Writing is thinking Outsourcing the entire task of writing to LLMs will deprive us of the essential creative task of interpreting our findings and generating a deeper theoretical understanding of the world.

Fantastic piece from @broniatowski.bsky.social about our latest preprint, an analysis of industry ties in social media research. (Yes, I owe you all a thread on it; bear with me)

"The deeper question is not whether every co-authorship should trigger a disclosure. It is whether we are willing to treat social media research as a domain where integrity safeguards scale with stakes."

Some reflections by @broniatowski.bsky.social on our preprint and some of the discussion around what constitutes a conflict of interest in @kakape.bsky.social's write-up. A few thoughts and reflections below 🧪 broniatowski.substack.com/p/when-is-a-...

It’s pretty funny seeing integrity conversation led by people who pretend they didn’t get their paper retracted over integrity violation and the guy who said covid wouldn’t kill that many people then doubled down.

I remember during the pandemic having to contact my employer on more than one occasion and prebunk the attempts to get me fired over viral tweets containing the hot takes that: 1) Vaccines reduced deaths from covid 2) John Ioannidis should name what statistical test he used

"Undisclosed ties to industry are common ... among authors, ... reviewers and academic editors ... industry ties are associated with a topical focus away from impacts of platform-scale features." @jbakcoleman.bsky.social et al. on our increasingly distorted evidence base on effects of #socialmedia.

Social media research has a conflict of interest problem: “these findings suggest industry influence in social media research is extensive, impactful, and often opaque” A real concern is that this may incentivize scholars to minimize the harms of social media platforms arxiv.org/pdf/2601.11507

Kai's write up and @cailinmeister.bsky.social's thread do a great job of summarizing our results. Rather than cover them a third time, I thought I'd clarify some misconceptions over our piece and COIS more broadly that keep cropping up scattered across replies. 🧵🧪

Great thread from our resident expert on industry influence, @cailinmeister.bsky.social, enumerating and contextualizing the key results of our recent preprint.

Many thanks to @kakape.bsky.social for covering our new work on industry ties to social media research!

Who is the Big Tobacco of today? In new work, we find 50% of high profile social media papers are connected to big tech through funding, collaboration and employment. Most connections aren't disclosed. @jbakcoleman.bsky.social @jevinwest.bsky.social @carlbergstrom.com 1 arxiv.org/abs/2601.11507

One of the issues that has come up again and again in my reporting on misinformation and social media is the massive influence social media companies have on research in the field. Last night a preprint dropped that tries to get at this with some numbers. My piece in @science.org (and 🧪🧵 coming):

Some coverage of our new findings, with perspectives and thoughts from @shelbygrossman.bsky.social, @cailinmeister.bsky.social, @naomioreskes.bsky.social, and @profsanderlinden.bsky.social

This looks 🔥🔥🔥 "we show that half of the research published in top journals has disclosable ties to industry in the form of prior funding, collaboration, or employment. However, the majority of these ties go undisclosed in the published research."

Ever wonder what proportion of high profile social media research is tied to the tech industry? New from me, @cailinmeister.bsky.social, @jevinwest.bsky.social and @carlbergstrom.com. Thread tomorrow. arxiv.org/abs/2601.11507

JCHForever.

Come hang, y’all! It’ll be a blast.

Do you study disinformation or want to start working in that area? Come to the DSI June 15-18th with @cailinmeister.bsky.social, @katestarbird.bsky.social, @jevinwest.bsky.social, @rcalo.bsky.social, @naomioreskes.bsky.social, @emmaspiro.bsky.social, and many more. disinfoinstitute.org

I'd also note that it becomes a *lot easier* to avoid dichotomization if you just give up entirely on tests and experiments and just start using bayesian tools to describe and summarize data.

Constructively, a lot of the replies seem to feel seen (the pain?) of this post. It can be hard to write up Bayesian credible regions when you know your paper is headed for reviewers who will write back "yeah but is it significant?" Here's my brief advice:

Bruh

One of my concerns with AI-assisted research in biology is that we're already looking only in the lamplight and AI incentivizes us to narrow the beam. Seems like it's happening... www.nature.com/articles/s41...

I just want to get this cozy.

In all seriousness, do any scientists here actually worry their literature is being polluted by special issues? Do you find yourself accidentally reading and citing MDPI and frontiers journals? Does the content impact your work?

scicomm advice: if you're going to joke about your own paper being "piss-poor", that verbal irony only works if the paper isn't actually bad.

Im flabbergasted we don’t retract and shame folks who regress y ~ f(y,x).

If you're interested in a short behind-the-scenes of the retraction of a mega-metascience paper—the first of its kind (the retraction, not the paper)—this might be for you! Had to gloss over so many details to observe allotted time but happy to share an extended version of my slide deck with links.

This is how I found out.

📽️ “Claims about scientific rigour require rigour” / with Berna Devezer @devezer.bsky.social youtu.be/qNJ8xqaObR8?... The event was organised by ReproducibiliTea UniBasel

Corrected errors on variance calculations and structure (thx @jbakcoleman.bsky.social) and added corresponding interval estimates. Note, see Joe's comments too... good points to consider. My aim wasn't really anything more than just pointing out you can meta-analyse these things if you want.

If gen AI systems often just repeat what they have seen elsewhere, then researchers using LLMs to simulate human behavior might have a serious ethics conundrum: maybe such studies are just analyzing observational data without consent? cc @mjcrockett.bsky.social www.theatlantic.com/technology/2...

FWIW, the secret to finding long lasting love is just being a human to other humans til one human and you start hanging out a lot.

Someone at the grey lady greenlit a story on incel tinted eugenics dating with AI. Given current events, it’s an odd use of key strokes.

Silicon Valley is a disorder. www.nytimes.com/2026/01/06/s...

This paragraph is a pretty good exercise in spot-the-bullshit. Can you see it? Reading this paragraph, you'd walk away with the conclusion that mere FDR correction can address replicability issues. The authors certainly try to make this claim. www.nature.com/articles/s41...

The author's should ask ChatGPT to provide feedback on the risks of nonresponse bias in their design. If you're trying to design-bias a study towards LLM-friendly findings, this is how you do it.

I'm teaching Statistical Rethinking again starting Jan 2026. This time with live lectures, divided into Beginner and Experienced sections. Will be a lot more work for me, but I hope much better for students. I will record lectures & all will be found at this link: github.com/rmcelreath/s...

who wants to see baby howlers? also look at that mom's face! she looks exhausted and exasperated because the babies don't stop moving for a second! unless they're asleep in ridiculous poses.

I’ve been in compliance

What makes this remarkable to me is that we have many published papers relying on metas data, and they’ve demonstrated a willingness to alter data being externally evaluated. Unlike Pruitt or Gino, we have no way of checking the integrity of data they’ve provided in the past.

Must read reporting

New reporting from @jeffhorwitz.bsky.social shows meta actively altering shared data to produce rose-tinted results in searches of the as library. Can we reasonably trust the data they share with academics? www.reuters.com/investigatio...

Every week, Nature publishes yet another breathless puff piece about some AI startup, based only unpublished claims from the company and interviewing only those who work there. How can the leading scientific journal publish piece after piece that would make Kevin Roose blush? I think it's that...

It's strange how rarely journalists covering this space can ask "Hey, but is it bullshit?". CEO's whose companies are over-leveraged, bubbly, and unprofitable promise a major breakthrough that will justify their fragile position and no one seems to *consider* they may be lying. It's Theranos 2.0.

700 miles driven in a day is a bit much.

*in expectation*

It sticks out in this article that #openscience top brass quickly pivoted from critiquing “gold standard” science to embracing it. Helping the very same nih director who is slashing science in the us, politicizing it, and shared conspiracy theories about me and my colleagues work.

Agree with the quoted statement by @richarddmorey.bsky.social and disagree with Gelman on that point of asymmetry. Much of what we call metascience today has gained popularity and momentum from scientists/policy makers/funders is by making major positive claims about how science works/doesn't work.