I’ve been doing education data work for a long time and somehow this never got on my radar: “Since 1979, the Western Interstate Commission for Higher Education (WICHE) has published Knocking at the College Door: Projections of High School Graduates. This analysis projects the number of high school graduates for all 50 states and the District of Columbia…”

I’m grateful there are so many people doing high-quality open source data like this!

This interview with Sylvester Stallone is wise, emotional, and gripping. And, it really made me want to read his memoir. I knew only bits and pieces before (that he banked on himself for Rocky, didn’t like Arnold). But from his childhood to adult regrets, its an astonishing read.

As someone who has immediate family struggling with mental health disorders, this profile was compassionate and very real feeling. It is hard to describe the ups and downs, day by day, but Brendan Quinn’s writing nails it. Much 💝 to Duncan and his family.

This article in the Economist gets to a layer of AI discourse that seems completely absent. Workers by the thousands are using AI to file administrative claims against their employers in Britain, putting a previously overly burdensome legal remedy in their hands. Sorry for the paywall, but this is worth a read.

Maureen Tkacik wrote the heck out of this piece which explains the collusion, consolidation, and consumer exploitation at the root of the censorship of Macklemore. The roots run deep and old, but there is hope that the public is showing we’re fed up!

Wes McKinney’s keynote at #positconf2026 is 🔥

The idea of a clanker constitution is one I’ve been working on as well, but not as elegant. Luckily he’s sharing it so we can read and learn from it.

Institutional actors already using AI chatbots as a propaganda vector but if you read the story AI also already surfaced the credibility gap. It’s an incredible story. We have to grapple with the ways this new technology and information dissemination method is being actively used.

Absolutely incredible quote to end this article:

The firm then enlisted planners to find a new route that avoided the supposed grave. “A lot of people were very happy about that, and the project is now going [ahead] and Dobby’s happy.”

In the end, he said, “we went quite close to some real Bronze Age remains, but we avoided Dobby’s grave”.

I’m excited to be attending PolicyLink Summit 2026: “We Are the Founders: Writing the Unfinished Story of Our Democracy.” I’m passionate about how data, social science, and policy can work together to liberate us and create a society that flourishes. So I’ll be listening and learning with others August 24-28 in DC eager to be inspired and find new ways to contribute. If you’re going get in touch and let’s be sure to meet up! I’d love to see as many people as I can.

From the event announcement:

“Come together to stake our claim to a future where all people can thrive—boldly advancing a blueprint for a nation that at last serves all. From our legal and regulatory systems to government at all levels, we will reimagine and redesign how this nation serves its people.”

I am so interested in attribution science and its applicability to social science as a complement (and perhaps corrective) to the obsession with isolating causality in a complex and multi-causal world. Great rundown by Ars Technica.

Pretty in-depth reporting here on what the near-term incentives are for Iran in the war with the US. Not as cut and dry as I thought and I appreciated the depth and breadth of sources in this one.

This is a really cool explanation of Pareto efficiency (which sounds boring I know) using interactive data viz and clear storytelling. It’s a great example of how a concept becomes more approachable when transported into a familiar domain in a friendly and thoughtful manner.

I really enjoyed this entry inHadley Wickham’s series on LLM coding tools. It is a level-headed look beyond the hype and hate at what works, what doesn’t, and working through conflicted feelings about how LLMs are changing statistical software practice.

This is a detailed look into the computation behind weather forecasting and how climate science is being integrated. The layering of models and the choice between ML and equation-based modeling always fascinates me. Social science has a lot to learn from these approaches.

This is bad. I use open models all the time - for simple coding, chores, and sensitive data. The open models are really good and super efficient. This move to squash them with regulation instead of competition is the proof. Innovation should be done in the open, like with OSS.

My old graduate school roommate, Daniel Walters a professor at Texas A&M, is co-author on this excellent article about the eroding independence of federal agencies and the opportunity it creates for more executive overreach and erosion of trust in the government.

A really excellent essay about how high-risk, low expected value acts like gambling, trying to go viral, etc. are a symptom of how the incentives have completely changed in the K shaped economy.

I have been interested in this idea and this article introduced me to the concept of “Answer Engine Optimization” or AEO. Unlike SEO, right now at least, it seems very easy to move and adjust. And signs are this is rapidly becoming the way to reach people…

Brian Phillips nails it. From an entertainment perspective, VAR is an abomination in almost every sport. It has gone too far. I hate waiting 20 seconds after any meaningful action to see if the referee will make or reverse a call that changes the game.

The term “understanding” does a lot of work in thinking about code and data science. All code is an abstraction. And, abstractions embody a balance of tradeoffs between competing concerns like readability, performance, and maintenance costs. This post lays that out really thoughtfully!

Consumer sentiment at an all time low. Corporate profits at an all time high 15% share of GDP. Employee compensation below 10% of GDP. Prices soaring, choice falling. Something has to change. Freedom and liberty can still be restored.

This is wonky, but as it is forecast to hit above 100F here in Boston this week, I plan on digging in and reading this really great report/policy vision that explains how a better world is possible. This is the kind of engaged applied social science that I love!

I was reading this nodding along and realized at some point, awhile back, I had no clue what it was talking about. But I was still enjoying it.

This was interesting to read. For quantitative analysis AI simply does most of the work when prompted now. Once you see it and believe it, the really interesting questions discussed in this article take on considerable urgency. It’s uncharted territory which is exciting to think about and very easy to get lost in.

I appreciate the technical content being put out by Lander Analytics. Consistently great stuff, on the cutting edge, thoughtfully presented. I use DuckDB all the time and read the official post about the Quack protocol, but this article made some practical recommendations that clicked for me.

This is a fun retrospective on technology. It’s good to stop amid the hype and hyperbole of the tech industry and take the wider view. Humbling and inspiring and grounding.

An awesome well thought out and detailed way to approach using AI assisted coding agents to give back to open source projects in a way that is pro-social. The key - start small and participate! Great advice.

Getting around to reading this and struck by the excellent language of surrender and choice. I am tempted to replace my writing with AI because it is hard for me and I’m not great at it, but I know the only way to get better is to suffer from through. I feel no problem farming out many coding chores to AI because I know what needs to be done and it is an issue of volume, not accuracy or novelty. Still, it’s an evolving dialogue in my work!

This article is talking about hundreds of thousands of armed drones, some autonomous, some not. A truly chilling way in which the future is already here.

This is a great quick read thinking about what the impact on open source software communities has been and will be when contributing code is easier but also less necessary. Helpful as a mirror to think about my own engagement with open source in the past and moving forward. How can I be a more intentional and productive contributor, not just a consumer?