase consistently and universally over time). A charitable way of depicting the Dickens‑Flynn model would be to say that it is intricate and complex; a less charitable depiction would emphasize its propensity towards convolution.
Which raises a question: why would Dickens and Flynn insist on developing a model of such intricacy and complexity? Why did they not gravitate instead to something more direct, with fewer moving parts? Flynn (2007), ever the paragon of candor, provides a thorough and revealing answer in the pages of his book What is Intelligence? There Flynn notes that during the height of the intelligence race debates, Richard Lewontin (1976) had offered a compelling description for how an environmental influence could uniformly impact an entire population while still leaving undisturbed any of that population’s genetically driven characteristics:
“Lewontin tried to solve the paradox. He distinguished the role of genes within groups from the role of genes between groups. He imagined a sack of seedcorn with plenty of genetic variation randomly divided into two batches, each of which would therefore be equal for overall genetic quality. Batch A is grown in a uniform and optimal environment, so within that group all height differences at maturity are due to genetic variation; batch B is grown in a uniform environment which lacks enough nitrates, so within that group all height differences are also genetic. However, the difference in average height between the two groups will, of course, be due entirely to the unequal quality of their two environments.”
Although Lewontin’s description proved mostly untenable within the context of the intelligence race debates, Flynn later recognized that it seemed to offer an ideal explanation for the Flynn effect:
“So now we seemed to have a solution. The present generation has some potent environmental advantage absent from the last generation that explains its higher average IQ. Let us call it Factor X. Factor X will simply not register in twin studies. After all, the two members of a twin pair are by definition of the same generation. Since Factor X was completely missing within the last generation, no one benefited from it at all and, therefore, it can hardly explain any IQ differences within the last generation. It will not dilute the dominance of genes. Since Factor X is completely uniform within the present generation, everyone benefits from it to the same degree and it cannot explain IQ differences within the present generation. Once again, the dominance of genes will be unchallenged. Therefore, twin studies could show that genes explain 100 percent of IQ differences within generations, and yet, environment might explain 100 percent of the average IQ difference between generations.”
And yet as Flynn attempted to apply Lewontin’s idea specifically to the Flynn effect, he quickly found himself frustrated:
“However, Lewontin offers us a poisoned apple. History has not experimented with the last two generations as we might experiment with plants in a laboratory. Consider the kind of factors that might explain massive IQ gains, such as better nutrition, more education, more liberal parenting, and the slow spread of the scientific ethos. It is quite unreal to imagine any of these affecting two generations with uniformity. Certainly, everyone was not badly nourished in the last generation, everyone well nourished at present; everyone without secondary school in the last generation, everyone a graduate at present; everyone raised traditionally in the last generation, everyone raised liberally at present; everyone bereft of the scientific ethos in the last generation, everyone permeated with it at present. If the only solution to our paradox is to posit a Factor X or a collection of such, it seems even more baffling than before. We should shut this particular door as follows: a solution is plausible only if it does not posit a Factor X.”
It is in this manner that Flynn begins to place a strange restriction around what he might deem to be an acceptable explanation for the Flynn effect: any explanation would have to carry all the desirable characteristics of a Factor X, but without actually being a Factor X. And it is into the space of this restriction that the Dickens‑Flynn model comes to be. Flynn is quite forthcoming about what he perceives to be the model’s most valuable characteristic:
“Best of all, our solution posits no Factor X.”
It is from out of this historical context that one can get a better sense for why the Dickens‑Flynn model must of necessity be so intricate and complex, and not simple and straightforward. It is as if Flynn has set forth the task of building a device designed to capture mice, and yet the device must in no way resemble a mousetrap. Therefore it is not all that surprising that the model’s surveyors soon find themselves inundated with the equivalent of levers, pulleys, waterwheels, whistles and bells, and if the objection is made that in the end it is still just a mousetrap, then the model’s architects can point to the enormous amounts of clever mathematical machinery and insist no one would mistake it for any such thing. And if the objection is raised that the mice are after all scurrying away, then the model’s assemblers can suggest that perhaps a few more pieces of calculational duct tape and functional chicken wire should take care of the matter. Whether or not the many free parameters of the Dickens‑Flynn model can ultimately be fitted to the characteristics of human intelligence is a matter difficult to judge, but that does not negate the readily made observation that the Dickens‑Flynn model is quite frankly a massively entangled contraption.
Flynn’s actual mistake is to have prematurely shut the door on a Factor X.
Flynn’s reasoning is perfectly correct when he notes that not only is every iterated item on his Factor X list inadequate for explaining the Flynn effect, but that indeed no particular item or subset of items could conceivably possess the requisite power or ubiquitous reach to account for population-wide, generational increases in raw intelligence scores. But instead of giving up—instead of prematurely shutting the door—what Flynn needs to do at this point is to engage in some thinking outside the box, or perhaps to summon a phrase more germane to the problem at hand, what Flynn needs to do is to engage in some thinking outside the human skull.
In the essay The Flynn Effect’s Unseen Hand, a model for human intelligence is presented in which the term environmental intelligence is defined as the total amount of non-biological pattern, structure and form tangibly contained within the human environment. Environmental intelligence serves as the all-encompassing, palpable location of human intelligence, and it has been the consistent increase in environmental intelligence over the course of human history that has served as the direct driver of the Flynn effect. It might not be entirely accurate to label environmental intelligence as a Factor X, since it is not really a factor, not a specific thing—instead environmental intelligence captures the impact of the structural surroundings as a whole. But nomenclature aside, environmental intelligence carries all the necessary characteristics of a Factor X. Environmental intelligence is ubiquitous. Environmental intelligence is constantly increasing. Environmental intelligence remains independent of the genetic influences driving individual intelligence differences.
The common objection that might be raised against a model of environmental intelligence is that it places the material location of intelligence firmly outside the human skull, firmly outside the human brain. But in exchange for jettisoning the widespread assumption that intelligence is a product strictly of human neurons—in exchange for accepting the total amount of non-biological pattern, structure and form as both the material substance of intelligence itself and as an ideal Factor X—what is regained thereby is a great deal of simplicity. Gone is the need for social multipliers. Gone is the need for triggers. Gone is the need for feedback loops. Indeed gone is the need for any type of genetic/environmental interaction at all, especially of the complex, intricate kind. What one regains by jettisoning the Dickens‑Flynn model and by accepting instead a model of environmental intelligence is all the simplicity and straightforwardness that Lewontin must have originally had in mind.
It may no longer be fashionable in this era of modern statistical science, but simplicity and straightforwardness should still count for something. It is better to catch one’s mice with a mousetrap.
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