Sunday, December 8, 2024

Friday links: against prediction markets, memory vs. history, the scientific method vs. Trident gum, and more

EcologyFriday links: against prediction markets, memory vs. history, the scientific method vs. Trident gum, and more


Also this week: the importance of celebrating good news, computer scientists are all from Lake Wobegon, evidence vs. evidence-based policy, De-extinction Inc., and more. Lots of good stuff this week!

From Jeremy:

Terry McGlynn on the importance of celebrating good news, and thanking people for fixing problems. In this case, the good news that NSF fixed a longstanding problem with gender bias at its prestigious Waterman Award. I’m one of the guilty parties Terry’s rightly criticizing–I was aware of the problem, but wasn’t aware it had been fixed. So: belated but sincere thanks to NSF for fixing this. Y’all are going to share Terry’s post on your social media platform of choice, right?

A new paper by Alexander Krauss claims in its abstract that only 75% of Nobel Prize-winning discoveries (and other Nobel-level discoveries) involved all major elements of the scientific method. The remaining 25% lacked some or all of hypotheses, observations, and experiments. The abstract emphasizes that 25%, as part of a broader argument for methodological pluralism in science. You don’t have to stick to the standard “scientific method;” you can make major discoveries in other ways. I do wish the paper had a “control” group of papers that didn’t report any major discoveries. Lack of control group aside, I don’t really buy the paper’s framing. I’m a methodological pluralist myself, but honestly, I gotta say that “75% of Nobel Prize-level discoveries use the standard scientific method” is a pretty good advertisement for the standard scientific method! I mean “good advertisement” quite literally. “Three out of four Nobel Prize winners recommend the standard scientific method” is quite close to the “four out of five dentists” who recommended Trident sugar-free gum in a famous old ad campaign. Note that I haven’t yet read the paper, and so cannot vouch for it, but am passing it along just because the abstract sounds interesting.

Why prediction markets don’t work all that well, and never will. Very good piece by two former advocates of prediction markets. I think this piece is a model example of policy analysis. Its thoroughness contrasts with the superficial paragraphs on “broader implications” that many scientists (including me!) stick at the ends of their papers.

Computer science authors’ perceptions of how their papers will do in peer review, vs. how they actually do. Very large and interesting dataset. I’m shocked that computer scientists apparently all think their own papers are much better than the average paper. Apparently, all computer scientists were born in Lake Wobegon. Curious if the results generalize to other fields.

I don’t think this is new, but it’s new to me: there’s a biotech startup company focused on de-extinction.

The claim that a massive comet hit the Earth 12,900 years ago refuses to die. Apparently, history does repeat itself.

Imagine the ecoevojobs.net comment threads if this experiment had been run on ecology faculty job seekers instead of economics faculty job seekers. The experiment feels icky to me, though I haven’t devoted a lot of time to thinking through the ethical issues. Also, I don’t believe the key result (Fig. 3); looks to me like a barely significant, garden of forking paths situation. Here are economist Tyler Cowen’s comments. Here’s sociologist Kieran Healy’s meme-based comment.

Special issue of Hypertext online magazine, asking if there is hope for evidence-based policy. It’s about social policy, but I think ecologists should read it too, because ecology faces the same issues. Especially the core issue: results of randomized controlled experiments don’t generalize–like, at all–to other places and times. How do you do “evidence-based policy” in the face of such variable, heterogeneous evidence? Whether it’s social policy or (say) conservation policy?

Dan Gardner on the line between memory and history. A major event (or famous person) lives in memory for roughly three generations at most. After that, it’s forgotten, unless it becomes part of the core history curriculum in K-12 schools. This seems right to me.

The Primitives have still got it. 🙂

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