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Political Analysis @polanalysis.bsky.social · 1d

While some answers have only a weak semantic connection to questions, they are generally relevant. They also find meaningful correlations between the quality of answers and the party affiliation of the MPs asking the questions. You can read the paper here: www.cambridge.org/core/journal...

Measuring the Quality of Answers in Political Q&As with Large Language Models | Political Analysis | Cambridge Core

Measuring the Quality of Answers in Political Q&As with Large Language Models

www.cambridge.org

Political Analysis @polanalysis.bsky.social · 1d

Currently in FirstView: In “Measuring the Quality of Answers in Political Q&As with Large Language Models,” @rmichaelalvarez.bsky.social and Jacob Morrier develop an approach for measuring the quality of answers in Q&A sessions using data from the Question Period in the Canadian House of Commons.

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Political Analysis @polanalysis.bsky.social · 5d

The authors discuss diagnostic tools to identify problems with estimation methods. Using two applied examples, they recommend researchers consider many estimation methods and model specifications and encourage open reporting. You can read the paper here: www.cambridge.org/core/journal...

What to Observe When Assuming Selection on Observables | Political Analysis | Cambridge Core

What to Observe When Assuming Selection on Observables

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Political Analysis @polanalysis.bsky.social · 5d

Currently in FirstView: In “What to Observe When Assuming Selection on Observables,” Kevin M. Quinn, Guoer Liu, Lee Epstein, and Andrew Martin clarify how most estimators justified by a selection-on-observables assumption are special cases of a general weighting estimator.

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Political Analysis @polanalysis.bsky.social · 8d

Counter to expectations, they find that elites are more likely to schedule an interview when outreach comes from a female alias. This suggests that qualitative interviews may be limited by gender biases. You can read the paper here: www.cambridge.org/core/journal...

Accessibility and Equity in the Research Process: Gender Bias in Elite Interview Recruitment | Political Analysis | Cambridge Core

Accessibility and Equity in the Research Process: Gender Bias in Elite Interview Recruitment

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Political Analysis @polanalysis.bsky.social · 8d

Currently in FirstView: In “Accessibility and Equity in the Research Process: Gender Bias in Elite Interview Recruitment,” Margaret A. T. Kenney and John Salchak study how researcher identity affects the research process. Specifically, they look at how this influences elite interview recruitment.

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Political Analysis @polanalysis.bsky.social · 9d

(2/2) @zengchen.bsky.social, @eliasdinas.bsky.social, @redatamtam.bsky.social, and more! Most papers are currently open access. You can read the new issue here: www.cambridge.org/core/journal...

Political Analysis: Volume 33 - Issue 4 | Cambridge Core

Cambridge Core - Political Analysis - Volume 33 - Issue 4

www.cambridge.org

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Political Analysis @polanalysis.bsky.social · 9d

The latest issue of PA is out now. We have a great collection of papers by @yamilrvelez.bsky.social, @sysilviakim.bsky.social, @mattblackwell.bsky.social, @sophieehill.bsky.social, @dwlee.bsky.social, @melissazrogers.bsky.social, @kaipingchen.bsky.social, @samuelbaltz.bsky.social (1/2)

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Political Analysis @polanalysis.bsky.social · 15d

This method tightens non-parametric partial identification bounds in settings where outcomes are endogenously missing, enabling more informative and assumption-agnostic inference about treatment effects. You can read the full paper here: www.cambridge.org/core/journal...

Generalizing Trimming Bounds for Endogenously Missing Outcome Data Using Random Forests | Political Analysis | Cambridge Core

Generalizing Trimming Bounds for Endogenously Missing Outcome Data Using Random Forests

www.cambridge.org

Political Analysis @polanalysis.bsky.social · 15d

Currently in FirstView: “Generalizing Trimming Bounds for Endogeneously Missing Outcome Data Using Random Forests." @cdsamii.bsky.social, Ye Wang, @jlzhou.bsky.social‬ present a partial identification approach that avoids strong assumptions. This is illustrated using a simulation and replication.

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Political Analysis @polanalysis.bsky.social · 22d

Using a Monte Carlo simulation, the authors explore conditions where the bracketing property holds and demonstrate that treatment effects cannot be bracketed when unobserved heterogeneity is correlated with the regressors. You can read the full paper here: www.cambridge.org/core/journal...

Fixed Effects, Lagged Dependent Variables, and Bracketing: Cautionary Remarks | Political Analysis | Cambridge Core

Fixed Effects, Lagged Dependent Variables, and Bracketing: Cautionary Remarks

www.cambridge.org

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Political Analysis @polanalysis.bsky.social · 22d

Currently in FirstView: “Fixed Effects, Lagged Dependent Variables, and Bracketing: Cautionary Remarks” by Matei Demetrescu, Manuel Frondel, Lukas Tomberg, and Colin Vance investigates a bracketing property used to yield bounds on treatment effects from fixed effects and lagged DV models.

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Reposted by Political Analysis

Cambridge University Press Political Science & IR @cambup-polsci.cambridge.org · 27d

#OpenAccess from @polanalysis.bsky.social -

Generative AI and Topological Data Analysis of Longitudinal Panel Data - cup.org/460fgFn

- Badredine Arfi

#FirstView

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Political Analysis @polanalysis.bsky.social · Sep 2

The authors discuss several potential uses for eye tracking data, including identifying inattention in surveys and measuring an item’s importance in a decision. They also provide starter code for analyzing eye tracking data. Read the full paper here: www.cambridge.org/core/journal...

Attention and Political Choice: A Foundation for Eye Tracking in Political Science | Political Analysis | Cambridge Core

Attention and Political Choice: A Foundation for Eye Tracking in Political Science

www.cambridge.org

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Political Analysis @polanalysis.bsky.social · Sep 2

Currently in FirstView: In “Attention and Political Choice: A Foundation for Eye Tracking in Political Science,” Libby Jenke and Nicolette Sullivan explain what eye tracking allows researchers to measure and how these measures are relevant to political science questions.

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Reposted by Political Analysis

Cambridge University Press Political Science & IR @cambup-polsci.cambridge.org · Aug 27

#OpenAccess from @polanalysis.bsky.social -

Decomposing Network Influence: Social Influence Regression - cup.org/3UKZjwv

"provides a statistical mechanism for explaining actor influence based on observable traits"

- Shahryar Minhas & Peter D. Hoff

#FirstView

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Political Analysis @polanalysis.bsky.social · Aug 26

They validate their findings using expert-, manifesto-, and poll-based estimates and show that ideological scores produced by LLMs closely map those obtained through expert-based evaluation. You can read the full paper here: www.cambridge.org/core/journal...

Mapping (A)Ideology: A Taxonomy of European Parties Using Generative LLMs as Zero-Shot Learners | Political Analysis | Cambridge Core

Mapping (A)Ideology: A Taxonomy of European Parties Using Generative LLMs as Zero-Shot Learners

www.cambridge.org

Political Analysis @polanalysis.bsky.social · Aug 26

Currently in FirstView: “Mapping (A)Ideology: A Taxonomy of European Parties Using Generative LLMs as Zero-Shot Learners.” Riccardo Di Leo, @zengchen.bsky.social, @eliasdinas.bsky.social‬, and @redatamtam.bsky.social see if ML can obtain measures of party ideology that match the validity of experts.

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Political Analysis @polanalysis.bsky.social · Aug 20

They use moral content in tweets as a case study, highlighting the vec-tionary's ability to process texts missed by conventional dictionaries and its ability to produce measurements more aligned with crowdsourced human assessments. You can read the paper here: www.cambridge.org/core/journal...

Constructing Vec-tionaries to Extract Message Features from Texts: A Case Study of Moral Content | Political Analysis | Cambridge Core

Constructing Vec-tionaries to Extract Message Features from Texts: A Case Study of Moral Content

www.cambridge.org

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Political Analysis @polanalysis.bsky.social · Aug 20

Currently in FirstView: “Constructing Vec-tionaries to Extract Message Features from Texts: A Case Study of Moral Content.” @kaipingchen.bsky.social and and colleagues introduce “vec-tionaries” which are embedding-based tools for measuring latent features of messages.

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Political Analysis @polanalysis.bsky.social · Aug 15

They show that PCRDs estimate the local average treatment effects for districts, not the effects of politician attributes. The paper also addresses confusion regarding PCRDs and offers tools for researchers using PCRDs. You can read the full paper here: www.cambridge.org/core/journal...

Seeing Like a District: Understanding What Close-Election Designs for Leader Characteristics Can and Cannot Tell Us | Political Analysis | Cambridge Core

Seeing Like a District: Understanding What Close-Election Designs for Leader Characteristics Can and Cannot Tell Us

www.cambridge.org

Political Analysis @polanalysis.bsky.social · Aug 15

Currently in FirstView: In “Seeing Like a District: Understanding What Close-Election Designs for Leader Characteristics Can and Cannot Tell Us,” Andrew Bertoli and Chad Hazlett examine the limitations of politician characteristic regression discontinuity (PCRD) designs.

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Political Analysis @polanalysis.bsky.social · Aug 8

They find that F-tests can mask weak instruments and understate the uncertainty surrounding estimates from two-stage least squares. IV estimates are often larger than OLS estimates, whose biases they are designed to correct. The paper is open access here: www.cambridge.org/core/journal...

How Much Should We Trust Instrumental Variable Estimates in Political Science? Practical Advice Based on 67 Replicated Studies | Political Analysis | Cambridge Core

How Much Should We Trust Instrumental Variable Estimates in Political Science? Practical Advice Based on 67 Replicated Studies - Volume 32 Issue 4

www.cambridge.org

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Political Analysis @polanalysis.bsky.social · Aug 8

We are pleased to announce the 2025 Editors’ Choice Award for the paper “How Much Should We Trust Instrumental Variable Estimates in Political Science? Practical Advice Based on 67 Replicated Studies” by @apoorvalal.com‬, @maclockhart.bsky.social, @yiqingxu.bsky.social‬, and @garyzu.bsky.social.

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Reposted by Political Analysis

Cambridge University Press Political Science & IR @cambup-polsci.cambridge.org · Aug 7

The latest winning article of the @polanalysis.bsky.social Editors' choice has been announced, find out more - cup.org/4551W22

The articles represent papers that the Editors see as providing an especially significant contribution to political methodology.

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