Also this week: an unusual retraction in Evolution, a shadow cv, distinguishing sheep from goats in scientific publishing, TED talk vs. TED talks, and more.
The shadow cv of a Princeton prof (ht Chris Blattman). My own shadow cv is here (needs updating). That Princeton prof even includes grad programs he didn’t get into. I’ll have to add that to mine. Undergrad too. For grad, I know I didn’t get into Washington and Oregon State, and I think maybe not UConn either. For undergrad, I didn’t get into Duke.
TED talk eats itself. (ht Chris Blattman)
Yet another reason why I regret ever publishing a paper with Frontiers. (ht Small Pond Science) (EDIT: Just to clarify, that’s the publisher Frontiers, not the ESA’s journal Frontiers in Ecology and the Environment)
A reminder, if one were needed, that Sci-Hub is not the scientific publishing equivalent of Robin Hood. (ht @kjhealy)
- Do what works for you. Don’t feel like you have to be on Twitter if you don’t like it or don’t get much out of it. It’s not essential, not even if (unlike me) you’re not yet an established scientist. It probably won’t become essential any time soon, if ever. And if it ever does become essential, the way email is, well, then you can just join it then. Anyone who says otherwise is overgeneralizing from themselves and people they happen to know.
- Remember that people who are not on Twitter can read or hear about anything you write on Twitter.
- Remember that Twitter is a very non-random sample of people. Of whom you will surely follow, and be followed by, a very non-random subset who are a lot like you in various ways. And each of whom tweets about some very non-random sample of everything they believe, think, and experience. All of which is totally fine–Twitter’s no different than the rest of life in that way. But because Twitter makes it easy to communicate with lots of people from far away whom you don’t know personally, it makes it easy to forget that you’re living in a filter bubble partially of your own making.
- Twitter is a terrible medium for debate.
Sticking with Chris, and in honor of the upcoming final exam season: Chris’ data confirm my anecdotal impression that the speed with which students complete exams is uncorrelated with their exam performance. Now I’m wondering if students think there’s a correlation…
A rare and unusual retraction from Evolution. Briefly, Fromhage, Jenions & Kokko 2016 discovered mathematical mistakes in Kokko & Wong 2007 that greatly alter the conclusions, and so wrote a new paper redoing the analyses and discussing the new conclusions. Apparently, the possibility of an erratum to K&W 2007 was considered and rejected because the erratum wouldn’t have had the same authors as the original paper. To be clear, there’s absolutely no suggestion of misconduct or sloppiness by anyone involved. It’s an unusual case and I confess I’m unsure of the best way to handle it (and note that I may not have enough information to have an informed opinion, since all I know is what’s in the link). I can see why Evolution handled the case as it did–the original paper wouldn’t have been published in that form had the mistakes been caught at the time, so there’s an argument that it shouldn’t stay published now that the mistakes have been discovered. But I wonder if it would’ve been better to attach an erratum rather than a retraction to the old paper, even if that meant relaxing the usual rules on erratum authorship. There’s a stigma attached to retractions, even one that says, as this one does, that the retraction is for “inadvertent technical errors”. As Brian’s written, mistakes happen in science. Authors who do the right thing and come forward about honest mistakes deserve to be praised and shouldn’t experience even a whiff of stigma.
UPDATE: Ben Ashby, one of the reviewers of the new paper, adds some additional information and commentary. He feels strongly that an erratum was the way to go. And here he elaborates on the comments in the previous link.
UPDATE #2: Andrew Gelman comments. He ends up in the same place as Ben (it would make sense to issue a correction rather than retraction here), but one of his comments along the way is quite odd:
No no no no no! Retraction is not a “penalty,” it is just a matter of correcting the scientific record.
No no no no no! In the minds of many, many scientists, retractions have a stigma attached to them that errata do not, no matter what the reason for the retraction (Aside: that’s in part because lots of readers don’t read closely and so assume all retractions are for misconduct or sloppiness.) Like it or not, whether you call it a retraction or correction matters to a lot of people. And you can’t change that by just telling people to think of retractions as corrections, or by saying that you personally think of them as corrections.
Andrew Gelman on how he interprets prior distributions on model parameters. Short version: in a frequentist way, but in some cases with a rather unconventional “population” in mind.
And finally, please enter your phone number. (ht Brad DeLong) If you’re a programmer, you will want to put down a plastic sheet on the floor before clicking that link, to make cleanup easier after your head explodes.🙂
This week, Nature had a column by Tricia Serio on subtle sexism in science, including a link to a website where women can share their stories of microaggressions. One thing I loved in the column was Serio’s account of how she purchased soccer referee cards to use to call out microaggressions. I received an email last week that warranted a yellow card; I love the idea of replying with a gif of someone being given a yellow card, but won’t actually do that.
I like Margaret Kosmala’s idea to have scheduled days to catch up on all the little non-work things that never seem to get done otherwise. I’ve been thinking that, once my baby is in daycare, I will need to take a day or two to do some serious organizing in my house. Presumably by June it will be safe to put away the snowpants and snow boots, right?
Advice for academics who don’t want to be part of the problem. (ht: Christie Bahlai) I had a conversation with someone yesterday morning (before seeing this site) about the first point (nominate women and people of color for prizes). (EDIT: It’s no longer the first point!) Something that helps when trying to come up with nominees is to look at a list of eligible people. This is the idea behind DiversifyEEB (introduced in this guest post by Gina Baucom) — please use it to identify scientists who are women and/or underrepresented minorities to nominate for awards!