31 to 40 of 274 Results
Jan 15, 2025
Clealand, Danielle, 2024, "Replication Data for Measuring Blackness Among a Mixed-Race Population: Afro-Latino Oversample", https://doi.org/10.7910/DVN/UWIVDA, Harvard Dataverse, V2, UNF:6:IaqTT7w3rACOm34ih4Pbrw== [fileUNF]
This dataset includes only the Afro-Latino oversample data from the 2020 Collaborative Multiracial Post-Election Survey. |
Jan 13, 2025
Lockerbie, Brad, 2025, "Replication Data for: The Challenge of Forecasting the 2024 Presidential and House Elections: Economic Pessimism and Election Outcomes", https://doi.org/10.7910/DVN/FMRDPF, Harvard Dataverse, V1
Utilizing a forecasting model based on economic pessimism and recognizing the difficulties of making such a forecast in such atypical times, the forecasting model predicts a narrow loss for the incumbent presidential party and a loss of 12 seats in the House of Representatives. Even with the unusual nature of politics in the United States over the... |
Jan 10, 2025
Zhirkov, Kirill; Lauren Van De Hey, 2025, "Replication Data for: Multidimensional Constructions of Target Groups and Their Political Implications: The Case of Immigrant (Il)legality", https://doi.org/10.7910/DVN/HPFSZJ, Harvard Dataverse, V1
Social construction theory postulates that policy outcomes depend on whether target groups are imagined as deserving or undeserving by the public. However, recent evidence demonstrates that the constructions in question are contentious rather than agreed upon. In this paper, we apply the conjoint-experimental method to measure the social constructi... |
Jan 10, 2025
You, Hye Young, 2025, "Replication Data for "Applications of GPT in Political Science Research: Extracting Information from Unstructured Text"", https://doi.org/10.7910/DVN/7KJLH7, Harvard Dataverse, V1
This paper explores the use of large language models (LLMs), specifically GPT, for enhancing information extraction from unstructured text in political science research. By automating the retrieval of explicit details from sources such as historical documents, meeting minutes, news articles, and unstructured search results, GPT significantly reduce... |
Jan 8, 2025
Jágr, David; Mansfeldová, Zdenka, 2025, "Replication Data for: THE DISRUPTIVE EFFECTS OF POLARIZATION ON THE LAW-MAKING PROCESS", https://doi.org/10.7910/DVN/L6YZV9, Harvard Dataverse, V1
The Czech Republic, as a country in Central and Eastern Europe, underwent what Ágh refers to as "parliamentarization" at the onset of the democratization process (Ágh 1997; 1999; 2003). Over three decades, this has changed, and tendencies towards executive expansion can now be observed in new and established democracies. However, this is not univer... |
Dec 20, 2024
Dowdle, Andrew; Randy Adkins; Karen Sebold; Wayne Steger, 2024, "Replication Data for: Forecasting the 2024 Republican Presidential Nomination: Can the Former Heavyweight Champ Win Another Title Shot?", https://doi.org/10.7910/DVN/DUZNXB, Harvard Dataverse, V1, UNF:6:SjoBJIkuTDQmZCZbrJE6aQ== [fileUNF]
Donald Trump’s bid for the 2024 Republican presidential nomination is unique in that no former president since Theodore Roosevelt in 1912 has sought the nomination of their political party, nor has a candidate sought the nomination while facing multiple criminal indictments. Using data from previous nomination cycles, we use presidential nomination... |
Dec 19, 2024
Love, Gregory J.; Carlin, Ryan E.; Singer, Matthew M., 2024, "Replication Data for: LASSOing the Governor’s Mansion: A Machine Learning Approach to Forecasting Gubernatorial Elections", https://doi.org/10.7910/DVN/2KT0XS, Harvard Dataverse, V1, UNF:6:NPSYPvs/wxx1Ljnr5fHeNw== [fileUNF]
Replication data and code for the article "LASSOing the Governor’s Mansion: A Machine Learning Approach to Forecasting Gubernatorial Elections" in the PS symposium on election forecasting, 2024. |
Dec 18, 2024
Bednarczuk, Michael, 2024, "Replication Data for: Forecasting US Voter Turnout", https://doi.org/10.7910/DVN/E4TVR0, Harvard Dataverse, V1, UNF:6:XAXwzJ1HFPXYk8Tp0VRVjA== [fileUNF]
Voter turnout is a crucial indicator of democratic health, yet forecasting turnout remains an understudied area in political science. This article presents two pioneering models for predicting U.S. presidential election turnout: The National Model and The State Model. The National Model, using data from 1868-2020, employs lagged turnout as its sole... |
Dec 6, 2024
Nunoo, Isaac, 2024, "Replication Data for: Uncovering African Agency: Non-State Actors and Sino-Ghana Relations", https://doi.org/10.7910/DVN/FXQZOX, Harvard Dataverse, V1
The burgeoning ‘ChinAfrica’ debates often fail to consider questions of African agency and in particular, the role played by civil society organizations (CSOs), the media and local groupings to give greater voice to African agency in Sino-African relations. Drawing on qualitative methods (interviews and content analysis), the study examines the rel... |
Dec 6, 2024
Lindsay, Spencer; Allen, Levi, 2024, "Replication Data for: "A Dynamic Forecast: An Evolving Prediction of the 2024 Presidential Election"", https://doi.org/10.7910/DVN/RLEUOF, Harvard Dataverse, V1, UNF:6:kDZumGmLaCYr4rf3RrjOWA== [fileUNF]
In this article, we build a model to predict the state-level results of the 2024 election. We do so by using polling from similar points in past election cycles and by using the results of the previous election. Notably, we update our model over time and the coefficients of the two variables change- the model puts more weight on polling as the elec... |
