Scientists, are not quite like explorers, just venturing off in direction and see what they find.
They have interests, that align with funding, which aligns with actionable data. And they follow them.
So who would even do such research? The best you could find is some meaningless difference in mean scores that is likely swamped by environmental factors. And the fact that "race" is far fuzzier than our intuition leads us to think (it turns out we're very good at applying racial labels to people, that genetically are simply not so clear especially at the edges of categories).^*
So it's hard to fund research with no purpose, that scientists aren't particularly interested in conducting. Instead [GWAS](https://en.wikipedia.org/wiki/Genome-wide_association_study) studies answer more useful questions that are actionable (you can do a genetic test and calculate a risk in principle).
* I'll clarify this statement because it's a common misconception. There are clearly genetic differences between racial groups. But they are complex statsical genetics that are impossible to cleanly pin down without large levels of miscategorization. And GWAS studies are answering the question which genes are associated with cognition and disorder.
> So who would even do such research? The best you could find is some meaningless difference in mean scores that is likely swamped by environmental factors.
Yes, I too find it easy to avoid doing research when I assume what that research is going to find out ahead of the time.
The research has already been done historically without convincing results. That's why they want NIH large dataset (you need large dataset to find a small effect size).
But NIH understably will not share a dataset that the contributors wouldn't want to used in this way.
But if you're a researcher in this domain just go get your own dataset. You'll have to tell the potential contributors you will allow research that might stigmatize them.
Good luck with recruitment.
It you don't think you could recruit for that study because participants would find it objectionable then you can't demand access to NIH dataset.
> So it's hard to fund research with no purpose, that scientists aren't particularly interested in conducting.
But that's not what happened. They didn't just decline to fund such research. The NIH banned it on their data set even if you had your own funding. You don't explicitly ban things that people are not interested in doing. e.g. the NIH doesn't ban using the data set to perform research on astrology. If I want to do research on the difference between Libras and Scorpios and I come up with the money, the policy is "OK, you do you."
I read the NIH policy and it seems quite reasonable to me.
The rule usually applied to datasets with broad consent is the surprise principle. Even if you have consent if the person is subsequently surprised by how it was used it's not informed consent.
To put it simply, how do we get samples from marginalised groups if we plan to allow to use that data for them to be marginalised?
If the NIH didn't actively oppose it how can they expect to get more participants ?
But the article is also about groups engaging in academic dishonesty to bypass NIH policy. It really makes me question their motives and that they aren't simply scientists seeking truth.
I was responding to the statement from the article that it had explicitly banned anything to do with race, ancestry, or ethnicity. I have not read the full policy.
> To put it simply, how do we get samples from marginalised groups if we plan to allow to use that data for them to be marginalised?
You said in your previous comment above that these categories aren't useful anyway, which brings up some questions:
1. If that is the NIH's opinion, then why did they label the data with those categories?
2. If these categories are actually not useful, then why should I care if the dataset isn't balanced between members of those categories?
> But the article is also about groups engaging in academic dishonesty to bypass NIH policy. It really makes me question their motives and that they aren't simply scientists seeking truth.
To the contrary, I consider any such restriction on the topic of research to be fundamentally unscientific and I mistrust any scientist who feels an ethical obligation to comply with such political censorship.
It's not restricted. NIH won't allow you to use the datasets they control for it. It is practically and pragmatically reasonable for them to do that. It's also ethically sound to not let the data subjects data be used for something they wouldn't want as the data controller.
If a scientist wants to do the research then they can pursue it and find a journal to publish it in. The reputable journals are unlikely to find it of interest unless it was a huge effect size. But we know any effect size must be tiny hence the need for a huge dataset.
They'd have to take samples and basically tell the person the intension was to check if some races were genetically inferior let's see how well they do with recruitment. I wouldn't give a sample.
Or just do a GWAS study and then develop metrics for estimating risk for individuals which can make use of ethnicity.
They have interests, that align with funding, which aligns with actionable data. And they follow them.
So who would even do such research? The best you could find is some meaningless difference in mean scores that is likely swamped by environmental factors. And the fact that "race" is far fuzzier than our intuition leads us to think (it turns out we're very good at applying racial labels to people, that genetically are simply not so clear especially at the edges of categories).^*
So it's hard to fund research with no purpose, that scientists aren't particularly interested in conducting. Instead [GWAS](https://en.wikipedia.org/wiki/Genome-wide_association_study) studies answer more useful questions that are actionable (you can do a genetic test and calculate a risk in principle).
* I'll clarify this statement because it's a common misconception. There are clearly genetic differences between racial groups. But they are complex statsical genetics that are impossible to cleanly pin down without large levels of miscategorization. And GWAS studies are answering the question which genes are associated with cognition and disorder.