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I'm presenting using heritability as an initial toy problem area for exploring building PPL/agent-based scenario models. I havent yet got to the point of buildi

I'm presenting using heritability as an initial toy problem area for exploring building PPL/agent-based scenario models. I havent yet got to the point of building the model out, but it's clear very early on that any observational distribution can be reproduced. I will have a more refined view when I've done that. re Sasha Gusev: disease, to some degree, can be studied with these methods if you have interventional evidence of a genetic cause. But since all non-genetic factors are almost obviously mutually interacting, with "compound interest", no explanatory model can be fit. eg., suppose your personality is entirely genetic: then why variation? Well, because of gene-environment interactions. eg., suppose your personality is 0% genetic: when why genetic co-variation? Because people's genes covary geographically, and due to the trait selection of partners... ie., families live in the same geography, and people of similar traits breed together. Why (very weak) correlation with genetic similarity? Because "compound interest" applies to the interacting factors, so even extremely weak geographical selection will compound. It is entirely unclear to me how you're meant to discriminate between teh infinite family of models on either side. Certainly, with correlation coefficients of ~.2, you're talking about pseudoscience either way. The causes would have to be extremely linear for such trivial correlations to mean anything at all, and they certainly arent.

whimsicalism 2y ago
I understand your objection and of course you can't just naively get causality from observational GWAS. That is true. Your rhetoric does not match the strength of your scientific objection. Let's imagine the worst case - these studies are absolutely useless for indicating any causality whatsoever. Even then, they are still extremely useful because they can explain away lots of environmental variation in a behavior of interest and increase the power of studies of human behavior. That's if they are purely non-causal and genetics actually has no impact whatsoever on behavior or the brain (a mechanistic stretch). Sorry, but this simply does not match your rhetoric of 'pseudoscience' and closing entire fields down. > Certainly, with correlation coefficients of ~.2, you're talking about pseudoscience either way. The causes would have to be extremely linear for such trivial correlations to mean anything at all, and they certainly arent. I simply don't agree, but I can tell you won't be convinced on this point.
- mjburgess 2y ago
  I'm certainly open to speculative generative (, explanatory) modelling of human populations to see what distributions of variation can be reproduced (indeed, that's what i'm doing). I'm less open to the reverse process: starting with observational distributions and then just fitting whatever model suits one's prejudices. There's a cost to the latter when we know, a priori, that the "scientists" prior belief about what models to use are the most significant factor determining the conclusions of the paper; and that we know that the data is vastly too weak to distinguish between priors. Compare the same problem in finance: this sort of linear easy-predictability thinking was a major factor in the financial crash of 2008; and it's something now widely seen with great suspicion amongst the financial industry.. who are well aware that "crisis" and "saftey" are both consistent with observational data. I would argue that we live in a world of "pseudo-scientific social science disasters", the entire industry of measuring people and classifying them is one big Science Crisis whose effects practitioners do not care about because they aren't the ones being fired and loosing all their money (or have rigged these measures to benefit themselves). Against this backdrop of, what ought be, researchers "going bust", universities collapsing, and research paper stock prices near zero -- i'd claim "pseudoscience" is a polite word. Esp. when those who should be long bust are still publishing papers immune from their effects on society.
- froh 2y ago
  > Your rhetoric does not match the strength of your scientific objection. thank you for this way of putting it. made my day.

whimsicalism 2y ago

I understand your objection and of course you can't just naively get causality from observational GWAS. That is true. Your rhetoric does not match the strength of your scientific objection. Let's imagine the worst case - these studies are absolutely useless for indicating any causality whatsoever. Even then, they are still extremely useful because they can explain away lots of environmental variation in a behavior of interest and increase the power of studies of human behavior. That's if they are purely non-causal and genetics actually has no impact whatsoever on behavior or the brain (a mechanistic stretch). Sorry, but this simply does not match your rhetoric of 'pseudoscience' and closing entire fields down. > Certainly, with correlation coefficients of ~.2, you're talking about pseudoscience either way. The causes would have to be extremely linear for such trivial correlations to mean anything at all, and they certainly arent. I simply don't agree, but I can tell you won't be convinced on this point.

mjburgess 2y ago
I'm certainly open to speculative generative (, explanatory) modelling of human populations to see what distributions of variation can be reproduced (indeed, that's what i'm doing). I'm less open to the reverse process: starting with observational distributions and then just fitting whatever model suits one's prejudices. There's a cost to the latter when we know, a priori, that the "scientists" prior belief about what models to use are the most significant factor determining the conclusions of the paper; and that we know that the data is vastly too weak to distinguish between priors. Compare the same problem in finance: this sort of linear easy-predictability thinking was a major factor in the financial crash of 2008; and it's something now widely seen with great suspicion amongst the financial industry.. who are well aware that "crisis" and "saftey" are both consistent with observational data. I would argue that we live in a world of "pseudo-scientific social science disasters", the entire industry of measuring people and classifying them is one big Science Crisis whose effects practitioners do not care about because they aren't the ones being fired and loosing all their money (or have rigged these measures to benefit themselves). Against this backdrop of, what ought be, researchers "going bust", universities collapsing, and research paper stock prices near zero -- i'd claim "pseudoscience" is a polite word. Esp. when those who should be long bust are still publishing papers immune from their effects on society.
froh 2y ago
> Your rhetoric does not match the strength of your scientific objection. thank you for this way of putting it. made my day.