Population Matters - thursday 2013-03-07 0006 last modified 2013-03-07 1529
Categories: Daily Grind
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Two fascinating pieces: one from a couple years ago on the hyper-specialization and normalization of laboratory mice and its detrimental effects on research, one on the unintended consequences of American social scientists studying only other Americans and its distorting effect on our understanding of humanity as a whole.

As both pieces point out, it matters a great deal which population is used in a study; the assumption of broad applicability may not be well founded. If you ever heard the idea that a hyper-low calorie diet might lead to longer life, that was a sound conclusion - if your population was lab rats. If your population was wild rats, it would likely be meaningless; lab rats are so far above the norm for their species in calorie consumption - eating whatever they want, living in a cage - that reducing calories to a species-normal level was bound to lead to healthier and longer lives. The studies are legitimate science, but they missed something foundational in their population that upsets the conclusions they reached. So too with the social sciences. No further commentary required: Americans are not normal. Though to be fair, maybe nobody is, and that may be grounds for re-examining what we think we know.

There should be a field of study devoted solely to questioning scientific research by disqualifying study populations. How much do we think we know now that's based squarely on deficient understanding of a population's inherent effect on data? It sounds like a fun and dangerous question to explore.

Comments

Skepticism

Or population skepticism. Time for you to get your PhD I think. I think there should generally be a bit more disqualification of things in general in this world. I've always been a fan of the idea that a person could become a politician solely on the idea that he would go and disqualify existing laws. Also I think you have a "top" that should be a "stop".

Ryan Anthony on March 07, 2013 09:47 AM

Ha, I thought I ...

Ha, I thought I fixed that "to" to "too," looks like I broke it more.

Ryan Lee on March 07, 2013 03:31 PM

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