This seems unduly pessimistic to me. The whole interesting thing about g is that it’s easy to measure and correlates with tons of stuff. I’m not convinced there’s any magic about FSIQ compared to shoddier tests. There might be important stuff that FSIQ doesn’t measure very well that we’d ideally like to select/edit for, but using FSIQ is much better than nothing. Likewise, using a poor man’s IQ proxy seems much better than nothing.
This may have missed your point, you seem more concerned about selecting for unwanted covariates than ‘missing things’, which is reasonable. I might remake the same argument by suspecting that FSIQ probably has some weird covariates too—but that seems weaker. E.g. if a proxy measure correlates with FSIQ at .7, then the ‘other stuff’ (insofar as it is heritable variation and not just noise) will also correlate with the proxy at .7, and so by selecting on this measure you’d be selecting quite strongly for the ‘other stuff’, which, yeah, isn’t great. FSIQ, insofar as it had any weird unwanted covariates, would probably much less correlated with them than .7
This may have missed your point, you seem more concerned about selecting for unwanted covariates than ‘missing things’, which is reasonable. I might remake the same argument by suspecting that FSIQ probably has some weird covariates too—but that seems weaker. E.g. if a proxy measure correlates with FSIQ at .7, then the ‘other stuff’ (insofar as it is heritable variation and not just noise) will also correlate with the proxy at .7, and so by selecting on this measure you’d be selecting quite strongly for the ‘other stuff’, which, yeah, isn’t great. FSIQ, insofar as it had any weird unwanted covariates, would probably much less correlated with them than .7