UNGA Voting Ideal Points (Bailey-Strezhnev-Voeten)联合国大会投票理想点 (Bailey-Strezhnev-Voeten)

This dataset provides annual ideal-point estimates for virtually all UN member states from 1946 to 2023, derived from roll-call voting records in the UN General Assembly (UNGA). Using a dynamic Bayesian item-response theory (IRT) model, each country-year is assigned a latent position on a single dimension: higher values indicate alignment with the United States and Western democracies, while lower values indicate alignment with the developing-world consensus. The dataset also reports bilateral voting-agreement scores with major powers (US, China, Russia).

Developed by Michael A. Bailey, Anton Strezhnev, and Erik Voeten, this is the standard benchmark for measuring state foreign-policy preferences in international organizations research. It is a direct indicator of institutional polarization risk: a country's ideal point captures how closely it aligns—or diverges—from the dominant blocs in multilateral settings, signalling potential exposure to bloc-based sanctions or diplomatic isolation.

本数据集利用联合国大会（UNGA）历届记名投票，通过动态贝叶斯项目反应理论（IRT）模型，估计 1946-2023 年几乎所有联合国会员国的年度理想点（ideal point）。理想点值越高，表明该国立场越接近美国及西方民主国家；值越低，则表明更趋近于发展中国家阵营共识。数据集同时提供各国与美国、中国、俄罗斯的双边投票一致度（Agreement Score）。

该数据集由 Bailey、Strezhnev 与 Voeten 开发，是国际组织研究中衡量国家外交政策偏好的权威指标，直接反映制度阵营化风险——理想点可量化目标国在多边场合的阵营归属，预判其面临集团化制裁或外交孤立的潜在风险。