What would you think if you heard about a new fortune-telling device that is touted to predict psychological traits like depression, schizophrenia and school achievement? What’s more, it can tell your fortune from the moment of your birth, it is completely reliable and unbiased — and it only costs £100.
This might sound like yet another pop-psychology claim about gimmicks that will change your life, but this one is in fact based on the best science of our times. The fortune teller is DNA. The ability of DNA to understand who we are, and predict who we will become has emerged in the last three years, thanks to the rise of personal genomics. We will see how the DNA revolution has made DNA personal by giving us the power to predict our psychological strengths and weaknesses from birth. This is a game-changer as it has far-reaching implications for psychology, for society and for each and every one of us.
This DNA fortune teller is the culmination of a century of genetic research investigating what makes us who we are. When psychology emerged as a science in the early twentieth century, it focused on environmental causes of behavior. Environmentalism — the view that we are what we learn — dominated psychology for decades. From Freud onwards, the family environment, or nurture, was assumed to be the key factor in determining who we are. (Plomin, 2018: 6, my emphasis)
The main premise of Plomin’s 2018 book Blueprint is that DNA is a fortune teller while personal genomics is a fortune-telling device. The fortune-telling device Plomin most discusses in the book is polygenic scores (PGS). PGSs are gleaned from GWA studies; SNP genotypes are then added up with scores of 0, 1, and 2. Then, the individual gets their PGS for trait T. Plomin’s claim—that DNA is a fortune teller—though, falls since DNA is not a blueprint—which is where the claim that “DNA is a fortune teller” is derived.
It’s funny that Plomin calls the measure “unbiased”, (he is talking about DNA, which is in effect “unbiased”), but PGS are anything BUT unbiased. For example, most GWAS/PGS are derived from European populations. But, for example, there are “biases and inaccuracies of polygenic risk scores (PRS) when predicting disease risk in individuals from populations other than those used in their derivation” (De La Vega and Bustamante, 2018). (PRSs are derived from statistical gene associations using GWAS; Janssens and Joyner, 2019.) Europeans make up more than 80 percent of GWAS studies. This is why, due to the large amount of GWASs on European populations, that “prediction accuracy [is] reduced by approximately 2- to 5-fold in East Asian and African American populations, respectively” (Martin et al, 2018). See for example Figure 1 from Martin et al (2018):
With the huge number of GWAS studies done on European populations, these scores cannot be used on non-European populations for ‘prediction’—even disregarding the other problems with PGS/GWAS.
By studying genetically informative cases like twins and adoptees, behavioural geneticists discovered some of the biggest findings in psychology because, for the first time, nature and nurture could be disentangled.
… DNA differences inherited from our parents at the moment of conception are the consistent, lifelong source of psychological individuality, the blueprint that makes us who we are. A blueprint is a plan. … A blueprint isn’t all that matters but it matters more than everything else put together in terms of the stable psychological traits that make us who we are. (Plomin, 2018: 6-8, my emphasis)
Nevermind the slew of problems with twin and adoption studies (Joseph, 2014; Joseph et al, 2015; Richardson, 2017a). I also refuted the notion that “A blueprint is a plan” last year, quoting numerous developmental systems theorists. The main thrust of Plomin’s book—that DNA is a blueprint and therefore can be seen as a fortune teller using the fortune-telling device to tell the fortunes of the people’s whose DNA are analyzed—is false, as DNA does not work how it does in Plomin’s mind.
These big findings were based on twin and adoption studies that indirectly assessed genetic impact. Twenty years ago the DNA revolution began with the sequencing of the human genome, which identified each of the 3 billion steps in the double helix of DNA. We are the same as every other human being for more than 99 percent of these DNA steps, which is the blueprint for human nature. The less than 1 per cent of difference of these DNA steps that differ between us is what makes us who we are as individuals — our mental illnesses, our personalities and our mental abilities. These inherited DNA differences are the blueprint for our individuality …
[DNA predictors] are unique in psychology because they do not change during our lives. This means that they can foretell our futures from our birth.
The applications and implications of DNA predictors will be controversial. Although we will examine some of these concerns, I am unabashedly a cheerleader for these changes. (Plomin, 2018: 8-10, my emphasis)
This quote further shows Plomin’s “blueprint” for the rest of his book—DNA can “foretell our futures from our birth”—and how it affects his conclusions gleaned from his work that he mostly discusses in his book. Yes, all scientists are biased (as Stephen Jay Gould noted), but Plomin outright claimed to be an unabashed cheerleader for his work. Plomin’s self-admission for being an “unabashed cheerleader”, though, does explain some of the conclusions he makes in Blueprint.
However, the problem with the mantra ‘nature and nurture’ is that it runs the risk of sliding back into the mistaken view that the effects of genes and environment cannot be disentangled.
Our future is DNA. (Plomin, 2018: 11-12)
The problem with the mantra “nature and nurture” is not that it “runs the risk of sliding back into the mistaken view that the effects of genes and environment cannot be disentangled”—though that is one problem. The problem is how Plomin assumes how DNA works. That DNA can be disentangled from the environment presumes that DNA is environment-independent. But as Moore shows in his book The Dependent Gene—and as Schneider (2007) shows—“the very concept of a gene requires the environment“. Moore notes that “The common belief that genes contain context-independent “information”—and so are analogous to “blueprints” or “recipes”—is simply false” (quoted in Schneider, 2007). Moore showed in The Dependent Gene that twin studies are flawed, as have numerous other authors.
Lewkowicz (2012) argues that “genes are embedded within organisms which, in turn, are embedded in external environments. As a result, even though genes are a critical part of developmental systems, they are only one part of such systems where interactions occur at all levels of organization during both ontogeny and phylogeny.” Plomin—although he does not explicitly state it—is a genetic reductionist. This type of thinking can be traced back, most popularly, to Richard Dawkins’ 1976 book The Selfish Gene. The genetic reductionists can, and do, make the claim that organisms can be reduced to their genes, while developmental systems theorists claim that holism, and not reductionism, better explains organismal development.
The main thrust of Plomin’s Blueprint rests on (1) GWA studies and (2) PGSs/PRSs derived from the GWA studies. Ken Richardson (2017b) has shown that “some cryptic but functionally irrelevant genetic stratification in human populations, which, quite likely, will covary with social stratification or social class.” Richardson’s (2017b) argument is simple: Societies are genetically stratified; social stratification maintains genetic stratification; social stratification creates—and maintains—cognitive differentiation; “cognitive” tests reflect prior social stratification. This “cryptic but functionally irrelevant genetic stratification in human populations” is what GWA studies pick up. Richardson and Jones (2019) extend the argument and argue that spurious correlations can arise from genetic population structure that GWA studies cannot account for—even though GWA study authors claim that this population stratification is accounted for, social class is defined solely on the basis of SES (socioeconomic status) and therefore, does not capture all of what “social class” itself captures (Richardson, 2002: 298-299).
Plomin also heavily relies on the results of twin and adoption studies—a lot of it being his own work—to attempt to buttress his arguments. However, as Moore and Shenk (2016) show—and as I have summarized in Behavior Genetics and the Fallacy of Nature vs Nurture—heritability estimates for humans are highly flawed since there cannot be a fully controlled environment. Moore and Shenk (2016: 6) write:
Heritability statistics do remain useful in some limited circumstances, including selective breeding programs in which developmental environments can be strictly controlled. But in environments that are not controlled, these statistics do not tell us much. In light of this, numerous theorists have concluded that ‘the term “heritability,” which carries a strong conviction or connotation of something “[in]heritable” in the everyday sense, is no longer suitable for use in human genetics, and its use should be discontinued.’ 31 Reviewing the evidence, we come to the same conclusion.
Heritability estimates assume that nature (genes) can be separated from nurture (environment), but “the very concept of a gene requires the environment” (Schneider, 2007) so it seems that attempting to partition genetic and environmental causation of any trait T is a fool’s—reductionist—errand. If the concept of gene depends on and requires the environment, then how does it make any sense to attempt to partition one from the other if they need each other?
Let’s face it: Plomin, in this book Blueprint is speaking like a biological reductionist, though he may deny the claim. The claims from those who push PRS and how it can be used for precision medicine are unfounded, as there are numerous problems with the concept. Precision medicine and personalized medicine are similar concepts, though Joyner and Paneth (2015) are skeptical of its use and have seven questions for personalized medicine. Furthermore, Joyner, Boros and Fink (2018) argue that “redundant and degenerate mechanisms operating at the physiological level limit both the general utility of this assumption and the specific utility of the precision medicine narrative.” Joyner (2015: 5) also argues that “Neo-Darwinism has failed clinical medicine. By adopting a broader perspective, systems biology does not have to.”
Janssens and Joyner (2019) write that “Most [SNP] hits have no demonstrated mechanistic linkage to the biological property of interest.” Researchers can show correlations between disease phenotypes and genes, but they cannot show causation—which would be mechanistic relations between the proposed genes and the disease phenotype. Though, as Kampourakis (2017: 19), genes do not cause diseases on their own, they only contribute to its variation.
GPS are unique predictors in the behavioural sciences. They are an exception to the rule that correlations do not imply causation in the sense that there can be no backward causation when GPS are correlated with traits. That is, nothing in our brains, behaviour or environment changes inherited differences in DNA sequence. A related advantage of GPS as predictors is that they are exceptionally stable throughout the life span because they index inherited differences in DNA sequence. Although mutations can accrue in the cells used to obtain DNA, like any cells in the body these mutations would not be expected to change systematically the thousands of inherited SNPs that contribute to a GPS.
Turkheimer goes on to say that this (false) assumption by Plomin and Stumm (2018) assumes that there is no top-down causation—i.e., that phenotypes don’t cause genes, or there is no causation from the top to the bottom. (See the special issue of Interface Focus for a slew of articles on top-down causation.) Downward causation exists in biological systems (Noble, 2012, 2017), as does top-down. The very claim that “nothing in our brains, behaviour or environment changes inherited differences in DNA sequence” is ridiculous! This is something that, of course, Plomin did not discuss in Blueprint. But in a book that, supposedly, shows “how DNA makes us who we are”, why not discuss epigenetics? Plomin is confused, because DNA methylation impacts behavior and behavior impacts DNA methylation (Lerner and Overton, 2017: 114). Lerner and Overtone (2017: 145) write that:
… it should no longer be possible for any scientist to undertake the procedure of splitting of nature and nurture and, through reductionist procedures, come to conclusions that the one or the other plays a more important role in behavior and development.
Plomin’s reductionist takes, therefore again, fail. Plomin’s “reluctance” to discuss “tangential topics” to “inherited DNA differences” included epigenetics (Plomin, 2018: 12). But it seems that his “reluctance” to discuss epigenetics was a downfall in his book as epigenetic mechanisms can and do make a difference to “inherited DNA differences” (see for example, Baedke, 2018, Above the Gene, Beyond Biology: Toward a Philosophy of Epigenetics and Meloni, 2019, Impressionable Biologies: From the Archaeology of Plasticity to the Sociology of Epigenetics see also Meloni, 2018). The genome can and does “react” to what occurs to the organism in the environment, so it is false that “nothing in our brains, behaviour or environment changes inherited differences in DNA sequence” (Plomin and Stumm, 2018), since our behavior and actions can and do methylate our DNA (Meloni, 2014) which falsifies Plomin’s claim and which is why he should have discussed epigenetics in Blueprint. End Edit
So the main premise of Plomin’s Blueprint is his two claims: (1) that DNA is a fortune teller and (2) that personal genomics is a fortune-telling device. He draws these big claims from PGS/PRS studies. However, over 80 percent of GWA studies have been done on European populations. And, knowing that we cannot use these datasets on other, non-European datasets, greatly hampers the uses of PGS/PRS in other populations—although the PGS/PRS are not that useful in and of itself for European populations. Plomin’s whole book is a reductionist screed—“Sure, other factors matter, but DNA matters more” is one of his main claims. Though, a priori, since there is no privileged level of causation, one cannot privilege DNA over any other developmental variables (Noble, 2012). To understand disease, we must understand the whole system and how when one part of the system becomes dysfunctional how it affects other parts of the system and how it runs. The PGS/PRS hunts are reductionist in nature, and the only answer to these reductionist paradigms are new paradigms from systems biology—one of holism.
Plomin’s assertions in his book are gleaned from highly confounded GWA studies. Plomin also assumes that we can disentangle nature and nurture—like all reductionists. Nature and nurture interact—without genes, there would be an environment, but without an environment, there would be no genes as gene expression is predicated on the environment and what occurs in it. So Plomin’s reductionist claim that “Our future is DNA” is false—our future is studying the interactive developmental system, not reducing it to a sum of its parts. Holistic biology—systems biology—beats reductionist biology—the Neo-Darwinian Modern Synthesis.
DNA is not a blueprint nor is it a fortune teller and personal genomics is not a fortune-telling device. The claim that DNA is a blueprint/fortune teller and personal genomics is a fortune-telling device come from Plomin and are derived from highly flawed GWA studies and, further, PGS/PRS. Therefore Plomin’s claim that DNA is a blueprint/fortune teller and personal genomics is a fortune-telling device are false.
(Also read Erick Turkheimer’s 2019 review of Plomin’s book The Social Science Blues, along with Steve Pitteli’s review Biogenetic Overreach for an overview and critiques of Plomin’s ideas. And read Ken Richardson’s article It’s the End of the Gene As We Know It for a critique of the concept of the gene.)
One debate in the philosophy of science is whether or not a scientific hypothesis should make testable predictions or merely explain only what it purports to explain. Should a scientific hypothesis H predict previously unknown facts of the matter or only explain an observation? Take, for example, evolutionary psychology (EP). Any EP hypothesis H can speculate on the so-called causes that led a trait to fixate in a biological population of organisms, but the claim that they can do more than that—that is, that they can generate successful predictions of previously unknown facts not used in the construction of the hypothesis—but that’s all they can do. The claim, therefore, that EP hypotheses are anything but just-so stories, is false.
Prediction and novel facts
For example, Einstein’s theory of general relativity predicted the bending of light, which was a novel prediction for the hypothesis (see pg 177-180 for predictions generated from Einstein’s theory). Fresnel’s wave theory of light predicted different infraction fringes to the prediction of the white spot—a spot which appears in a circular object’s shadow due to Fresnel diffraction (see Worrall, 1989). So Fresnel’s theory explained the diffraction and the diffraction then generated testable—and successful—novel predictions (see Magnus and Douglas, 2013). There is an example of succeful novel prediction. Ad hoc hypotheses are produced “for this” explanation—so the only evidence for the hypothesis is, for example, the existence of trait T. EP hypotheses attempt to explain the fixation of any trait T in humans, but all EP hypotheses do is explain—they generate no testable, novel predictions of previously unknown facts.
A defining feature of science and what it purports to do is to predict facts-of-the-matter which are yet to be known. John Beerbower (2016) explains this well in his book Limits of Science? (emphasis mine):
At this point, it seems appropriate to address explicitly one debate in the philosophy of science—that is, whether science can, or should try to, do more than predict consequences. One view that held considerable influence during the first half of the twentieth venture is called the predictivist thesis: that the purpose of science is to enable accurate predictions and that, in fact, science cannot actually achieve more than that. The test of an explanatory theory, therefore, is its success at prediction, at forecasting. This view need not be limited to actual predictions of future, yet to happen events; it can accommodate theories that are able to generate results that have already been observed or, if not observed, have already occurred. Of course, in such cases, care must be taken that the theory has not simply been retrofitted to the observations that have already been made—it must have some reach beyond the data used to construct the theory.
That a theory or hypothesis explains observations isn’t enough—it must generate successful predictions of novel facts. If it does not generate any novel facts-of-the-matter, then of what use is the hypothesis if it only weakly justifies the phenomenon in question? So now, what is a novel fact?
A novel fact is a fact that’s generated by hypothesis H that’s not used in the construction of the hypothesis. For example, Musgrave (1988) writes:
All of this depends, of course, on our being able to make good the intuitive distinction between prediction and novel prediction. Several competing accounts of when a prediction is a novel prediction for a theory have been produced. The one I favour, due to Elie Zahar and John Worral says that a predicted fact is a novel fact for a theory if it was not used to construct that theory — where a fact is used to construct a theory if it figures in the premises from which that theory was deduced.
Mayo (1991: 524; her emphasis) writes that a “novel fact [is] a newly discovered fact—one not known before used in testing.” So a fact is novel when it predicts a fact of the matter not used in the construction of the hypothesis—i.e., a future event. About novel predictions, Musgrave also writes that “It is only novel predictive success that is surprising, where an observed fact is novel for a theory when it was not used to construct it.” So hypothesis H entails evidence E; evidence E is not used in the construction of hypothesis H, therefore E is novel evidence for hypothesis H.
To philosopher of science Imre Lakatos, a progressive research program is one that generates novel facts, whereas a degenerating research program either fails to generate novel facts or the predictions made that were novel continue to be falsified, according to Musgrave in his article on Lakatos. We can put EP in the “degenerating research program, as no EP hypothesis generates any type of novel prediction—the only evidence for the trait is the existence of the trait.
The term “just-so stories” comes from Rudyard Kipling Just-so Stories for Little Children. Then Gould and Lewontin used the term for evolutionary hypotheses that can only explain and not predict future as-of-yet-known events. Law (2016) notes that just-so stories offer “little in the way of independent evidence to suggest that it is actually true.” Sterelny and Griffiths (1999: 61) state that just-so stories are “… an adaptive scenario, a hypothesis about what a trait’s selective history might have been and hence what its function may be.” Examples of just-so stories covered on this blog include: beards, FOXP2, cartels and Mesoamerican ritual sacrifice, Christian storytelling, just-so storytellers and their pet just-so stories, the slavery hypertension hypothesis, fear of snakes and spiders, and cold winter theory. Smith (2016: 278) has a helpful table showing ten different definitions and descriptions of just-so stories:
So the defining criterion for just-so stories is that there must be independent evidence to believe the proposed explanation for the existence of the trait. There must be independent reasons to believe a certain hypothesis, as the defining feature of a scientific hypothesis or theory is whether or not it can predict yet-to-happen events. Though, as Beerbower notes, we have to be careful that we do not retrofit the observations.
One can make an observation. Then they can work backward (what Richardson (2007) elicits is “reverse engineering”) and posit (speculate about) a good-sounding story (just-so storytelling) to explain this observation. Reverse engineering is “a process of figuring out the design of a mechanism on the basis of an analysis of the tasks it performs” (Buller, 2005: 92). Of course, the just-so storyteller can then create a story to explain the fixation of the trait in question. But that’s only (purportedly) the explanation of why the trait came to fixation for us to observe it today. There are no testable predictions of previously unknown facts. So it’s all storytelling—speculation.
The theory of natural selection is then deployed to attempt the explain the fixation of trait T in any population. It is true that a hypothesis is weakly corroborated by the existence of trait T, but what makes it a just-so story is the fact that there are no successful predictions of previously unknown facts,
When it comes to EP, one can say that the hypothesis “makes sense” and it “explains” why trait T still exists and went to fixation. However, the story only “makes sense” because there is no other way for it to be—if the story didn’t “make sense”, then the just-so storyteller wouldn’t be telling the story because it wouldn’t satisfy their aims of “proving” that a trait is an adaptation.
Smith (2016:277-278) notes 7 just-so story triggers:
1) proposing a theory-driven rather than a problem-driven explanation, 2) presenting an explanation for a change without providing a contrast for that change, 3) overlooking the limitations of evidence for distinguishing between alternative explanations (underdetermination), 4) assuming that current utility is the same as historical role, 5) misusing reverse engineering, 6) repurposing just-so stories as hypotheses rather than explanations, and 7) attempting to explain unique events that lack comparative data.
EP is most guilty of (3), (4), (5), (6), and (7). It is guilty of (3) in that it hardly ever posits other explanations for trait T, it’s always “adaptation”, as EP is an adaptationist paradigm. It is guilty of (4) perhaps the most. That trait T still exists and is useful for this today is not evidence that trait T was selected-for its use as we see it today. This then leads to (5) which is the misuse of reverse engineering. Just-so stories are ad hoc (“for this”) explanations and these types of explanations are ad hoc if there is no independent data for the hypothesis. Of course, it is guilty of (7) in that it attempts to explain, of course, unique events in human evolution. Many problems exist for evolutionary psychology (see for example Samuels, 1998; Lloyd, 1999; Prinz, 2006;), but the biggest problem is the ability of any hypothesis to generate testable, novel predictions. Smith (2016: 279) further writes that:
An important weakness in the use of narratives for scientific purposes is that the ending is known before the narrative is constructed. Merton pointed out that a “disarming characteristic” of ex post facto explanations is that they are always consistent with the observations because they are selected to be so.
Bo Winegard, in his defense of just-so storytelling, writes “that inference to the best explanation most accurately describes how science is (and ought to be) practiced. According to this description, scientists forward theories and hypotheses that are coherent, parsimonious, and fruitful.” However, as Smith (2016: 280-281) notes, that a hypothesis is “coherent”, “parsimonious” and “fruitful” (along with 11 more explanatory virtues of IBE, including depth, precision, consilience, and simplicity) is not sufficient to accept IBE—IBE is not a solution to the problems proposed by the just-so story critics as the slew of explanatory virtues do not lend evidence that T was an adaptation and thusly do not lend evidence that hypothesis H is true.
Simon (2018: 5) concludes that “(1) there is much rampant speculation in evolutionary psychology as to the reasons and the origin for certain traits being present in human beings, (2) there is circular reasoning as to a particular trait’s supposed advantage in adaptability in that a trait is chosen and reasoning works backward to subjectively “prove” its adaptive advantage, (3) the original classical theory is untestable, and most importantly, (4) there are serious doubts as to Natural Selection, i.e., selection through adaptive advantage, being the principal engine for evolution.” (1) is true since that’s all EP is—speculation. (2) is true in evolutionary psychologists notice trait T and that, since it survived today, there must be a function it performs for why natural selection “selected” the trait to propagate in species (though selection cannot select-for certain traits). (3) it is untestable in that we have no time machine to go back and watch how trait T evolved (this is where the storytelling narrative comes in: if only we had a good story to tell about the evolution of trait T). And finally, (4) is also true since natural selection is not a mechanism (see Fodor, 2008; Fodor and Piattelli-Palmarini, 2010).
EP exists in an attempt to explain so-called psychological adaptations humans have to the EEA (environment of evolutionary adaptiveness). So one looks at the current phenotype and then looks to the past in an attempt to construct a “story” which shows how a trait came to fixation. There are, furthermore, no hallmarks of adaptation. When one attempts to use selection theory to explain the fixation of trait T, they must wrestle with spandrels. Spandrels are heritable, can increase fitness, and they are selected as well—as the whole organism is selected. This also, of course, falls right back to Fodor’s (2008) argument against natural selection. Fodor (2008: 1) writes that the central claim of EP “is that heritable properties of psychological phenotypes are typically adaptations; which is to say that they are typically explained by their histories of selection.” But if “psychological phenotypes” cannot be selected, then the whole EP paradigm crumbles.
This is why EP is not scientific. It cannot make successful predictions of previously unknown facts not used in the construction of the hypothesis, it can only explain what it purports to explain. The claim, therefore, that EP hypotheses are anything but just-so stories is false. One can create good-sounding narratives for any type of trait. But that they “sound good” to the ear, and are “plausible” are not reasons to believe that the story told is true.
Are all hypotheses just-so stories? No. Since a just-so story is an ad hoc hypothesis and a hypothesis is ad hoc if it cannot be independently verified, then a hypothesis that makes predictions which can be independently verified are not just-so stories. There are hypotheses that generate no predictions, ad hoc hypotheses (where the only evidence to believe H is the existence of trait T), and hypotheses that generate novel predictions. EP is the second of these—the only evidence we have to believe H is true is that trait T exists. Independent evidence is a necessary condition of science—that is, the ability of a hypothesis to predict novel evidence is a necessary condition for science. That no EP hypothesis can generate a successful novel prediction is evidence that all EP hypotheses are just-so stories. So for the criticism to be refuted, one would have to name an EP hypothesis that is not a just-so story—that is, (1) name an EP hypothesis, (2) state the prediction, and then (3) state how the prediction follows from the hypothesis.
To be justified in believing hypothesis H in explaining how trait T became fixated in a population there must be independent evidence for this belief. The hypothesis must generate a novel fact which was previously unknown before the hypothesis was constructed. If the hypothesis cannot generate any predictions, or the predictions it makes are continuously falsified, then the hypothesis is to be rejected. No EP hypothesis can generate successful predictions of novel facts and so, the whole EP enterprise is a degenerative research program. The EP paradigm explains and accommodates, but no EP hypothesis generates independently confirmable evidence for any of its hypotheses. Therefore EP is not a scientific program and just-so stories are not scientific.
Mexican drug cartels kill in some of the most heinous ways I’ve ever seen. I won’t link to them here, but a simple Google search will show you the brutal, heinous ways in which they kill rivals and snitches. Why do they kill like this? I have a simple just-so story to explain it: Mexican drug cartels—and similar groups—kill the way they do because they are descended from Aztecs, Maya, and other similar groups who enacted ritual sacrifices to appease their gods.
For example, Munson et al (2014) write:
Among the most noted examples, Aztec human sacrifice stands out for its ritual violence and bloodshed. Performed in the religious precincts of Tenochitlan, ritual sacrifice was a primary instrument for social integration and political legitimacy that intersected with militaristic and marketplace practices, as well as with beliefs about the cosmological order . Although human sacrifice was arguably less common in ancient Maya society, physical evidence indicates that offerings of infant sacrifices and other rituals involving decapitation were important religious practices during the Classic period , .
The Aztecs believed that sacrificial blood-letting appeased their gods who fed on the human blood. They also committed the sacrifices “so that the sun could continue to follow its course” (Garraud and Lefrere, 2014). Their sun god—Uitzilopochtli—was given strength by sacrificial bloodletting, which benfitted the Aztec population “by postponing the end of the world” (Trewby, 2013). The Aztecs also sacrificed children to their rain god Tlaloc (Froese, Gershenson, and Manzanilla, 2014). Further, the Aztec ritual of cutting out still-beating hearts arose from the Maya-Toltec traditions (Ceruti, 2015).
Regarding Aztec sacrifices, Winkelman (2014: 50) writes:
Anthropological efforts to provide a scientific explanation for human sacrifice and cannibalism were initiated by Harner (1970, 1977a, 1977b). Harner pointed out that the emic normalcy of human sacrifice—that it is required by one’s gods and religion—does not alone explain why such beliefs and behaviours were adopted in specific societies. Instead, Harner proposed explanations based upon causal factors found in population pressure. Harner suggested that the magnitude of Aztec human sacrifice and cannibalism was caused by a range of demographic-ecological conditions—protein shortages, population pressure, unfavourable agricultural conditions, seasonal crop failures, the lack of domesticated herbivores, wild game depletion, food scarcity and famine, and environmental circumscription limiting agricultural expansion.
So, along with appeasing and “feeding” their gods, there were sociological reasons for why they committed human sacrifices, and even cannibalism.
When it comes to the Maya (a civilization that independently discovered numerous things while being completely isolated from other civilizations), they had a game called pok-ta-tok—due to the sound the ball made when the players hit it or it fell on the ground. Described in the Popul Vuh (the Ki’iche Maya book that lays out their creation myth), humans and the lords of the Underworld played this game. The Maya Hero Twins Hunahpu and Xbalanque went to the Underworld to do battle against the lords of the Underworld—called Xibalba (see Zaccagnini, 2003: 16-20 for a description of the myth Maya Hero Twins and how it relates to pok-ta-tok and also Myers (2002: 6-13)). See Tokovinine (2002) for more information on pok-ta-tok.
This game was created by the Olmec, a pre-cursor people to the Maya, and later played by the Aztecs. The court was seen as the portal to Xibalba. The Aztec then started playing the game and continued the tradition of murdering the losing team. The rubber ball  weighed around ten pounds, and so it must have caused a lot of bruising and head injuries to players who got hit in the head and body with the ball—as they used their forearms and thighs to pass the ball. (See The Brutal and Bloody History of the Mesoamerican Ball Game, Where Sometimes Loss Was Death.)
According to Zaccagnini (2003: 6) “The ballgame was executed for many reasons, which include social functions, for recreation or the mediation of conflict for instance, the basis for ritualized ceremony, and for political purposes, such as acting as a forum for the opposing groups to compete for political status (Scarborough 1991:141).” Zaccagnini (2003: 7-8) states that the most vied-for participants in the game were captured Maya kings and that they were considered “trophies” of the kings’ people who captured them. Those who were captured had to play the game and they were—essentially—fighting (playing) for their lives. The Maya used the game for a stand-in for war, which is seen in the fact that they played with invading Toltecs in their region (Zaccagnini, 2003: 8).
Death by decapitation occurred to the losers of the game, and, sometimes, skulls of the losing players were used inside of the rubber balls they used to play the game. The Maya word for ball—quiq—literally means “sap” or “blood” which refers to how the rubber ball itself was constructed. Zaccagnini (2003: 11) notes that “The sap can be seen as a metaphoric blood which flows from the tree to give rise to the execution of the ballgame and in this respect, can imply further meaning. The significance of blood in the ballgame, which implies death, is tremendous and this interpretation of the connection of blood and the ball correlated with the notion that the ball is synonymous with the human head is important.” (See both Zaccagnini, (2003) and Tokovinine (2002) for pictures of Maya hieroglyphs which depict winning and losing teams, decapitations, among other things.)
So, the game was won when the ball passed through the hoop which was 20-30 feet in the air, hanging from a wall. These courts, too, were linked to celestial events that occurred (Zaccagnini, 2003). It has been claimed that the ball passing through the hoop was a depiction of the earth passing through the center of the Milky Way.
Avi Loeb notes that “The Mayan culture collected exquisite astronomical data for over a millennium with the false motivation that such data would help predict its societal future. This notion of astrology prevented the advanced Mayan civilization from developing a correct scientific interpretation of the data and led to primitive rituals such as the sacrifice of humans and acts of war in relation to the motions of the Sun and the planets, particulary Venus, on the sky.” The planets and constellations, of course, were also of importance in the Maya society. Šprajc (2018) notes that “Venus was one of the most important celestial bodies”, while also stating:
Human sacrifices were believed necessary for securing rain, agricultural fertility, and a proper functioning of the universe in general. Since the captives obtained in battles were the most common sacrificial victims, the military campaigns were religiously sanctioned, and the Venus-rain-maize associations became involved in sacrificial symbolism and warfare ritual. These ideas became a significant component of political ideology, fostered by rulers who exploited them to satisfy their personal ambitions and secular goals. In sum, the whole conceptual complex surrounding the planet Venus in Mesoamerica can be understood in the light of both observational facts and the specific socio-political context.
The relationship between the ballgame, Venus, and the fertility of the land in regard to the agricultural cycle and Venus is also noted by Šprajc (2018). The Maya were expert astronomers and constantly watched the skies and interpreted certain things that occurred in the cosmos in the context of their beliefs.
I have just described the ritualistic sacrifices of the Maya. This, then, is linked to my just-so story, which I first espoused on Twitter back in July of 2018:
Then in January of this year, white nationalist Angelo John Gage unironically used my just-so story!:
Needless to say, I found it hilarious that it was used unironically. Of course, since Mexicans and other Mesoamericans are descendants of the Aztec, Maya and other Indian groups native to the area, one can make this story “fit with” what we observe today. Going back to the analysis above of the Maya ballgame pok-ta-tok, the Maya were quite obviously brutal in their decapitations of the losing teams of the game. Since they decapitated the losing players, this could be seen as a sort of cultural transmission of certain actions (though I strongly doubt that that is why cartels and similar groups kill in the way they do—the exposition of the just-so story is just a funny joke to me).
In sum, my just-so story for why Mexican drug cartels and similar groups kill in the way they do is, as Smith (2016: 279) notes “always consistent with the [observation] because [it is] selected to be so.” The reasons why the Aztecs, Maya, and other Mesoamerican groups participated in these ritualistic sacrifices are numerous: appeasing gods, for agricultural fertility, to cannibalism and related things. There were various ecological reasons why the Aztecs may have committed human sacrifice, and it was—of course—linked back to the gods they were trying to appease.
The ballgame they played attests to the layout of their societies and how it made their societies function in the context of their beliefs regarding appeasing their numerous gods. When the Spanish landed at Mesoamerica and made first contact with the Maya, it took them nearly two centuries to defeat them—though the Maya population was already withering away due to climate change and other related factors (I will cover this in a future article). Although the Spanish destroyed many—if not most—Maya codices, we can glean important information of their lifestyle and how and why they played their ballgame which ended in the ritualistic sacrifice of the losing team.
One of the weaknesses, in my opinion, to HBD is the focus on the Paleolithic and modern eras while glossing over the major developments in between. For instance, the links made between Paleolithic Western Europe’s Cromagnon Art and Modern Western Europe’s prowess (note the geographical/genetic discontinuity there for those actually informative on such matters).
Africa, having a worst archaeological record due to ideological histories and modern problems, leaves it rather vulnerable to reliance on outdated sources already discussed before on this blog. This lack of mention however isn’t strict.
Eventually updated material will be presented by a future outline of Neolithic to Middle Ages development in West Africa.
A recent example of an erroneous comparison would be in Heiner Rindermann’s Cogntivie Capitalism, pages 129-130. He makes multiple claims on precolonial African development to explained prolonged investment in magical thinking.
- Metallurgy not developed independently.
- No wheel.
- Dinka did not properly used cattle due to large, uneaten, portions left castrated.
- No domesticated animals of indigenous origin despite Europeans animals being just as dangerous, contra Diamond (lists African dogs, cats, antelope, gazelle, and Zebras as potential specimens, mentions European Foxes as an example of a “dangerous” animal to be recently domesticated along with African Antelopes in the Ukraine.
- A late, diffused, Neolithic Revolution 7000 years following that of the Middle East.
- Less complex Middle Age Structure.
- Less complex Cave structures.
Now, technically, much of this falls outside of what would be considered “neolithic”, even in the case of Africa. However, understanding the context of Neolithic development in Africa provides context to each of these points and periods of time by virtue of causality. Thus, they will be responded by archaeological sequence.
Dog domestication, Foxes, and human interaction.
The domestication of dogs occurred when Eurasian Hunter-Gathers intensified megafauna hunting, attracting less aggressive wild dogs to tame around 23k-25k ago. Rindermann’s mention of the fox experiment replicates this idea. Domestication isn’t a matter of breaking the most difficult of animals, it’s using the easiest ones to your advantage.
In this same scope, this needs to be compared to Africa’s case. In regards to behavior they are rarely solitary, so attracting lone individuals is already impractical. The species likewise developed under a different level of competition.
They were probably under as much competition from these predators as the ancestral African wild dogs were under from the guild of super predators on their continent.
What was different, though, is the ancestral wolves never evolved in an enviroment which scavenging from various human species was a constant threat, so they could develop behaviors towards humans that were not always characterized by extreme caution and fear.
Europe in particular shows that carnivore density was lower, and thus advantageous to hominids.
Consequently, the first Homo populations that arrived in Europe at the end of the late Early Pleistocene found mammal communities consisting of a low number of prey species, which accounted for a moderate herbivore biomass, as well as a diverse but not very abundant carnivore guild. This relatively low carnivoran density implies that the hominin-carnivore encounter rate was lower in the European ecosystems than in the coeval East African environments, suggesting that an opportunistic omnivorous hominin would have benefited from a reduced interference from the carnivore guild.
This would be a pattern based off of megafaunal extinction data.
The first hints of abnormal rates of megafaunal loss appear earlier, in the Early Pleistocene in Africa around 1 Mya, where there was a pronounced reduction in African proboscidean diversity (11) and the loss of several carnivore lineages, including sabertooth cats (34), which continued to flourish on other continents. Their extirpation in Africa is likely related to Homo erectus evolution into the carnivore niche space (34, 35), with increased use of fire and an increased component of meat in human diets, possibly associated with the metabolic demands of expanding brain size (36). Although remarkable, these early megafauna extinctions were moderate in strength and speed relative to later extinctions experienced on all other continents and islands, probably because of a longer history in Africa and southern Eurasia of gradual hominid coevolution with other animals.
This fundamental difference in adaptation to human presence and subsequent response is obviously a major detail in in-situ animal domestication.
Another example would be the failure of even colonialists to tame the Zebra.
This will just lead me to my next point. That is, what’s the pay-off?
Pastoralism and Utility
A decent test to understand what fauna in Africa can be utilized would the “experiments” of Ancient Egyptians, who are seen as the Eurasian “exception” to African civilization. Hyenas, and antelope from what I’ve, were kept under custody but overtime didn’t resulted in selected traits. The only domesticated animal in this region would be Donkeys, closer relatives to Zebras.
This brings to light another perspective to the Russian Fox experiments, that is, why have pet foxes not been a trend for Eurasians prior to the 20th century? It can be assumed then that attempts of animals domestication simply where not worth investment in the wake of already domesticated animals, even if one grew up in a society/genetic culture at this time that harnessed the skills.
For instance, a slow herd of Eland can be huddled and domesticated but will it pay off compared to the gains from investing into adapting diffused animals into a new environment? (This will be expanded upon as well into the future).
Elephants are nice for large colonial projects, but unique herding discouraging local diseases that also disrupts population density again effects the utility of large bodied animals. Investing in agriculture and iron proved more successful.
Cats actually domesticated themselves and lacked any real utility prior to feasting on urban pests. In Africa, with highly mobile groups as will be explained later, investment in cats weren’t going to change much. Wild Guineafowl, however, were useful to tame in West Africa and use to eat insects.
As can be seen here, Pastoralism is roughly as old in Africa diffused from the Middle East as compared to Europe. Both lacked independently raised species prior to it and making few innovations in regard to in situ beasts beyond the foundation. (Advancement in plant management preceding developed agriculture, a sort of skill that would parallel dog domestication for husbandry, will be discussed in a future article).
And given how advanced Mesoamericans became without draft animals, as mentioned before, their importance seems to be overplayed from a pure “indigenous” perspective. The role in invention itself ought be questioned as well in what we can actually infer.
Borrowed, so what?
In a thought experiment, lets consider some key details in diffusion. The invention of Animal Domestication or Metallurgy is by no means something to be glossed over as an independent invention. Over-fixating on this however in turn glosses over some other details on successful diffusion.
Why would a presumably lower apt population adopt a cognitively demanding skill, reorient it’s way of society around it, without attributing this change to an internal change of character compared to before? Living in a new type of economy system as a trend it undoubtedly bound to result in a new population in regards to using cognition to exploit resources. This would require contributions to their own to the process.
This applies regards to African Domesticated breeds,
Viewing domestication as an invention also produces a profound lack of curiosity about evolutionary changes in domestic species after their documented first appearances. [……] African domesticates, whether or not from foreign ancestors, have adapted to disease and forage challenges throughout their ranges, reflecting local selective pressures under human management. Adaptations include dwarfing and an associated increase in fecundity, tick resistance, and resistance to the most deleterious effects of several mortal infectious diseases. While the genetics of these traits are not yet fully explored, they reflect the animal side of the close co-evolution between humans and domestic animals in Africa. To fixate upon whether or not cattle were independently domesticated from wild African ancestors, or to dismiss chickens’ swift spread through diverse African environments because they were of Asian origin, ignores the more relevant question of how domestic species adapted to the demands of African environments, and how African people integrated them into their lives.
The same can be said for Metallurgy,
We do not yet knowwhether the seventh/sixth century Phoenician smelt-ing furnace from Toscanos, Spain (illustrated byNiemeyer in MA, p.87, Figure 3) is typical, but it isclearly very different from the oldest known iron smelt-ing technology in sub-Saharan Africa. Almost all pub-lished iron smelting furnaces of the first millennium calBC from Rwanda/Burundi, Buhaya, Nigeria, Niger,Cameroon, Congo, Central African Republic and Ga-bon are slag-pit furnaces, which are so far unknownfrom this or earlier periods in the Middle East or NorthAfrica. Early Phoenician tuyères, which have squareprofiles enclosing two parallel (early) or converging(later) narrow bores are also quite unlike those de-scribed for early sites in sub-Saharan Africa, which arecylindrical with a single and larger bore.
African ironworkers adapted bloomery furnacesto an extraordinary range of iron ores, some of whichcannot be used by modern blast furnaces. In bothnorthern South Africa (Killick & Miller 2014)andinthe Pare mountains of northern Tanzania (Louise Ilespers. comm., 2013) magnetite-ilmenite ores contain-ing up to 25 per cent TiO2(by mass) were smelted.The upper limit for TiO2in iron ore for modernblast furnaces is only 2 per cent by mass (McGan-non 1971). High-titanium iron ores can be smeltedin bloomery furnaces because these operate at lowertemperatures and have less-reducing furnace atmo-spheres than blast furnaces. In the blast furnace tita-nium oxide is partially reduced and makes the slagviscous and hard to drain, but in bloomery furnacesit is not reduced and combines with iron and siliconoxide to make a ﬂuid slag (Killick & Miller 2014). Blastfurnace operators also avoid ores containing morethan a few tenths of a percent of phosphorus or ar-senic, because when these elements are dissolved inthe molten iron, they segregate to grain boundaries oncrystallization, making the solid iron brittle on impact.
Bulls (and rams) are often, but not necessarily, castrated at a
fairly advanced age, probably in part to allow the conformation and characteristics of the animal to become evident before
the decision is made. A castrated steer is called muor buoc, an
entire bull thon (men in general are likened to muor which are
usually handsome animals greatly admired on that account; an
unusually brave, strong or successful man may be called thon,
that is, “bull with testicles”). Dinka do not keep an excess of
thon, usually one per 10 to 40 cows. Stated reasons for the
castration of others are for important esthetic and cultural
reasons, to reduce fighting, for easier control, and to prevent
indiscriminant or repeat breeding of cows in heat (the latter
regarded as detrimental to pregnancy and accurate
Since then, Pearl Millet, Rice, Yams, and Cowpeas have been confirmed to be indigenous crops to the area. This is against hypotheses of others. Multiple studies show late expansion southwards, thus likely linking them to Niger-Kongo speakers. Modern SSA genetics revealed farmer population expansion signals similar to that of Neolithic ancestry in Europeans to their own late date of agriculture in the region as well.
Made multiple remarks on Africa’s “exemplars”, trying to construct a sort of perpetual gap since the Paleolithic by citing Renfew’s Neuroscience, evolution and the sapient paradox: the factuality of value and of the sacred. However, Renfrew doesn’t quite support the comparisons he made and approaches a whole different point.
The discovery of clearly intentional patterning on fragments of red ochre from the Blombos Cave (at ca 70 000 BP) is interesting when discussing the origins of symbolic expression. But it is entirely different in character, and very much simpler than the cave paintings and the small carved sculptures which accompany the Upper Palaeolithic of France and Spain (and further east in Europe) after 40 000 BP.[….]
It is important to remember that what is often termed cave art—the painted caves, the beautifully carved ‘Venus’ figurines—was during the Palaeolithic (i.e. the Pleistocene climatic period) effectively restricted to one developmental trajectory, localized in western Europe. It is true that there are just a few depictions of animals in Africa from that time, and in Australia also. But Pleistocene art was effectively restricted to Franco-Cantabria and its outliers.
It was not until towards the end of the Pleistocene period that, in several parts of the world, major changes are seen (but see Gamble (2007) for a more nuanced view, placing more emphasis upon developments in the Late Palaeolithic). They are associated with the development of sedentism and then of agriculture and sometimes stock rearing. At the risk of falling into the familiar ‘revolutionary’ cliché, it may be appropriate to speak of the Sedentary Revolution (Wilson 1988; Renfrew 2007a, ch. 7).[….] Although the details are different in each area, we see a kind of sedentary revolution taking place in western Asia, in southern China, in the Yellow River area of northern China, in Mesoamerica, and coastal Peru, in New Guinea, and in a different way in Japan (Scarre 2005).
Weil (2014) paints a picture of African development in 1500, both relative to the rest of the world and heterogeneity within the continent itself, using as his indicators population density, urbanization, technological advancement, and political development. Ignoring North Africa, which was generally part of the Mediterranean world, the highest levels of development by many indicators are found in Ethiopia and in the broad swathe of West African countries running from Cameroon and Nigeria eastward along the coast and the Niger river. In this latter region, the available measures show a level of development just below or sometimes equal to that in the belt of Eurasia running from Japan and China, through South Asia and the Middle East, into Europe. Depending on the index used, West Africa was above or below the level of development in the Northern Andes and Mexico. Much of the rest of Africa was at a significantly lower level of development, although still more advanced than the bulk of the Americas or Australia.