iiinova — where your digital self keeps evolving

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Diana B. Greenwald @dbgreenwald.bsky.social · 28/09/2026

Attaching some random screenshots but could’ve done this across hundreds of city blocks or stretches of road.

Satellite image of complete destruction of buildings in southern Gaza.

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Max Kennerly @maxkennerly.bsky.social · 20/09/2026

"This election is about the threat of trans kids" is the worst possible messaging for Dems yet so many candidates are leaning into it. No voter will flip R->D over it. Low-info voters read this as "you're focused on bullshit that doesn't affect me" while the base reads this as "you're an asshole."

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Jed Kolko @jedkolko.bsky.social · 17/09/2026

The 2025 American Community Survey should have come out today. But it has been delayed because of unusual political encroachment at Census. ACS drives business and policy decisions, especially in local communities, and is the primary input to Census’s immigration estimates.

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Bobby Kogan @bbkogan.bsky.social · 17/09/2026

Have been incredibly busy these past two months, but finally really turning my attention back to my upcoming appropriations paper. Some of the data are not 100% done yet, but I want to focus on how much domestic discretionary funding has been cut in the last few years. Posted only on Bluesky.

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Cyrus Samii @cdsamii.bsky.social · 16/09/2026

Half of our seminars should be pre analysis plans and the other half results. Imagine if people had an up front stake in your research, and imagine getting great input before you finalize your analysis strategy. It should be the norm.

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Cory McCartan @corymccartan.com · 15/09/2026

NYT poll of LV shows D+9 generic ballot ±3.2. Plugging that into my simple congressional swing model (tinyurl.com/cmchousemodel) gives 241D–194R, with 94% chance of D win. Effect of redistricting in that environment is R+4 seats, with TX and FL doing the heavy lifting, and NC slightly backfiring

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Mark Joseph Stern @mjsdc.bsky.social · 15/09/2026

Others have said this but it’s truly insane that Brett Kavanaugh, lover of the major questions doctrine, thinks there’s a good chance USPS can use a vague grant of authority over mail processing to radically alter absentee voting procedures in all 50 states without congressional approval. Come on.

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Cory McCartan @corymccartan.com · 15/09/2026

From Alito dissent on mail ballots (L). How can this possibly be squared with the "major questions doctrine"!?!? (R from WV v. EPA)

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jamelle @jamellebouie.net · 06/09/2026

the other strange thing about this is that the 2024 election result was exceptionally narrow and yet commentators left and right talk about it like it was 1984

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Anton Strezhnev @astrezh.bsky.social · 02/09/2026

This is cool but I think an over-use of RD - CEF really looks like it curves at the cut point. But why do we expect a jump? Impact is probably higher for internal locations - so the relevant treatment intensity isn’t at 0.

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Cory McCartan @corymccartan.com · 01/09/2026

He literally goes around with this slide. The same 'proof' would imply that no stationary AR(1) process with unbounded increments can exist. Error probability is not constant!

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jamelle @jamellebouie.net · 01/09/2026

you could basically predict the direction public opinion under trump if you took the view that a) the 2024 election was about inflation and b) "wokeness" wasn't especially salient nor was it especially unpopular.

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Amanda Weiss @amandaweiss.bsky.social · 27/08/2026

Ofc I say this and personally put WAY too much effort into reviews. And then I die inside when my papers spend six months under review or get torpedoed because someone was not on board with my type of paper existing or are evaluated by someone who doesn't know how math works. So there's that...

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AFL-CIO @aflcio.org · 25/08/2026

America’s unions are proud to endorse @sbworkersunited.org’s boycott of stand-alone corporate Starbucks stores. Workers are fed up with unchecked corporate greed, and we’re standing with them in their fight for a fair contract. No contract? NO COFFEE! ✊ www.boycottstarbucks.net

Boycott Starbucks. No Contract? No coffee. Period. BoycottStarbucks.net

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Cory McCartan @corymccartan.com · 24/08/2026

Data center opposition seems a pretty rational strategy to me even though I may not be totally on board. If you are feeling threatened + angry at new tech, why not contest it on turf you can historically win on & do so locally (NIMBYism) rather than directly try to fight a new technology (hard)?

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Ben Williamson @benpatrickwill.bsky.social · 18/08/2026

What's most upsetting me as a journal editor is that many papers we receive where AI use is disclosed for editing and language refinement actually appear to have been ruined rather than improved by AI. We get what seem like promising underpinning studies, but totally obscured by over-complex text.

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Cory McCartan @corymccartan.com · 16/08/2026

Very concerning the NYT killed this excellent piece at the behest of the scammy firms it exposes

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Melody Huang @melodyyhuang.bsky.social · 13/08/2026

Really excited to see that my paper with Erin Hartman on assessing non-ignorable nonresponse in survey weighting is (finally) out! doi.org/10.1093/poq/...

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Etche_homo @etche.bsky.social · 07/08/2026

Corroborated by my own experience with other Big Publisher journal titles Yet we're more impressed on evaluation committees by 1st-author candidates for [things] who made it through the gauntlet. Let's vow to check that impulse & turn to our professional society titles when possible & independent.

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Cory McCartan @corymccartan.com · 07/08/2026

Out yesterday at Nature Human Behaviour is my paper with @chriskenny.bsky.social on a unified way to measure individual & group harms in redistricting! Due to extortionate APC fees (~$13k) we did not publish open access, but you can read for free at rdcu.be/fyd95 !

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Individual and differential harm in redistricting

Nature Human Behaviour - McCartan and Kenny develop a framework for quantifying the individual-level impacts of redistricting in the USA, showing its applicability for identifying partisan...

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Kevin Morris @kevintmorris.bsky.social · 06/08/2026

Happy birthday to the Voting Rights Act. Complicated feelings on this particular anniversary.

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Ryan Enos @ryanenos.bsky.social · 05/08/2026

Don't posit a theory that is only interesting because it implies X causes variation in Y, test for a statistical relationship between X and Y, but then say you are not interpreting causally. Of course you are interpreting it causally. That was the whole point of what you just did.

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Dan Simpson @danpsimpson.bsky.social · 04/08/2026

Mechanically, what this means is that it’s assuming fairly smooth interactions between covariates. So if you want flexible models of interaction you have to build them in yourself. Which is, after all, what you’d expect with BART.

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Dan Simpson @danpsimpson.bsky.social · 04/08/2026

This is definitely interesting. It’s probably worth noting in high dimensions that mixed sobolev spaces are much smoother than usual sobolev spaces. So think of this kernel as closer to a squared exponential than a Matern-1. But still rough enough that the paths aren’t analytic.

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Noah Greifer @noahgreifer.bsky.social · 03/08/2026

Fascinating and clear paper by @corymccartan.com and @melodyyhuang.bsky.social, greatly enhancing our understanding of how Bayesian Additive Regression Trees (BART) works and why it is so effective. A must-read for my fellow BART enthusiasts. #statssky #causalinference

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Cory McCartan @corymccartan.com · 03/08/2026

New WP w/@melodyyhuang.bsky.social studying the success of BART models, which regularly win causal inference competitions! We argue that BART should be thought of as a random features approximation to a limiting GP. This view helps understand BART & apply it in more places arxiv.org/abs/2607.28844

Seeing the Forest for the Trees: The Gaussian Process Limit of BART

Cory McCartan & Melody Huang

Abstract:
Bayesian Additive Regression Trees (BART) have shown state-of-the-art performance in both prediction and causal inference problems. Previous theoretical work has attempted to explain BART’s superior performance by establishing posterior contraction rates for standard BART models, but these rates depend strongly on the number of covariates. Here, we take a different approach and study the behavior of BART as the number of trees grows towards infinity. We show that in this regime, BART converges to a Gaussian process (GP) with a particular kernel. The kernel and its corresponding reproducing kernel Hilbert space (RKHS) have favorable inferential properties that help explain BART’s excellent performance. We introduce random tree features as an approximation to this limiting GP, and establish minimax-optimal learning rates for ridge
regression on these random features that depend only logarithmically on dimension. In addition to providing insight into the empirical success of BART, random tree features offer a computational benefit over traditional MCMC estimation. The random-features approximation also allows
practitioners to easily incorporate BART into any model which has a linear predictor, expanding the applicability and flexibility of BART.

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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 03/08/2026

arXiv📈🤖 Seeing the Forest for the Trees: The Gaussian Process Limit of BART By McCartan, Huang

Bayesian Additive Regression Trees (BART) have shown state-of-the-art performance in both prediction and causal inference problems. Previous theoretical work has attempted to explain BART's superior performance by establishing posterior contraction rates for standard BART models, but these rates depend strongly on the number of covariates. Here, we take a different approach and study the behavior of BART as the number of trees grows towards infinity. We show that in this regime, BART converges to a Gaussian process (GP) with a particular kernel. The kernel and its corresponding reproducing kernel Hilbert space (RKHS) have favorable inferential properties that help explain BART's excellent performance. We introduce *random tree features* as an approximation to this limiting GP, and establish minimax-optimal learning rates for ridge regression on these random features that depend only logarithmically on dimension. In addition to providing insight into the empirical success of BART, random tree features offer a computational benefit over traditional MCMC estimation. The random-features approximation also allows practitioners to easily incorporate BART into any model which has a linear predictor, expanding the applicability and flexibility of BART.

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G Elliott Morris @gelliottmorris.com · 03/08/2026

Dems strongly favored to take the House in our new election forecast. Senate just better than a tossup: Iowa: 41% Dem Texas: 48 Alaska: 51 Ohio: 53 Maine: 68 Michigan: 69 North Carolina: 84 Georgia: 94 www.gelliottmorris.com/p/democrats-...

gelliottmorris.com

Democrats strongly favored to take the House, Senate tilts Democratic in our new election forecast (crosspost)

Our brand-new election forecast for the 2026 congressional midterms puts Democrats at above even odds to take control of both chambers

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Cambridge University Press Political Science & IR @cambup-polsci.cambridge.org · 30/07/2026

#OpenAccess from @apsrjournal.bsky.social - Redistricting Reforms Reduce Gerrymandering by Constraining Partisan Actors - cup.org/4pNwXA7 - @corymccartan.com, @chriskenny.bsky.social, @simko.bsky.social, EMMA EBOWE, MICHAEL Y. ZHAO & KOSUKE IMAI #FirstView

Banner with the hashtag #OpenAccess on a green background and the text "American Political Science Review" on a blue background below.

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Cory McCartan @corymccartan.com · 30/07/2026

Out today in the APSR: our paper studying which gerrymandering reforms work! Long story short, do what Michigan does! Slightly longer story: we project these different complex reforms onto a 1-dimensional "partisan leeway" axis, and do continuous-trt DiDiD there. doi.org/10.1017/S000...

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jon ben-menachem @jbenmenachem.com · 25/07/2026

If there is a practical difference then people should just talk in simple terms about what is to be done. The dictionary definition stuff is largely exhausting, pedantic navel gazing

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[Christopher M. Federico] @chrispps.bsky.social · 24/07/2026

this elite mindset is tedious in the extreme and desperately unaware of how little correspondence it has with empirical mass opinion (including the actual 'middle of the road' voter in the wild), but it would also be less of a problem for the rest of us under proportional representation

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Chris Kenny, PhD @chriskenny.bsky.social · 21/07/2026

Thrilled to share that I received POLMETH's Statistical Software Award for 2026 for the #rstats package geomander. It's a performant toolkit for working with spatial data, especially election and demographic data. Learn more about the package at christophertkenny.com/geomander/

christophertkenny.com

Geographic Tools for Studying Gerrymandering

A compilation of tools to complete common tasks for studying gerrymandering. This focuses on the geographic tool side of common problems, such as linking different levels of spatial units or estimatin...

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Dead Carl @deadcarl.bsky.social · 19/07/2026

Peacetime politics involves less physical danger than war, but it has some dangers in common: both require what Clausewitz calls “moral courage” by which he means the willingness to accept risks and moral responsibility. This is what I saw lacking on that panel. 1/🧵

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Jay Rosen @jayrosen.bsky.social · 20/07/2026

Here's something I post from time to time. My answer to a reader who asked me: what could journalists do NOW to break with some of their more corrosive habits.

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Cory McCartan @corymccartan.com · 15/07/2026

Interesting read. I think both can be true: (a) the public reads more than ever, and (b) standardized tests, phones (TM), & pandemic have hindered college students' ability to engage with longer works. Academics see (b) and are receptive to hearing that reading has cratered everywhere

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Robin Ryder @robinryder.bsky.social · 08/07/2026

I have just resigned from the board of "Statistics and Computing", along with 17 other Associate Editors. This was a difficult decision: this great journal has published many tremendous articles under the leadership of EiC Ajay Jasra, and before him David Hand, Gilles Celeux, and Mark Girolami.

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Adam Bonica @adambonica.bsky.social · 02/07/2026

If there’s an issue Democrats could run on and win in a landslide, it’s anti-corruption. But first the Dem establishment needs to deal with its own corruption problem. It’s not enough to be right about Trump’s corruption—they also have to be credible.

Bar chart from Reuters/Ipsos poll of 1,019 U.S. adults, Sept. 19–21, 2025, asking which party has a better plan on 11 issues. Republicans lead on crime (40% vs. 20%), immigration (40% vs. 22%), foreign conflicts (35% vs. 23%), U.S. economy (34% vs. 24%), gun control (32% vs. 28%), political extremism (30% vs. 26%), and corruption (27% vs. 21%). Democrats lead on respect for democracy (31% vs. 29%), healthcare (34% vs. 25%), women’s rights (38% vs. 25%), and environment (37% vs. 23%). Margin of error ±3 points; third-party and non-responses excluded.

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Cory McCartan @corymccartan.com · 22/06/2026

Had a great time presenting Shiro Kuriwaki's and my new EI methods to EPSS in Belfast on Saturday! Our R package implementing all these methods (as well as partial ID bounds) is also now on CRAN! corymccartan.com/seine/

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Cory McCartan @corymccartan.com · 11/06/2026

New R package on CRAN! ONNX is a runtime & file format for ML models. 'onnxr' lets you load & run models in about 2 lines of code! E.g. image detection running in ms from a pretrained model. Perfect for embeddings, smaller models, etc. And lots of .onnx available online! corymccartan.com/onnxr/

R code snippet:
library(onnxr)
model = onnx_model(model_path)
res = onnx_run(model, img, simplify = TRUE)

Vermeer's "The Milkmaid" with person, bowls, dining table detected by ML model running via onnxr

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Andy Vitek @avitek.bsky.social · 09/06/2026

This take may ruffle some feathers. Not only do political parties expel members all the time, but the ability to do so is absolutely crucial for maintaining political cohesion and protecting against demagogic capture. Like would anyone on this platform object if the Democrats expelled Fetterman?

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Kevin Morris @kevintmorris.bsky.social · 05/06/2026

Few people are putting this so plainly. This is what is happening. Miss me with partisanship, as if partisanship isn't a vessel for achieving policy goals — including racial ones

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Stephen Nuñez @socio-steve.bsky.social · 04/06/2026

So I urge you to look at the folks who will inevitable call for us to privatize social security in the wake of this report and check for the overlap with the folks who brought us the surging inequality and a sluggish economic recovery that got us here. 4/4

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Chris Geidner @chrisgeidner.bsky.social · 03/06/2026

This is truly one of the worst things the court has done — both in terms of legitimacy and in terms of the law — since I have been covering the court.

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