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I wouldn't expect a marked difference in the quality of non-controversial research whether funded by a national granting agency or private industry. That said, I'm not an expert on the topic, either.

As for "controversial" science in the sense of "any science that business/industry doesn't like," the pattern is quite similar whether we're talking about lead, asbestos, climate change, et cetera:

Find a couple of researchers who will play ball to say your product is safe despite all the evidence to the contrary. Point to this repeatedly any time the topic comes up. Ignore the mountain of evidence that says you're wrong at all costs, and undermine it any way you can. Buy as many politicians as you can to try and prevent regulation.

As for vaping, I'd need to see some examples of bad academic research. I'm not sure you can blame the scientists for the consequences of poorly-regulated businesses. They can only test the products that they're given and tell you whether they're safe. They can't tell you if a manufacturer is going to change the oil they use or decide to include heavy metals.

That's up to the regulators to prevent.

Without a Google Scholar search, I'd just point to how industry dealt with things like asbestos, lead, tobacco, and greenhouse gas emissions.

Science definitely needs scrutiny, debate, and evidence. That said, whenever someone's loudly proclaiming that an entire field is corrupt and incorrect, it should raise suspicions.

What's more likely: that thousands of (generally underpaid) researchers in hundreds of competing labs worldwide are all in cahoots, or that a few dissenting voices are funded by industry to argue that point of view?

Hi David,

I agree that pitting the "top priority" group against the "no resources" group in a correlation is an odd way of approaching the data. I was trained not to create dichotomous variables unless advanced statistics tell us that the data is, indeed, dichotomous. Doing so gets rid of variance that may well be useful. The current analysis goes even further by excluding large numbers of people, as you noted.

I would be interested in seeing non-parametric correlations that can deal with ordinal data (e.g, Spearman's) used on the full sample. I'm guessing the story may be different.

From your article on the male variability hypothesis:

Recent studies indicate that greater male variability in mathematics persists in the U.S., although the ratio of boys to girls at the top end of the distribution is reversed in some specific immigrant groups.


These results have been replicated and expanded in a 2019 meta-analytical extension [...], which found that policies leading to greater female participation in the workforce tended to increase female variability and, therefore, decrease the variability gap.

These sound like arguments for environment to me, which would mean that "Frank" is still likely correct and "Grace" is misinformed on what the patriarchy is and how it works.

Thanks for the interesting article, Jamie!

I'd be inclined to think that it's the second explanation offered in the discussion that's driving the effect--naturalness bias happens in a lot of areas, and the AFFT texts were pretty lab/tech-heavy. It would be easy to test whether the first mechanism you proposed is correct by asking people whether they think farming will be replaced with these technologies. Future studies could also present the AFFTs in a less science-heavy way to see if the effect is attenuated. :)

Yeah, the more I looked into the guy, the more his critique fit into context. His work finds a home on some websites of questionable repute. haha

And as you point out, the people you meet in academia generally don't tend to be as he's characterized them.

I would be willing to bet that he has a financial motive to argue against the prevailing scientific consensus, just as we see in other instances where facts turn out to be inconvenient for corporate interests.

Thanks for your feedback.

I was trying to figure out why the author would be so, so critical of scientific research.

I would say he was downright uncharitable, in fact.

It turns out that he's also argued quite strongly that high levels of refined sugar in people's diets are no problem: e.g., https://www.sciencedaily.com/releases/2018/08/180827110730.htm

To do so, he has to throw aside mountains of scientific research. I would say his attack above is a necessary part of that effort.

So while I am concerned about inefficiencies in academic work and the waste of taxpayer dollars, I'm much more worried about the effects of corporate money on research.

I wouldn't say that there are no inefficiencies in academia. There are inefficiencies in every line of work.

I would say that on the whole, a lot of great still work gets done.

I definitely wouldn't say that academia is rife with "incompetence in concert with a lack of accountability."

Sure, there are people with Ph.Ds who are not strong researchers. There are lot of them who are, though.

We may just disagree on the ratio of the two groups based on our own experiences.

I would argue the article is extremely pessimistic.

Yes, funds sometimes get misallocated or are given to people who have committed fraud.

More often, they go to hard-working researchers who really don't make that much at all...people who hate fake or misleading scientific claims more than the average taxpayer.

And yes, there's a replication crisis...that people are aware of working to address.

In short, I think the author uses an extremely broad brush: "The widespread inability of publicly funded researchers to generate valid, reproducible findings is a testament to the failure of universities to properly train scientists and instill intellectual and methodologic rigor."

And yet, scientific breakthroughs happen all the time and the world is better for it.

In short, maybe the author is burnt out or has only ever worked with poor colleagues? Or hasn't been funded in a while?

Most of the researchers I've met are honest and hard-working and doing their best to get it right, even in the face of challenging questions and strained resources.

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