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.
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.