Let LLM help you achieve your regression with Stata. Evolve from reg monkey to causal thinker.
A (RLlib-compatible) multi-agent environment for probing the boundaries of MARL and social sciences
Python implementation of a toolkit for researchers studying electoral polarization. Features ideological and affective polarization analysis, issue salience modeling, and comprehensive statistical validation following Ginzburg's (2024) framework. Jupyter Notebook based.
This project aims to use Large Language Models (LLMs) to assist with Grounded Theory analysis. The entire workflow uses "Open Source Cases" as the subject of study. Through several automated stages, it extracts causal relationships from the original case texts and progressively builds a theoretical model.
Course website for PS211 at Boston University (Fall 2025). CC BY-NC-SA 4.0. Built with Quarto.
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