Also this week: Wikipedia vs. its own success, liberal activism vs. science, how to fund high risk, high reward research, Robert Trivers’ wild life, new ggplot2, and (much) more!
A bit late to this, but that’s ok, because it’s great: a Christmas morality tale about researcher degrees of freedom (or p-hacking; call it what you will). Read this for your next lab group meeting and discuss what you’d do in that situation–and more importantly, how you’d avoid ending up in that situation in the first place. I’m also mulling over the difficult collective action problem hinted at at the end of the piece:
To let this result enter the literature wouldn’t have a significant effect, it wouldn’t cause anybody to go down an experimental path that they weren’t going to anyway, and it didn’t rule out any life-saving approaches. There was no point being puritanical about it.
Multiply that completely understandable line of thought by the number of labs in the world to get a rough sense of the scale of the collective action problem here. Put bluntly: most individual bits of science have little or no impact, a fact of which most scientists are well aware. Does that select for a collective lowering of standards? I’ve asked that question before, but back then I hadn’t cottoned on to the collective action problem here. It’s true that one mistaken paper rarely matters much–but if lots of papers are mistaken, and if knowledge that no one paper matters increases the frequency and seriousness of mistakes in papers, then in aggregate mistaken papers might matter a lot.
Andrew Hendry vs. Alex Bond on the proposition that anyone with a decent record can get an academic job, if only they’re persistent and not too picky about their first job. I think both have some good points. Do yourself a favor and read the comments on both pieces too. I may have more on this in a future post (sadly, no time to post on this now, I’m swamped).
Stephen Heard reflects on his first year of blogging. Keep it up Stephen!
This is up my alley: Extinct is a new group blog on the philosophy of paleontology. For instance, here’s my Calgary colleague Adrian Currie arguing that we should resist the lure of simple narratives about why evolutionary history played out as it did (wonder if Robert Trivers, highlighted below, would agree?) Accessible and thoughtful.
Grumpy Geophysicist argues that NSF isn’t funding sufficiently risky work, because work that challenges current views doesn’t get funded. Do folks here agree? At the end, there’s an interesting suggestion about how to identify high risk, high reward work:
Long ago, GG was told that Eldridge Moores had a policy back when he edited the journal Geology; his preference (so it was told) was to publish papers producing one review recommending “accept without changes” and another recommending rejection. Although this occasionally produced papers that, in retrospect, fully justified the “reject” recommendation, the basic idea had merit: it could be good to focus on the papers that so challenged part of the community that they felt those papers should be squashed. Perhaps this is apocryphal, but it seems worth considering. Maybe program managers, instead of having panelists vote on a grade for a proposal, should simply time how long they want to argue about any given proposal and fund the ones producing the longest arguments.
One downside of funding the most controversial work is that, if a field is divided into opposing camps, you end up funding lots of work that just perpetuates the argument rather than resolving it. More broadly, I think “riskiness” isn’t unidimensional and can be tricky to judge; see for instance my interview with Rich Lenski on whether the LTEE was a low-risk or high-risk experiment. Related: my old post on “experiments so crazy they just might work”. (ht Retraction Watch)
Empiricism is replacing theory in economics. Includes time series data on the types of papers published by leading econ journals. Always interesting to read about trends in other fields that share some of ecology’s features. Stick with it to the end for some interesting comments on economics’ last fling with empiricism and why it was abandoned.
Next time you complain about Wikipedia getting something wrong and someone responds by saying “Well, why don’t you just edit it yourself?”, feel free to reply “Because Wikipedia doesn’t want me to” and link to this paper. Wikipedia is an amazing project and absolutely has its uses. But the days of Wikipedia as an open resource anyone could edit are long gone in practice, even if they’re still there in principle. Nowadays, there is no hypocrisy or selfishness in (i) making use of Wikipedia, (ii) complaining when it’s wrong or unhelpful, and (iii) not editing it yourself. (ht Marginal Revolution) Related: Meg’s cautionary tale of having students edit Wikipedia as an assignment.
Here’s Jesse Singal’s review of Alice Dreger’s Galileo’s Middle Finger: Heretics, Activists, and the Search for Justice in Science. Sounds interesting and important. It’s about cases in which collisions between science and liberal activism have driven both off the rails (in contrast to the anti-science conservatives scientists usually worry about). I don’t think it’s an exercise in “both sides do it” false balance to worry about such cases. Other reviews from the New York Times, the journal Human Nature, writer Clinton Peters, and science journalist Ellen Rupert Shell (those last two thoughtfully critical in places).
Paul Krugman comments on time series data on the political leanings of US academics, including scientists. US academics as a group identify more with the left than they used to. For reasons Krugman lists, I’m mostly not too worried about this issue in the context of science. Kevin Drum weighs in too. He says we shouldn’t need to argue about why the trend is happening, because the various hypotheses are easily testable. (p.s. my understanding is that the data discussed do not come from a random sample, so treat with caution)
NSF 101. From Margaret Kosmala. Useful for grad students and postdocs.
Prediction vs. causal inference in regression. Nice short practical overview of the differences between these two uses of regression. (ht Jim Grace, via the comments)
Summary and commentary on the Ontario provincial government’s final consultation report on a new funding formula for its universities. Short version: big changes are coming. Funding is likely to be decoupled from undergraduate enrollments and instead tied to some yet-to-be-determined formula based on outcomes and student satisfaction. And the provincial government is likely to get more directly involved in managing at least some universities.
A profile of Robert Trivers, based on his forthcoming memoir Wild Life: Adventures of an Evolutionary Biologist. If you only read one book this year, this should probably be it. Don’t believe me? Quoting from the blurb:
But unlike other renowned scientists, Trivers has spent time behind bars, drove a getaway car for Huey P. Newton, and founded an armed group in Jamaica to protect gay men from mob violence.
and the profile:
His dissertation was so strong that when he showed up before the evaluating committee, which included such luminaries as E. O. Wilson and Ernst Mayr, they skipped the charade of making him defend it and simply offered their congratulations.
and the profile again:
His college roommates once showed him pictures of a hippo and a rhino and asked him to identify which was which. He picked wrong.
Oh, and he decided to become an evolutionary biologist after failing to get into law school and taking a job writing children’s books about biology. (ht: Marginal Revolution)
Jacquelyn Gill has a list of 10 straightforward things you can do to support diversity in academia in 2016. Lots of good ideas there!
There’s a new version of ggplot2, which sounds like it’s a pretty major update.