Skill UI

A comprehensive guide for defending the methodological rigor of academic manuscripts, particularly for top-tier journals. It covers advanced causal identification techniques (DID, IV, RDD) for quantitative work, robust experimental design, and detailed strategies for process tracing and case selection in qualitative research. The core focus is ensuring the design is highly reproducible and clearly addresses potential confounding variables and rival explanations.

This guide provides comprehensive best practices for packaging and documenting NLP research artifacts (datasets, models, prompts, etc.) for academic submission (e.g., NAACL/ARR). It emphasizes rigorous provenance tracing, ensuring reproducibility, and ethically handling sensitive data, particularly community-owned or indigenous language resources.

This guide helps scholars rigorously defend the methodological design of academic papers, particularly in International Relations and Comparative Politics. It covers advanced techniques such as process tracing, case selection logic, quantitative cross-national panel data analysis (DID, IV, RDD), and experimental design. Its core purpose is to strengthen causal claims by explicitly addressing selection bias, defining scope conditions, and ruling out major rival explanations.