[ExI] IQ and beauty
pharos at gmail.com
Fri Oct 9 08:50:54 UTC 2015
On 9 October 2015 at 09:16, rex wrote:
> Current thought is that the large majority of species that have ever
> existed are extinct, but that's irrelevant to my observation that a
> "just so" argument that exaggerated traits may progress to extinction
> does not imply that they will frequently do so. It's similar to
> group selection: it seems plausible and was accepted without question
> for decades. Eventually, the conditions necessary for group selection
> were elucidated and found to be be so restrictive that group selection
> almost never happens in the wild.
> I suspect extinctions due to runaway exaggerated traits are also
> rare. So far, not a single example has been presented. A quick search
> didn't turn up any examples, but it did reveal an example where sexual
> dimorphism "improved the carrying capacity of the environment, and thus
> presumably population viability."
There is currently great concern about the amount of published
research that cannot reproduce results when retested.
Nature has published a new article.
The issue goes well beyond cases of fraud. Earlier this year, a large
project that attempted to replicate 100 psychology studies managed to
reproduce only slightly more than one-third. In 2012, researchers at
biotechnology firm Amgen in Thousand Oaks, California, reported that
they could replicate only 6 out of 53 landmark studies in oncology and
haematology. And in 2009, Ioannidis and his colleagues described how
they had been able to fully reproduce only 2 out of 18
microarray-based gene-expression studies.
Evolutionary theory has been one of the worst disciplines for the
'Just so' story fallacy.
As data-analysis results are being compiled and interpreted,
researchers often fall prey to just-so storytelling — a fallacy named
after the Rudyard Kipling tales that give whimsical explanations for
things such as how the leopard got its spots. The problem is that
post-hoc stories can be concocted to justify anything and everything —
and so end up truly explaining nothing. Baggerly says that he has seen
such stories in genetics studies, when an analysis implicates a huge
number of genes in a particular trait or outcome. “It's akin to a
Rorschach test,” he said at the bioinformatics conference. Researchers
will find a story, he says, “whether it's there or not.
A good story is not evidence.
Even when evidence is provided, you need to get it checked by groups
that don't believe the good story. Because the claimed evidence may
not really be there either.
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