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AFAIK as IQ is deliberately intended to be normalized, the gap is exactly the same 85 to 100 as 100 to 115, and if you think that those two aren't the same, you are also inherently saying that IQ is the wrong tool for the job. That's not even getting into the whole "what benchmark do we set 100 at", do we update it year to year or try to peg it to some historical benchmark (though this is not necessarily fatal to IQ as a metric in the same way the first is, it does present a question that must be addressed when using IQ).
Simply using IQ necessitates that you grapple with these things. That's the nature of using numbers to describe something human. You, the invoker of IQ, need to prove the numbers work as numbers and aren't better being left as philosophical concepts or practical examples, or point to something well established that does. The simple, self-evident fact that IQ is fit to a normal curve and you yourself don't seem to believe that a symmetric 15 point gap is equal across the domain is in and of itself a tacit admission that IQ is the wrong tool. Are you familiar with the statistical notions of how an assigned number scale can be nominal, or ordinal, or interval, or ratio? It's not a perfect paradigm by any means, but it's one you must grapple with at least on some level, and happens to be incredibly relevant here in this case. See also OP's initial claim that the distribution has a weird asymmetric tail, also evidence (though more mild) against using IQ as the correct tool. Similarly, the fact that you dodge the 100-center question, which is a fundamentally important question to the use of IQ, is not acceptable.
I mean, I get the whole all models are wrong but some are useful, but these are just the very basics, the fundamentals, they are not nitpicks. An example of something that at least does attempt to address these issues and mostly succeeds is the Likert scale. You might be familiar with it. It's the classic 5 or 7 point scale in response to a question, with "strongly agree" and "slightly agree" and "not sure" and disagree options. There's a natural zero, and at least psychologists attempt to say that the distance between each point is "equal". I know forced normalization distorts this equal-distance formulation slightly, in terms of the math, but two properties that persist across the transformation are the aforementioned symmetry of responses, and also the center point of responses. These two decisions are non-negotiable and mandatory to make and cannot be hand-waved away. They are inherent to the math and the use of a numerical model.
Funny, yes you do. That's literally how using statistics and math to evaluate social problems works. You can't just slap a number system onto something and call it good. That's Stats 101. Even some more advanced numerical analysis can sometimes reach the literal opposite conclusion if done or designed incorrectly. On that same note, explanatory power is also insufficient if your categories are fundamentally flawed. Why? Because what you want to do with your model matters. Even if you are trying to be predictive vs just descriptive of the past changes some potentially vital assumptions. It's, mathematically, just wild to vigorously defend arbitrary categories that have demonstrated flawed mechanisms and so-so generalizability just because it happens to kind of work as an explanation. That's not rigor, it's agenda, quite frankly. And we are talking about IQ as a tool, and you defend it based on... some non-sequiter argument about how people in charge are ignoring it or something?
You can hand-wave away the fuzzy boundary problem all you want in an observational sense, but it actually matters a lot (this is underselling it, it's literally foundational) IF you want to use IQ as a tool of making actual proscriptive, "do this and not this" kind of arguments based on what it tells you. Such as exhibit A: do we continue, change, intensify, stop, etc. "racial uplift" efforts?
I additionally think, as a factual matter, claiming that all efforts to help Black people in the last 50-60 years have failed is a pretty wild and weakly supported take. As far as I know the proportional wealth gap for example stalled out more in the 1980s or so, so 45 years, but your language seems to imply this is a more longstanding. Perhaps a more useful question I have for you then would be, at what point historically do you think things presumably got 'fair enough' that you can say "well we tried and failed so it must be their fault not ours"? I assume that is your actual argument, yes? That we as a society tried and failed at "racial uplift" and no use throwing good money after bad, that kind of thing?
My grandpa told me a story last year about how while he was growing up his dad decided to quit being a realtor because he was so mad at the realtor's association refusing to allow him to sell a house to a nice, well-off Asian couple the house they wanted because of explicit redlining. He was willing to go to bat for them and fight it and they just gave up. Redlining for example only became technically illegal in 1968 and sure as hell didn't magically stop overnight. You know, the main way Americans build generational wealth. Sound familiar? Don't get me wrong, there's sure a limit to assistance, and personally I favor a more, well not entirely race-blind approach, but certainly a more targeted approach that mainly focuses on wealth as it is rather than other groupings.
Not that I disagree, just want to make sure we're on the same page: the way I see it you just doused every single social science with gasoline, and are standing above them with a lit match in your hand. I don't mind getting rid of the HBD hypothesis this way, but I want to make sure that when the whole thing is done, you're not going to try and tell me that that little pile of ashes where "implicit bias" used to stand, is still a valid structure.
Actually a great, great question. In one sense, you are right that social sciences do in fact have some potential, deep-seated issues. Education is particularly thorny among them. As a field, they have figured out some methods to cope, which I will say sadly not all who undertake research fully understand, though the best do. The basic and relevant point here is that for a "measure" to be accepted in the social sciences, there are a few helpful traits we might look for. You might find the wikipedia page on psychological statistics and its cross-references including test validity interesting.
To steal a reddit ELI5:
Most of my arguments here in this thread have to do with some variation of validity. In other words, people are taking a tool and using it for something that it is not designed to do, and in fact incompatible with that use. Unlike physical reality, where you could use a hoe instead of a shovel to dig a hole and it would just be annoying and take more time, in the math realm when you do try to do something a tool fundamentally cannot do, the risks are higher and things not working as expected are also higher. You might, for example, use a shovel that only digs up dirt with the intention to create a hole but in fact leaves clay and gravel behind and the job only half-done, because it turns out the shovel literally only picked up dirt. I hope that's an okay analogy, there's probably a better one. Researchers themselves often grapple with these questions all the time (hopefully literally all of the time, but you know how modern science has its flaws too). To put a simple example, your bread and butter linear regression assumes, as a core assumption, that you've selected all the variables that matter. If you left something out, you get well, not "bad" results exactly, but ones that will possibly not help you accomplish what you want to accomplish, and at worst might send you the wrong direction entirely. See: multicollinearity, confounders, and test design in multiple linear regression for more resources there.
That's not to say social sciences are the worst sciences and are all doomed. If you read many actual papers, it's not uncommon for a paper to specifically examine these arguments in detail. That's why I bring up the Likert scale, which I still do have a handful of issues with, but is relatively common and well-established and for which advances and self-questioning continues. See, for example this paper. IQ by contrast has a much more difficult history and variation in both implementation and interpretation, along with a tendency for misunderstandings. In my personal, subjective opinion, the actual worst field of science is much of food research, but that's a thread for another day.
All the above basically concerns the fundamental misunderstandings about IQ. As evidenced by the many downvotes my posts have accumulated, sadly such fundamental misunderstandings continue. "Why don't I notice a 85 to 100 the same as 100 to 115 intelligence difference" as a question indicates that the question is faulty in at least one way, not that they have somehow discovered some deep principle of life. As to my allusion to fuzzy categories being similarly relevant and something we can't ignore, that's more of a fundamental psychometric and math question, along the lines of "how to lie with statistics". My points there were not questioned so I feel no need to go into detail there.
But that's just the thing, I'm pretty sure they are if you insist on a standard high enough to reject IQ.
Economics is notorious for sacrificing resemblance to reality for the ability to model something mathematically. Accuracy is their only justification for doing so, except you're not supposed to look at it too closely either, because their accuracy sucks. When you point that out their only comeback is "well, it's the best we have".
Psychology isn't as obsessed with mathematical modeling, but they work with variables that are neither easily quantifiable, nor directly measurable. Yes, as you point out they came up with some ways to cope with that, but that doesn't change the fact that it's cope. The fact that there's an objectively right answer to an IQ test will always give you a leg up over "agree / disagree" type tests.
And don't get me started about sociology, somehow it manages to combine the worst of both worlds. How can you tell me with a straight face that I should take their arguments about crime, poverty, education, etc., when you want me to reject one of the strongest effects they discovered based on an esoteric argument about epistemology? These dudes made an entire test supposedly showing you're a secret racist, and wrote a ton of papers around it, and are now trying to say "IQ tests only measure performance on IQ tests"? That's absurd.
I meant it when I painted that visual with you holding the match. I'm fine with you dropping it, and setting the whole thing ablaze, but you're doing exactly what I was expected - pretending that the far less rigorous parts of social sciences will be the ones that survive this.
Isn't that just a Russell Conjugation? I'm advancing as self-questioning continues - you have a difficult history and variation in implementation and interpretation.
I beg your pardon - what?!
You're going to tell me that the only thing we can be sure IQ tests measure is IQ, but down votes measure misunderstanding of IQ?
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