Week 1: Science from Particles to People

DSAN 5650: Causal Inference for Computational Social Science
Summer 2026, Georgetown University

Jeff Jacobs

jj1088@georgetown.edu

Wednesday, May 20, 2026

Schedule

Today’s Planned Schedule:

	Start	End	Topic
Lecture	6:30pm	7:00pm	Quick Hello Hi Everyone Style Intro →
	7:00pm	7:25pm	science \leadsto Social Science “Phase Transition” →
	7:25pm	7:50pm	Motivating Examples I: Social Science →
Break!	7:50pm	8:00pm
	8:00pm	8:30pm	Motivating Examples II: Causal Inference →
	8:30pm	9:00pm	Course Logistics →

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Who Am I? Why Is Georgetown Having Me Teach This?

Prof. Jeff Introduction!

• Born in NW DC → high school in Rockville, MD
• University of Maryland: Computer Science, Math, Econ

The World Outside of DC

Studied abroad in Beijing (Peking University/北大) → internship with Huawei in Hong Kong (HKUST)

Stanford, MS in Computer Science

Research Economist, UC Berkeley

Columbia, PhD in Political Economy

Why Is Georgetown Having Me Teach This?

Fig 1: Years spent questing in dungeons of academia

• Quanty things \leadsto PhD in Political Economy
• PhD exam major: Political Philosophy
• PhD exam minor: International Relations (“How to Do Things with Translations”)
• Brain-changing Research Fellowships at…
• Santa Fe Institute: dedicated to the multidisciplinary study of complex systems: physical, computational, biological, social
• Centre for the Study of the History of Political Thought, Queen Mary University of London (QMUL): New approaches to the history of political thought [Quentin Skinner, “Cambridge School”] have changed how we study ideas from the past and their relevance to contemporary politics. The focus of the Centre is to explore [that sort of thing then, innit guv’nor!].

Dissertation (NLP x History)

“Our Word is Our Weapon”: Text-Analyzing Wars of Ideas from the French Revolution to the First Intifada

(IR Part) Wars of Ideas I: Cold War

• Cold War arms shipments (SIPRI) vs. propaganda (Печать СССР): here, to 🇪🇹

(Middle East Part) Wars of Ideas II: First Intifada, 1987-1993

Research Nowadays

• Most cited paper: “Monopsony in Online Labor Markets” (Uses Double-Debiased ML for Causal Inference!)
• Most recent paper: “Operationalizing Freedom as Non-Domination in the Labor Market” (Cambridge U Press)
• Rarely cited paper but often-thought-about obsession: “How To Do Things With Translations”
• Related thing you can buy in a bookstore: [Editorial board for new translation of] Capital, Vol. 1 by Karl Marx (Princeton U Press)

But Now… Teaching!

• Growth mindset: “I can’t do this” \leadsto “I can’t do this yet!”
• Think of anything you’re able to do… There was a point in life when you didn’t know how to do it! What happened? Your brain established and/or rearranged neural pathways as you struggled with it!
• How does this neural re-arrangement work? One “cheatcode” is spaced repetition:

Image source

Lil Wayne on Spaced Repetition

Fig 2: From The Carter (Documentary)

Maria Montessori on Your Final Project

Our teaching should be governed, not by a desire to make students learn things, but by the endeavor to keep burning within them that light which is called curiosity. (Montessori 1916)

• To this end: your final project is to explore some potential causal linkage from X to Y (more later!)
• The sole requirement is: sufficient curiosity to serve as fuel for your journey from associational world to causal world

Earning Your Grade: Effort + Growth Mindset!

Because you learn to          by         ing, the more         ing you do [adapted to where you’re at, background-wise, time-outside-of-class-wise], the better grade you can get:

• For each          you do [“good faith attempt”], you receive one ✅s
• If it looks good as-is, with “good” defined as “demonstrates understanding of the relevant material [to instructors, in dialogue with students]”, you receive a second ✅
• Otherwise you can earn this second ✅ by re-trying until understanding is achieved

✅s convert to points via (required) main quests, (technically not required) sidequests:

Main Quest	#	Completion?	Understanding?
Homework (🔲🔲)	4	🔲🔲🔲🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲🔲🔲🔲
Midterm (🔲🔲)	1	🔲🔲	🔲🔲
Project (🔲🔲🔲)	1	🔲🔲🔲	🔲🔲🔲
Meeting (🔲)	2	🔲
Total = 27 🔲s

Side Quest
Lab (🔲)	8	🔲🔲🔲🔲	🔲🔲🔲🔲
Reading (🔲)	8	🔲🔲🔲🔲	🔲🔲🔲🔲
Meeting (🔲)	2	🔲
Total = 17 🔲s
Combined = 44 🔲s

0.5	1.0	1.5	2.0	2.5	3.0	3.5	4.0
🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲	🔲🔲🔲🔲🔲
🏃‍♀️			🙇‍♀️🧘🧠💪 ↓ 💪🧠🧘🙇‍♀️		🏃‍♀️
✅✅✅✅✅	✅✅✅✅✅	✅✅✅✅✅	✅✅✅✅✅	✅✅✅✅✅	✅✅✅✅✅	✅✅✅✅✅	✅✅✅✅✅

The Science \leadsto Social Science “Phase Transition”

Today’s Demo: Schelling’s Attendance Model

Course Logistics

JupyterHub

https://guhub.io

Image source

References

Montessori, Maria. 1916. Spontaneous Activity in Education: A Basic Guide to the Montessori Methods of Learning in the Classroom. Lulu Press. https://books.google.com?id=c0PYvAEACAAJ.