Why didn't the disaster convince everyone that nuclear power is unsafe? Indeed, some saw the fact that there were no confirmed deaths attributable to the disaster as proof that nuclear power is safe, while others saw the whole event as confirmation that nuclear power is a disaster waiting to happen. According to The Inquiry, a nation's history has a lot to do with how it reads the facts. Germany's history is one of division and war, and nuclear power associated with bombs, but French researchers and engineers have long been involved in the development of nuclear power, so there's a certain amount of national pride in this form of energy. It may not be an unrelated point that therefore many people in France have vested interests in nuclear power. Still, same picture, different reading of it.
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| Cattenom nuclear power plant, France; Wikipedia |
Reading ability is entirely genetic
And, I was alerted to yet another paper reporting that intelligence is genetic (h/t Mel Bartley); this time it's reading ability, for which no environmental effect was found (or acknowledged). (This idea of little to no environmental effect is an interesting one, though, given that the authors, who are Dutch, report that heritability of dyslexia and reading fluency is higher among Dutch readers -- 80% compared with 45-70% elsewhere -- they suggest because Dutch orthography is simpler than that of English. This sounds like an environmental effect to me.)
The authors assessed reading scores for twins, parents and siblings, and used these to evaluate additive and non-additive genetic effects, and family environmental factors. As far as I can tell, subjects were asked to read aloud from a list of Dutch words, and the number they read correctly within a minute constituted their score. And again, as far as I can tell, they did not test for nor select for children or parents with dyslexia, but they seem to be reporting results as though they apply to dyslexia.
The authors report a high correlation in reading ability between monozygotic twins, a lower correlation between dizygotic twins, and between twins and siblings, and a higher correlation between spouses, which to the authors is evidence of assortative mating (choice of mate based on traits associated with reading ability). They conclude:
Such a pattern of correlation among family members is consistent with a model that attributes resemblance to additive genetic factors, these are the factors that contribute to resemblance among all biological relatives, and to non-additive genetic factors. Non-additive genetic factors, or genetic dominance, contributes to resemblance among siblings, but not to the resemblance of parents and offspring. Maximum likelihood estimates for the additive genetic factors were 28% (CI: 0–43%) and for dominant genetic factors 36% (CI: 18–65%), resulting in a broad-sense heritability estimate of 64%. The remainder of the variance is attributed to unique environmental factors and measurement error (35%, CI: 29–44%).Despite this evidence for environmental effect (right?), the authors conclude, "Our results suggest that the precursors for reading disability observed in familial risk studies are caused by genetic, not environ- mental, liability from parents. That is, having family risk does not reflect experiencing a less favorable literacy environment, but receiving less favorable genetic variants."
The ideas about additivity are technical and subtle. Dominant effects, that is, non-additive interactions among alleles within a gene in the diploid copies of an individual, are not inherited as additive ones are (if you are a Dd and that determines your trait, only one of those alleles, and hence not enough to determine the trait, is transmitted to any of your offspring). Likewise, interactions (between loci), called epistasis, is also not directly transmitted.
There are many practical as well as political reasons to believe that interactions can be ignored. In a practical sense, even multiple 2-way interactions make impossible sample size and structure demands. But in a political sense, additive effects mean that traits can be reliably predicted from genotype data (meaning, even at birth): you estimate the effects of each allele at each place in the genome, and add them to get the predicted phenotype. There is money to be made by that, so to speak. But it doesn't really work with complex interactions. Strong incentives, indeed, to report additive effects and very understandable!
Secondly, all these various effects are estimated from samples, not derived from basic theory about molecular-level physiology, and often they are hardly informed by the latter at all. This means that replication is not to be expected in any rigorous sense. For example, dominance is estimated by the deviation of average traits in AA, Aa, and aa individuals from being in 0, 1, 2 proportions if (say) the 'a' allele contributed 1-unit of trait measure. Dominance deviations are thoroughly sample-dependent. It is not easy to interpret those results when samples cannot be replicated (the concepts are very useful in agricultural and experimental breeding contexts, but far less so in natural human populations). And this conveniently overlooks the environmental effects.
This study is of a small sample, especially since for many traits it now seems de rigueur to have samples of hundreds of thousands to get reliable mapping results, not to mention a confusingly defined trait, so it's difficult, at least for me, to make sense of the results. In theory, it wouldn't be terribly surprising to find a genetic component to risk of reading disability, but it would be surprising, particularly since disability is defined only by test score in this study, if none of that ability was substantially affected by environment. In the extreme, if a child hasn't been to school or otherwise learned to read, that inability would be largely determined by environmental factors, right? Even if an entire family couldn't read, it's not possible to know whether it's because no one ever had the chance to learn, or they share some genetic risk allele.
In people, unlike in other animals, assortative mating has a huge cultural component, so, again, it wouldn't be surprising if two illiterate adults married, or if they then had no books in the house, and didn't teach their children that reading was valuable. But this doesn't mean either reading or their mate-choice necessarily has any genetic component.
So, again, same data, different interpretations
But why? Indeed, what makes some Americans hear Donald Trump and resonate with his message, while others cringe? Why do we need 9 Supreme Court justices if the idea is that evidence for determination of the constitutionality of a law is to be found in the Constitution? Why doesn't just one justice suffice? And, why do they look at the same evidence and reliably and predictably vote along political lines?
Or, more uncomfortably for scientists, why did some people consider it good news when it was announced that only 34% of replicated psychology experiments agreed with the original results, while others considered this unfortunate? Again, same facts, different conclusions.
Why do our beliefs determine our opinions, even in science, which is supposed to be based on the scientific method, and sober, unbiased assessment of the data? Statistics, like anything, can be manipulated, but done properly they at least don't lie. But, is IQ real or isn't it? Are behavioral traits genetically determined or aren't they? Have genome wide association studies been successful or not?
As Ken often writes, much of how we view these things is certainly determined by vested interest and careerism, not to mention the emotional positions we inevitably take on human affairs. If your lab spends its time and money on GWAS, you're more likely to see them as successful. That's undeniable if you are candid. But, I think it's more than that. I think we're too often prisoners of induction, based on our experience, training, predilections of what observations we make or count as significant; our conclusions are often underdetermined, but we don't know it. Underdetermined systems are those that are accounted for with not enough evidence. It's the all-swans-are-white problem; they're all white until we see a black one. At which point we either conclude we were wrong, or give the black swan a different species name. But, we never know if or when we're going to see a black one. Or a purple one.
John Snow determined to his own satisfaction during the cholera epidemic in London in 1854 that cholera was transmitted by a contagion in the water. But in fact he didn't prove it. The miasmatists, who believed cholera was caused by bad air, had stacks of evidence of their own -- e.g., infection was more common in smoggy, smelly cities, and in fact in the dirtier sections of cities. But both Snow and the miasmatists had only circumstantial evidence, correlations, not enough data to definitively prove their were right. Both arguments were underdetermined. As it happened, John Snow was right, but that wasn't to be widely known for another few decades when vibrio cholerae was identified under Robert Koch's microscope.
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| "The scent lies strong here; do you see anything?"; Wikipedia |
Both sides strongly (emotionally!) believed they were right, believed they had the evidence to support their argument. They weren't cherry-picking the data to better support their side, they were looking at the same data and drawing different conclusions. They based their conclusions on the data they had, but they had no idea it wasn't enough.
But it's not just that, either. It's also that we're predisposed by our beliefs to form our opinions. And that's when we're likely to cherry pick the evidence that supports our beliefs. Who's right about immigrants to the US, Donald Trump or Bernie Sanders? Who's right about whether corporations are people or not? Who's right about genetically modified organisms? Or climate change? Who's right about behavior and genetic determinism?
And it's even more than that! If genetics and evolutionary biology have taught us anything, they've taught us about complexity. Even simple traits turn out to be complex. There are multiple pathways to most traits, most traits are due to interacting polygenes and environmental factors, and so on. Simple explanations are less likely to be correct than explanations that acknowledge complexity, and that's because evolution doesn't follow rules, except that what works works, and to an important degree that's what is here to be examined today.
Simplistic explanations are probably wrong. But they are so appealing.
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