Political Analysis

The October 2026 issue of Political Analysis (Volume 34, Issue 4) is out, and every article is open access. Eight papers on protest voting in Congress, coalition governments, conjoint designs, Gaussian processes, vision-language models, and more. Highlights in the thread below.

Letter: Jonathan Colner shows how free computer vision tools can extract text sections from poorly formatted PDFs. Pulling agenda items from city council minutes took about an hour per city vs. about 31 hours by hand, and closely matched two ground-truth datasets. doi.org/10.1017/pan.2025.10006

The October 2026 issue of Political Analysis (Volume 34, Issue 4) is out, and every article is open access. Eight papers on protest voting in Congress, coalition governments, conjoint designs, Gaussian processes, vision-language models, and more. Highlights in the thread below.

Cho, Kim & Hazlett: standard methods pick one best-fitting model and miss the uncertainty from extrapolation. Gaussian processes keep the range of plausible fits, so intervals widen past the edge of the data. Shown for poor overlap, interrupted time series, and RD. doi.org/10.1017/pan.2026.10032

The October 2026 issue of Political Analysis (Volume 34, Issue 4) is out, and every article is open access. Eight papers on protest voting in Congress, coalition governments, conjoint designs, Gaussian processes, vision-language models, and more. Highlights in the thread below.

Why do some coalitions collapse sooner? In “A Multilevel Model for Coalition Governments,” Benjamin Rosche accounts for parties that join many governments and finds coalitions whose parties rely more on member funding end sooner, driven most by less cohesive parties. doi.org/10.1017/pan.2026.10039

The October 2026 issue of Political Analysis (Volume 34, Issue 4) is out, and every article is open access. Eight papers on protest voting in Congress, coalition governments, conjoint designs, Gaussian processes, vision-language models, and more. Highlights in the thread below.

Why do standard models rank the Squad as moderate Democrats? In “Accounting for Protest Voting in the U.S. Congress,” Anthony Fowler and Jeffrey B. Lewis show that once protest votes are accounted for, the Squad are among the most liberal House members. doi.org/10.1017/pan.2026.10037

Currently in FirstView: In “Let Them Eat Pie: Addressing Sample Selection in Multiparty Elections,” Ali Kagalwala, @tmqm.bsky.social, Guy Whitten, and Yongzhi Xu introduce a novel maximum likelihood approach that accounts for the biases that come from sample selection in a compositional setting.

Currently in FirstView: In “The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information,” Clara Bicalho, Adam Bouyamourn, and Thad Dunning show how balance tests can lead to false conclusions and develop tests that upweight covariates associated with outcomes.

Currently in FirstView: In “Monotone Ecological Inference,” Hadi Elzayn, @jacobsgoldin.bsky.social, Cameron Guage, Daniel Ho, and Claire Morton characterize the biases of, and relationships among ecological inference (EI) estimators for identifying group means and differences.

Currently in FirstView: In “On the Foundations of the Design-Based Approach,” P. M. Aronow, Austin Jang, and @mollyow.bsky.social propose a design-based framework for analyzing randomized trials and survey sampling that avoids strong claims about the data-generating process.

Currently in FirstView: In “Post-Treatment Problems: What Can We Say about the Effect of a Treatment among Sub-Groups Who (Would) Respond in Some Way?,” Chad Hazlett, Nina McMurry, and Tanvi Shinkre propose the treatment reactive average causal effect (TRACE).

Currently in FirstView: In “Estimating Treatment Effects on Proportions with Synthetic Controls,” @bogatyrev.bsky.social and @lstoetze.bsky.social examine synthetic control methods (SCMs) and make the case for jointly estimating synthetic controls across multiple compositional outcomes.

Currently in FirstView: In “Improving Small-Area Estimates of Public Opinion by Calibrating to Known Population Quantities,” @wpmarble.bsky.social and Josh Clinton provide a framework for incorporating known population data to improve estimates of small subgroups in MRP models.

Currently in FirstView: In “Text as Behavior,” @owasow.bsky.social proposes using features of open-ended tasks to study text as behavior. Stats like the number of characters can approximate effort and significantly improve estimation.

Currently in FirstView: In “Democracy Manifest or Democracy Latent? A Unified Framework for Identifying Regime Types and Transitions,” @omerorsun.bsky.social and Muhammet A. Bas develop and validate a framework to study regimes that addresses measurement uncertainty and missing data.

Currently in FirstView: In “Using Multilingual Language Technology to Classify Open-Ended Survey Responses: Conceptions of Democracy in a Cross-Cultural Survey Setting,” S. Dahlberg, L. Dürlich, S. Axelsson, Y. Zhao, and J. Nivre examine the use of LMs in analyzing open-ended survey responses.

Currently in FirstView: In “Adaptive Randomization in Conjoint Survey Experiments,” @jennahgosciak.bsky.social, @dmolitor.bsky.social, and @ianlundberg.bsky.social develop an adaptive design for conjoint experiments that summarizes the range of effects of one attribute as a function of all others.

Currently in FirstView: In “From Faces to Politics: Vision-Language Models (Sometimes) Link Visual Demographic Characteristics to Ideological Labels,” S. Jeon, M. Lee, @jacobmontgomery.bsky.social, and @calvinklai.bsky.social ask how models use demographics as shortcuts for ideological attribution.

Currently in FirstView: In “Correcting Nonignorable Nonresponse Bias in Turnout Estimation Using Callback Data,” Xinyu Li, Naiwen Ying, Kendrick Qijun Li, Xu Shi, and Wang Miao look at the role of callback data as a way of adjusting for nonresponse bias in estimating voter turnout.

Currently in FirstView: In “Inference at the Data’s Edge: Gaussian Processes for Estimation and Inference in the Face of Extrapolation Uncertainty,” Soonhong Cho, Doeun Kim, and Chad Hazlet illustrate the value of Gaussian Processes (GPs) for capturing counterfactual uncertainty. 

Currently in FirstView: In “A Multilevel Model for Coalition Governments: Uncovering Party-Level Dependencies Within and Between Governments,” Benjamin Rosche extends the Multiple Membership Multilevel Model to represent the multilevel structure of coalition government data.

Currently in FirstView: In “Accounting for Protest Voting in the U.S. Congress,” Anthony Fowler and Jeffrey B. Lewis estimate a model of congressional voting that allows for non-ideological protest voting. This has significant implications for roll-call estimates of ideology.

Currently in FirstView: In “A Dynamic Discrete Choice Approach to Attitude Stability and Constraint,” @alecia-nepaul.bsky.social and Steven Stern introduce a discrete choice framework to identify influential attitudes within attitude systems.

Currently in FirstView: in “Refining Gamson: The Isometric Log-Ratio Transformation and Portfolio Proportionality in Multiparty Governments,” Lanny Martin and Georg Vanberg propose the isometric log-ratio (ILR) as an alternative to the additive log-ratio (ALR) transformation.

Currently in FirstView: in “Modeling Hierarchical Spatial Interdependence for Limited Dependent Variables,” Ali Kagalwala and Kankyeul Yang propose a class of spatial hierarchical models with binary outcomes to account for spatially independent and spatially dependent unobserved group effects.