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Molly Offer-Westort @mollyow.bsky.social · 27/08/2026

It's so useful! And vdV barely touches on cross-fitting, which is why I wanted the tie-in. I also love Kennedy's review, it has made a lot of this material more concrete for me.

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Molly Offer-Westort @mollyow.bsky.social · 26/08/2026

E.g., I also worked in connections to some of the materials that I teach in my causal inference and ML course related to double-debiased ML, including Chernozhukov et al. 2016 and @edwardhkennedy.bsky.social's 2022 review arxiv.org/abs/2203.06469 arxiv.org/abs/1608.00060

arxiv.org

Semiparametric doubly robust targeted double machine learning: a review

In this review we cover the basics of efficient nonparametric parameter estimation (also called functional estimation), with a focus on parameters that arise in causal inference problems. We review bo...

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Molly Offer-Westort @mollyow.bsky.social · 26/08/2026

Clearly, another person reading this book could also use AI to work through the concepts. I found myself really wanting a companion reader to help make connections across chapters and concepts, so that is the goal of this document, to provide structured links and connections to external references.

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Molly Offer-Westort @mollyow.bsky.social · 26/08/2026

I participated in a reading group of Asymptotic Statistics this summer (thanks @bobbygulotty.bsky.social!). The text is very dense and there is not a lot of hand-holding, so I used an AI assistant to write up notes informed by our discussions mollyow.github.io/bloomsday/

mollyow.github.io

Reading Companion for Asymptotic Statistics

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Reposted by Molly Offer-Westort

Political Analysis @polanalysis.bsky.social · 25/06/2026

Currently in FirstView: In “On the Foundations of the Design-Based Approach,” P. M. Aronow, Austin Jang, and @mollyow.bsky.social propose a design-based framework for analyzing randomized trials and survey sampling that avoids strong claims about the data-generating process.

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Reposted by Molly Offer-Westort

Aaron Strauss @aaronstrauss.bsky.social · 13/02/2026

Research Obsession Day 8: A reminder to meet voters where they are, featuring research by @mollyow.bsky.social on persuading voters on climate. Plus: why microtargeting ain't all that. journals.sagepub.com/doi/full/10....

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Molly Offer-Westort @mollyow.bsky.social · 13/01/2026

It does feel like there’s a little fear mongering wrt the power of the terminal, though.

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Molly Offer-Westort @mollyow.bsky.social · 13/01/2026

In both my grad and undergrad classes today we went over responsible use of Claude Code with version control, I think this will be an essential feature of workflow for this generation of PhDs.

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Reposted by Molly Offer-Westort

Research & Politics @respol.bsky.social · 02/03/2025

K. Munger argues that, when an agnostic approach is applied, the goal of prediction is generically impossible. A. Jang, @mollyow.bsky.social, S. Wang & P. M. Aronow situate Munger’s critique in a broader literature and point to ways in which gnosis can facilitate the accumulation of knowledge.

doi.org

Sage Journals: Discover world-class research

Subscription and open access journals from Sage, the world's leading independent academic publisher.

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Reposted by Molly Offer-Westort

Data Science Institute @dsi-uchicago.bsky.social · 07/05/2024

Congratulations Assistant Professor Molly Offer-Westort (@mollyow.bsky.social) on becoming a 2024 Carnegie Corporation of New York Fellow! This fellowship will support Molly Offer-Westort in her work to study how social media platforms impact our democracy

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Molly Offer-Westort @mollyow.bsky.social · 27/02/2024

The 2024 syllabus for my Advanced topics Causal Inference & Machine Learning course is up! @uchicago.bsky.social @dsi-uchicago.bsky.social t.co/3P6nO98aVA

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Molly Offer-Westort @mollyow.bsky.social · 01/09/2023

This is a fantastic opportunity for graduate students working in data science—across a wide range of disciplines. Info session Sept 6. datascience.uchicago.edu/research/pos...

Join the Rising Stars in Data Science VIRTUAL INFO SESSION! Date: Wednesday September 6, 2023. Time: 2-3pm CT. Who: Applicants must be full-time graduate students within 1-2 years of obtaining a PhD, or a current postdoctoral scholar, fellow, or researcher. What: Learn more about the program, hear from the Universities, and ask questions of past program participants.

The Rising Stars in Data Science workshop, hosted November 13-14 by the University of Chicago in collaboration with the University of California San Diego, focuses on celebrating and fast tracking the careers of exceptional data scientists at a critical inflection point in their career: the transition to postdoctoral scholar, research scientist, industry research position, or tenure track position. Over the first three years of Rising Stars at UChicago, the annual workshop has hosted a total of 91 Rising Stars from nearly 40 institutions.

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