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Existing approaches to estimating politicians' latent positions along specific dimensions often fail when relevant data is limited.
“Fine-Tuning Language Models from Human Preferences”
Daniel. Ziegler, Nisan Stiennon, Jeffrey Wu, Tom. Brown, Alec Radford, Dario Amodei, Paul Christiano and Geoffrey Irving · 1909
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“Rank Analysis of Incomplete Block Designs: The Method of Paired Comparisons”
Ralph Bradley and Milton. Terry · 1952
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“A Spatial Model for Legislative Roll Call Analysis”
Keith. Poole and Howard Rosenthal · 1985
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“Ideology and Congress: A Political Economic History of Roll Call Voting”
Keith. Poole and Howard Rosenthal · 1997
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“Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators”
James. Heckman and James. Snyder · 1997
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“Are Women More Likely to Vote for Women’s Issue Bills than Their Male Colleagues?”
Michele. Swers · 1998
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“Pivotal Politics: A Theory of U.S. Lawmaking”
Keith Krehbiel · 1998
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“Candidate Positioning in U.S. House Elections”
Stephen Ansolabehere, James. Snyder and Charles Stewart · 2001
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“Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999”
Andrew. Martin and Kevin. Quinn · 2002
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“Beyond the Median: Voter Preferences, District Heterogeneity, and Political Representation”
Elisabeth. Gerber and Jeffrey. Lewis · 2004
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“The Statistical Analysis of Roll Call Data”
Joshua Clinton, Simon Jackman and Douglas Rivers · 2004
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“Setting the Agenda: Responsible Party Government in the U.S. House of Representatives”
Gary. Cox and Mathew. McCubbins · 2005
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“Beyond the Roll-Call Arena: The Determinants of Position Taking in Congress”
Benjamin Highton and Michael. Rocca · 2005
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“Spatial Models of Parliamentary Voting”, Analytical Methods for Social Research
Keith. Poole · 2005
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“Language Models are Few-Shot Learners”
Tom. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever and Dario Amodei · 2005
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“A Scaling Model for Estimating Time-Series Party Positions from Texts”
Jonathan. Slapin and Sven-Oliver Proksch · 2008
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“Economic Inequality and Political Representation”
Larry. Bartels · 2009
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“Measuring Bias and Uncertainty in DW-NOMINATE Ideal Point Estimates via the Parametric Bootstrap”
Royce Carroll, Jeffrey. Lewis, James Lo, Keith. Poole and Howard Rosenthal · 2009
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“Measuring Legislative Preferences” Publisher Copyright: © The several contributors 2011. All rights reserved
Nolan McCarty · 2011
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“Testing the power of arguments in referendums: A Bradley–Terry approach” Special Symposium: Germany’s Federal Election September 2009
Peter Loewen, Daniel Rubenson and Arthur Spirling · 2011
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“The Ideological Mapping of American Legislatures”
Boris Shor and Nolan McCarty · 2011
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“Bradley-Terry Models in R: The BradleyTerry2 Package”
Heather Turner and David Firth · 2012
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“Validating Estimates of Latent Traits from Textual Data Using Human Judgment as a Benchmark”
Will Lowe and Kenneth Benoit · 2013
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“Mapping the Ideological Marketplace”
“Racial or Spatial Voting? The Effects of Candidate Ethnicity and Ethnic Group Endorsements in Local Elections”
Cheryl Boudreau, Christopher. Elmendorf and Scott. MacKenzie · 2019
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“Partisan Associations of Twitter Users Based on Their Self-Descriptions and Word Embeddings” Presented at APSA 2019, 2019
Patrick. Wu, Walter. Mebane Jr., Logan Woods, Joseph Klaver and Preston Due · 2019
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“Word Embeddings for the Analysis of Ideological Placement in Parliamentary Corpora”
Ludovic Rheault and Christopher Cochrane · 2019
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“The Illustrated GPT-2 (Visualizing Transformer Language Models)” Retrieved from https://jalammar.github.io/illustrated-gpt2/ , 2019
Jay Alammar · 2019
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“News Sharing on Social Media: Mapping the Ideology of News Media Content, Citizens, and Politicians”
Gregory Eady, Richard Bonneau, Joshua. Tucker and Jonathan Nagler · 2020
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Adam Bonica · 2014
Cited alongside, same era.
“ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients”
Seongho Kim · 2015
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“Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data”
Pablo Barberá · 2015
Cited alongside, same era.
“Substance and Change in Congressional Ideology: NOMINATE and Its Alternatives”
Devin Caughey and Eric Schickler · 2016
Cited alongside, same era.
“Database on Ideology, Money in Politics, and Elections”, Available at https://data.stanford.edu/dime , 2016
Adam Bonica · 2016
Cited alongside, same era.
“Opting Out of Congress: Partisan Polarization and the Decline of Moderate Candidates”
Danielle. Thomsen · 2017
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“A Pairwise Comparison Framework for Fast, Flexible, and Reliable Human Coding of Political Texts”
David Carlson and Jacob. Montgomery · 2017
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“Minority Opposition and Asymmetric Parties? Senators’ Partisan Rhetoric on Twitter”
Annelise Russell · 2021
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“Gender and Representation Bias in GPT-3 Generated Stories”
Li Lucy and David Bamman · 2021
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“Voteview: Congressional Roll-Call Votes Database” https://voteview.com/ , 2021
Jeffrey. Lewis, Keith Poole, Howard Rosenthal, Adam Boche, Aaron Rudkin and Luke Sonnet · 2021
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“Training language models to follow instructions with human feedback”
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama and Alex Ray · 2022
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“Trump and the Shifting Meaning of “Conservative”: Using Activists’ Pairwise Comparisons to Measure Politicians’ Perceived Ideologies”
Daniel. Hopkins and Hans Noel · 2022
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“Ends Against the Middle: Measuring Latent Traits when Opposites Respond the Same Way for Antithetical Reasons”
JBrandon Duck-Mayr and Jacob Montgomery · 2022
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“Illustrating Reinforcement Learning from Human Feedback (RLHF)” https://huggingface.co/blog/rlhf
Nathan Lambert, Louis Castricato, Leandro von Werra and Alex Havrilla · 2022
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Petter Törnberg · 2023
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“GPT is an effective tool for multilingual psychological text analysis”
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“AI Chat Assistants can Improve Conversations about Divisive Topics”, 2023
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“Out of One, Many: Using Language Models to Simulate Human Samples”
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