Bolashak Fellows at Johns Hopkins SAIS · Two-Day Seminar 2026

AI & Machine Learning for Governance & Policy Research

Trees, forests, and neural networks on governance data; dictionaries and large language models on Federal Reserve, IMF, and World Bank documents. Everything runs in claude.ai — no installation, no code.

Upload the data Ask in plain English Interpret the output Verify every claim
Roumen Vesselinov, PhD
Roumen Vesselinov, PhD
Where to go

Four workspaces for the seminar

Each opens in its own page. The datasets and documents are yours to download; the Day 1 and Day 2 pages put ready-to-run prompts next to a link into Claude.

23
DATA

Quality of Government datasets

Twenty-three country-year datasets built from the University of Gothenburg's QoG data — each with a one-click data and description download.

Open datasets →
32
TEXT

Policy documents

Central bank statements, IMF and World Bank reports, rating actions, and communiqués — the raw material for the Day 2 text-analysis labs.

Open documents →
1
MACHINE LEARNING

Day 1 agenda & slides

Prediction on governance data: decision trees, random forests, and neural networks. Full schedule plus every Day 1 slide deck to download.

Open Day 1 →
2
AI & POLICY TEXT

Day 2 agenda & slides

Turning documents into data: dictionary sentiment and large language models on real Fed, IMF, and World Bank text. Schedule plus all Day 2 decks.

Open Day 2 →
HANDS-ON

Labs for Day 1 & 2

The working space: copy a ready-made prompt, open Claude in a new tab, run it on your file, then interpret and verify the result.

Open the labs →
2 days9:00–12:00 & 1:00–5:00
1 toolclaude.ai, free tier
0 codeupload, ask, interpret, verify