I'm excited to (belatedly) announce the two inaugural #URSSI Early Career Fellows, @matthewfeickert.com & @samzhang.bsky.social !
You can read more in our official post: urssi.us/blog/2025/04...
We'll be opening our next call for fellowship proposals in the coming months, keep an eye out!
An AI feature that I *actually* want in Zoom: when it sees you're about to sneeze, it auto-mutes you.
h/t @aaronclauset.bsky.social @nicklaberge.bsky.social @samzhang.bsky.social
By
Matt Hardy @mdahardy.bsky.social
Sam Zhang @samzhang.bsky.social
Jessica Hullman @jessicahullman.bsky.social
Jake Hofman jakehofman.com
Dan Goldstein @dggoldst.bsky.social
1/ I’m excited to share our article "Gendered hiring and attrition on the path to parity for academic faculty" with Hunter Wapman @aaronclauset.bsky.social @danlarremore.bsky.social , now published @elife.bsky.social : elifesciences.org/articles/93755
To be clear, I would agree with you even if removing yourself from consideration didn't change the hired applicant quality at all. But this is just a cherry on top, to say that it can make a difference, sometimes more than others
Yes! Personal distaste aside, suppose N candidates apply, with quality drawn from some distribution, and the employer hires the highest quality applicant (stupid devil's advocate assumptions). Then removing yourself from consideration will still lower the expected quality of the hire, which is good.
who did this
I feel very brave just being the only person to like your post Jeff! May that be a courageous example for you in dealing with your coffee pot spider
Wait weren't you asking about D3? But this makes me realize that an R interface to webweb could be a hit. It has python and matlab right now.
Also you can export your network as json and put it in directly, if you just want a screenshot. See the dropdown menu: webwebpage.github.io/docs/example...
plugging some work from labmates, led by @danlarremore.bsky.social -- do you know about webweb? webwebpage.github.io
I went to Swarthmore (where Tim Burke, author of the OP blog post, teaches), and I participated on some consultant-run focus groups even as an undergrad! Maybe there tend to be fixed numbers of consultants per university, so at small colleges the ratio is higher...
slide title: "attrition over a career." shows data indicating that for "all-cause attrition", at every career age, women are more likely to leave than men
slide title: "study design." highlights the survey portion of the study, intended to elicit the reasons faculty leave their jobs, noting that gendered reasons for leaving are more important than gendered rates of leaving
slide title: "push & pull." shows data indicating that women feel pushed out of their academic jobs at substantially higher rates than men, and that gender+career age are the strongest predictors of whether a survey respondent reported feeling pushed out of their faculty job
slide title: "conclusions." 1. women faculty universally leave academia at higher rates than men, but the rates vary in magnitude by domain and career age, mainly effecting tenured women, in non-STEM fields, at lower-prestige universities. but regardless of the rates, women leave for different, more worrisome reasons than men: they feel pushed out of their jobs. retention efforts have to focus on these reasons, not the rates
Slides from my talk "Gender & Retention Patterns Among US Faculty" earlier this week @UMass ADVANCE, on our paper with the same name, led by @kspoon.bsky.social. What an amazing team at UMass, doing critical work to improve science and academia 👏
aaronclauset.github.io/slides/Claus...
A visualization of a Normal distribution with label "True (unknown) population" and a label pointing to the mean with the text "I want to estimate this"
Same as previous, but with the addition of a row showing a sample of five draws from the population distribution, the mean, and its uncertainty
Same as previous, but with several additional rows showing how the uncertainty in the mean becomes narrower as sample size goes up. Then, another column titled "Predictive uncertainty" showing the same population distribution with an arrow pointing to its density curve and the label "I want to predict this".
Same as previous, but with additional rows in the "Predictive uncertainty" column showing that as the sample size goes up, the predictive uncertainty distribution does not get narrower, but it becomes a better approximation of the true population distribution.
I like this framing a lot, and use it in slides when describing the difference between these two types of uncertainty
Snow geese fill the sky at sunset in Washington's Skagit Valley.
I am delighted to announce that the Department of Biology at the University of Washington is advertising for a tenure-track assistant professor position on the quantitative understanding of collective behavior.
I will be chairing the search; details are here: apply.interfolio.com/130336
what about Amia Srinivasan's "The Right to Sex"? my teenaged self would have loved it, I think, and maybe it would have sped up my political development by like a decade...
the real horror here is misspelling "correlation"...
also this seems relevant! bsky.app/profile/ecoe...
hat tip @aaronclauset.bsky.social
I agree it's not the reporters who are lazy -- reporters are extraordinarily overworked after all -- but also it's not because of the "ignorant populace" either, which would be blaming the victim. Instead, people become ignorant when journalism (and education, etc) gets gutted for profit
My faves:
“When Alexander saw the breadth of his domain he wept, for there were no more worlds to conquer” (not Plutarch; Die Hard)
“Let my armies be the rocks and the trees and the birds of the sky” (not Charlemagne; Indiana Jones & the Holy Grail)
Ezekiel 25:17 doesn’t exist except in Pulp Fiction
My recent paper in Economic Journal:
In the Econ job market men and women are recommended differently: letters for women stress hard work, those for men more likely highlight brilliance. This affects job placement.
Link to Paper: t.co/HUieaMuERd
With Giovanni Facchini and Markus Eberhardt
Hard to top Florian’s thread:
Output of DALLE-3 with the following prompt: Illustration of a gigantic contraption, appearing almost like a creature, with multiple arms stretching out to grasp artworks and literature from heaps around it. These treasures are dropped into a big cauldron labeled 'AI Mixer'. As the vat stirs, the contents morph into a shimmering digital concoction. From the vat, hoses spray this concoction onto oversized canvases and printing machinery, creating puzzling and distorted results. Another group of machines then grabs these outputs, converting them into a different, more viscous digital substance.
🤔
paper abstract "Kids these days: Why the youth of today seem lacking" by Protzko and Schooler. it's a zinger!
This 2019 Science Advances paper lives rent-free in my head, and I think it's the social science paper that I mention the most in everyday conversation with my peers or elders... #youths #olds #science
www.science.org/doi/10.1126/...
Andrew Gelman reviewed my book, Modeling Social Behavior.
“The book has social science, it has code, it has graphs—it’s got everything… I hope it’s taught in thousands of classes and sells a zillion copies.”
statmodeling.stat.columbia.edu/2023/10/24/m...
I have been informed that I am being replaced as the Editor in Chief of @eLife for retweeting a @TheOnion piece that calls out indifference to the lives of Palestinian civilians.
Profoundly disappointing if true. Whether or not Michael's post was in good taste, he retweeted a mainstream satirical site to his personal social media account.
As an eLife editor I have no interest in monitoring my social media activity to ensure everything I post represents the journal.
if you want to attend @nativemath.bsky.social 's talk I would be happy to catch you up my spiel over Zoom sometime later :)
along those lines, you could do someone from beetlejuice?
1/ New paper! “Gender and retention patterns among U.S. faculty” w/ N Laberge KH Wapman @samzhang AC Morgan M Galesic BK Fosdick @danlarremore @aaronclauset: www.science.org/doi/10.1126/...
A systematic study of gendered rates & reasons for faculty attrition in US academia 🧵
This is a stick-breaking/string-cutting construction, and the distribution over the set of numbers you get is a draw from a Dirichlet(1, 1, ..., 1) distribution (with N ones), which is a uniform distribution over the N-simplex. But the Dirichlet distribution is "unordered", in case that matters.
