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LLM Use Cases in Political Science
Exploring applications of large language models for measuring ideology and predicting vote choice.

Spatial Machine Learning
Leveraging spatial data and machine learning techniques to map and predict the geographical distribution of political preferences.

Experimental Approaches to Democracy
Investigating the tradeoff between democratic support and institutional safeguards (e.g. party bans).

Causal inference

• Regression discontinuity designs (see here or here)
• Instrumental variable approaches (see here)
• Other natural experiments (see here)

Spatial econometrics

• The design of electoral districts (see here)
• Interfederal cooperation, competition, and redistribution (see here)
• Geographical sorting and the emergence of political actors (here)

Machine Learning and LLMs

• Using LLMs to measure the ideology of heads of government (see here)
• LLMs vs supervised machine learning for electoral predictions (in progress)
• Using spatial machine learning to map pre-industrial regime preferences (in progress)