Ryan Briggs

@ryancbriggs.net

Raising kids & bread & grant money. Cleaning data & diapers & fish. EA (bed nets, not light cone). Social scientist. typos. twitter.com/ryancbriggs

When I was visiting my mom she gave me some bottles of alcohol that she was never going to drink, and I just opened this one and turns out it’s maple syrup

What looks like a bottle of tequila

It has been embarrassing reading this and similar critiques, because they accuse the report of not doing things that it manifestly does do (like adjusting for time to accumulate citations). I hope everyone involved is more careful in their regular work. You hurt your causes by flubbing this hard.

Alex Usher@alexusherhesa.bsky.social · 2w ago

Here is my letter to the MacDonald Laurier Institute on the subject of their appalling research. Use as you will. I recommend sending something of your own, though. And if you know anyone associated with MLI - and Board directors, say - send it to them, too.

Incredible. When E—n M—k & his crew obliterated USAID in a weekend, they deleted a vast trove of publicly-funded knowledge: the Development Experience Clearinghouse. A Canadian high school student (!) happened to have downloaded the entire thing for a project. AidData has now posted it for all.

Before reimagining development data, remember what we’ve learned

Why we’re publishing a free, searchable, and ungated archive featuring a quarter-century of USAID evaluation reports.

aiddata.org

I’m late to this but the ninja creami is viral for good reason. It’s wild how good of a product you can get out of it, including vegan ice cream (almond milk + coconut cream).

We are seeing similar at RP. It's not just AI. Also a huge increase in Chinese social science. Which is often very good. But AI slop is flooding the system. One author with 30 submissions in a month... now they "could" be super productive.... or it could be AI slop.

Ryan Briggs@ryancbriggs.net · 2mo ago

Spoke to an editor of a good social science journal who reported submission volume is now 400% higher than during Covid. He entirely blames AI.

I won’t get into the data or analysis here (yet), but I’m very confident that lower ranked journals do not publish more null results than higher ranked ones. I looked across 11 disciplines and all have this (lack of a) pattern.

This was a fun paper. We analyze results from a global survey of development studies (DS) profs and find that the income group of their country doesn't explain much about their views on DS. Instead, their discipline is huge.

Development Studies Association @devcomms.bsky.social · 3mo ago

In a new @eadi.bsky.social reflection paper, @ryancbriggs.net & @andypsumner.bsky.social, @kings-sga.bsky.social explore what drives deep disagreements in development studies—and point to the “disciplinary baggage” of PhD training. Read more: buff.ly/ASH1bL9

New blog post: Evaluating Dr. Cuddy’s Claim that the Debunking of Power Posing is a Myth. daniellakens.blogspot.com/2026/05/eval... On an AI generated description of a non-existent study, incorrectly citing findings from studies, and the importance of scientific criticism.

Evaluating Dr. Cuddy’s Claim that the Debunking of Power Posing is a Myth

In this blog post I will analyse the arguments that Dr. Amy Cuddy provided in a blog post “The "Power Posing Was Debunked" Myth: What the Re...

daniellakens.blogspot.com

In the Fall I'll be teaching a new MA-level methods course entitled "Applied Statistical Evaluation of Development Projects". It will be 12 weeks, in R, and aimed around RCT evaluations. This is a draft outline. What am I missing? What seems redundant?

1. Course Introduction and Setup
 Course overview; installing RStudio; introduction to causal inference; ModernDive Chapters 1–2 for newcomers.
2. Data, Tidy Data, Wrangling, and Visualization
 Core R skills for importing, cleaning, reshaping, summarizing, and visualizing evaluation data.
3. Sampling, Uncertainty, and Inference 
Sampling variation, confidence intervals, hypothesis testing, and the logic of statistical uncertainty.
4. Difference in Means as Regression 
Equivalence between difference-in-means estimates and lm(y ~ treat); ATE as the treatment coefficient; control mean as the intercept; covariates for precision gains; simulations and re-analysis of Karlan–List charity data.
5. Interactions and Treatment Effect Heterogeneity 
Interaction terms, subgroup analysis, heterogeneous effects; simulations, Karlan–List charity data, and Thornton HIV data.
6. Standard Errors, Power, and Research Design 
Bias, variance, RMSE, clustering, power analysis, and how underpowered studies contribute to selection on significance and inflated estimates.
7. Noncompliance, Take-Up, and Instrumental Variables 
ITT, TOT, LATE, compliers etc, and randomized encouragement designs; Thornton HIV testing incentives; reading from The Effect Chapter 19 or Causal Inference: The Mixtape IV chapter.
8. Spillovers, Externalities, and Peer Effects
 How spillovers can bias experimental estimates; identifying, measuring, and interpreting spillover effects in development evaluations.
9. Pre-Analysis Plans, Measurement, and Cost-Effectiveness
 PAPs, outcome measurement, measurement error, index construction, and basic cost-effectiveness analysis.
10. Meta-Analysis and Evidence Aggregation 
Fixed-effect and random-effects meta-analysis; Bayesian meta-analysis using baggr; interpreting accumulated evidence across studies.
11. Case Study: Deworming Evidence I
 Critical re-analysis of the main deworming results; statistical interpretation; cost-effectiveness implications.

An interesting EA forum post that is an anonymized slack chat about GiveWell and EA-style CE analysis: "across EA cost-effectiveness analyses, much more typically goes toward estimating the effect than estimating the costs." forum.effectivealtruism.org/posts/ru3wyS...

Global Health Charity Founders on GiveWell, Evidence Action, and M+E — EA Forum

The following is a lightly edited and anonymized transcript of a discussion among charity founders, researchers, and funders in Ambitious Impact’s Sl…

forum.effectivealtruism.org

I'll be teaching a grad methods class focused on experiments in the fall for a development studies dept. I'm looking for published development RCTs. Ideally they would have: 1. replication packages in R, or 2. fairly simple code I could rewrite in R. Anyone have recommendations?

June 2024: The latest general-purpose LLMs could not count the r's in strawberry. July 2025: The latest general-purpose LLMs get gold in the International Math Olympiad. May 2026: The latest general-purpose LLM solve an 80 year old problem, one of the "best-known questions in combinatorial geometry"

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OpenAI has used a "general purpose reasoning model" to disprove that the square grid type construction is the best solution to the planar unit distance problem. I am sure the "AI is completely useless" crowd will now change their ways, right?

An OpenAI model has disproved a central conjecture in discrete geometry

An OpenAI model solved the 80-year-old unit distance problem, disproving a major conjecture in discrete geometry and marking a milestone in AI-driven mathematics.

openai.com