Political Science Research and Methods (PSRM) Dataverse

Political Science Research and Methods (PSRM) is the official journal of the European Political Science Association. It publishes original scholarly work of the highest quality from all subfields of political science with particular focus on research applying rigorous methods to empirical and theoretical problems.

PSRM is a signatory of the Data Access and Research Transparency (DA-RT) statement, promoting data sharing and research transparency in political science. PSRM requires that authors make materials available to enable others to replicate the results of research. This Dataverse is dedicated to that material.

For more information about contributing to the journal, see the instructions for contributors. Authors uploading datasets should see the guide to using PSRM Dataverse.

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61 to 70 of 610 Results

Replication Data for: Yellow Peril or Model Minority? Measuring Janus-Faced Prejudice toward Asians in the United States Nov 4, 2024 Kim, Daegyeong; Han, Enze, 2024, "Replication Data for: Yellow Peril or Model Minority? Measuring Janus-Faced Prejudice toward Asians in the United States", https://doi.org/10.7910/DVN/897CMJ, Harvard Dataverse, V1 There are two prominent but seemingly contradictory symbols of how Asians are racialized domestically within the United States: “yellow peril” and “model minority.” How do these two racial tropes relate to each other? What effects do they have on the formation of support for race-targeted public policy? In this paper, we propose and empirically tes...
Replication Data for: Multidimensional Conflicts over Disarmament and International Security: Analyzing Speeches in the First Committee of the UN General Assembly Oct 29, 2024 Finke, Daniel; Risse, Tobias, 2024, "Replication Data for: Multidimensional Conflicts over Disarmament and International Security: Analyzing Speeches in the First Committee of the UN General Assembly", https://doi.org/10.7910/DVN/WV0ECC, Harvard Dataverse, V2, UNF:6:mqn+y1xZdLE8m89bW1Ogpw== [fileUNF] In this article, we explore the rhetorical space structuring the debates in the UN General Assembly’s (UNGA) Committee on Disarmament and International Security. To this end, we unfold states’ speeches by combining three established methods. First, we estimate terms’ relevance for latent topics structuring the debates with Structural Topic Modeling...
Replication Data for: How To Train Your Stochastic Parrot: Large Language Models for Political Texts Oct 22, 2024 Ornstein, Joseph T.; Blasingame, Elise N.; Truscott, Jake S., 2024, "Replication Data for: How To Train Your Stochastic Parrot: Large Language Models for Political Texts", https://doi.org/10.7910/DVN/DZZ0OM, Harvard Dataverse, V1, UNF:6:h+hsdYDBd4erQlJSAX1SRw== [fileUNF] Large language models pretrained on massive corpora of text from the Internet have transformed the way that computer scientists approach natural language processing over the past five years. But such models have yet to see widespread adoption in the social sciences, partly due to their novelty and upfront costs. In this paper, we demonstrate how fe...
Replication Data for: Europeans’ attitudes toward the EU following Russia’s invasion of Ukraine Oct 22, 2024 Unan, Asli; Klüver, Heike, 2024, "Replication Data for: Europeans’ attitudes toward the EU following Russia’s invasion of Ukraine", https://doi.org/10.7910/DVN/WRLXWI, Harvard Dataverse, V1, UNF:6:4rq7KNmPImQavlZeBGJOag== [fileUNF] The Russian invasion of Ukraine in February 2022 has had profound effects on the stability and security of Europe. This study examines the attitudes of Europeans toward the European Union (EU) in the aftermath of the invasion of Ukraine. Using Special Eurobarometer data collected between February and April 2022 with a representative sample of the E...
Replication Data for: Advocacy campaigns and gender bias in media coverage of elections Oct 17, 2024 Gessler, Theresa; Gilardi, Fabrizio; Kubli, Maël, 2024, "Replication Data for: Advocacy campaigns and gender bias in media coverage of elections", https://doi.org/10.7910/DVN/UQ5R7L, Harvard Dataverse, V1, UNF:6:oeX4Mro4u/ADMe/oKG8Wvg== [fileUNF] An important feature of women's underrepresentation in politics are differences in the media portrayal of female candidates. This paper studies how advocacy campaigns may affect such bias, leveraging the 2019 Swiss federal elections, which were shaped by two nation-wide, cross-party campaigns advocating for gender equality. The empirical analysis c...
Replication Data for: "Are Solidarity and Identification as People of Color Distinct? Validating New Measures Across Asian, Black, Latino, and Multiracial Americans" Oct 2, 2024 PEREZ, EFREN, 2024, "Replication Data for: "Are Solidarity and Identification as People of Color Distinct? Validating New Measures Across Asian, Black, Latino, and Multiracial Americans"", https://doi.org/10.7910/DVN/X4YIDO, Harvard Dataverse, V1 Mounting U.S. research suggests many non-White individuals feel solidarity with, and identify as, people of color (PoC). Yet measurement limitations prevent scholars from testing whether these constructs are empirically different. We explain why these concepts diverge and evaluate our claims with an expanded battery of measures across U.S. Asian, B...
Replication Data for: Do External Threats Increase Bipartisanship in the United States? An Experimental Test in the Shadow of China's Rise Sep 25, 2024 Yeung, Eddy S. F.; Weifang, Xu, 2024, "Replication Data for: Do External Threats Increase Bipartisanship in the United States? An Experimental Test in the Shadow of China's Rise", https://doi.org/10.7910/DVN/I43DNF, Harvard Dataverse, V1 Do external threats increase American bipartisanship? While previous scholarship suggests they do, recent research argues that security threats from foreign adversaries may further polarize Americans amid hyperpartisanship, as information about external threats is often filtered through partisan lens. We subject these competing perspectives to an e...
Replication Data for: American Partisans Vastly Under-Estimate the Diversity of Other Partisans’ Policy Attitudes Sep 24, 2024 Dias, Nicholas C.; Lelkes, Yphtach; Pearl, Jacob, 2024, "Replication Data for: American Partisans Vastly Under-Estimate the Diversity of Other Partisans’ Policy Attitudes", https://doi.org/10.7910/DVN/RX37FT, Harvard Dataverse, V3 A popular explanation for America's democratic ills is that Republicans and Democrats misperceive one another to hold extreme attitudes. However, Americans may also misperceive the diversity of partisans' attitudes to ill effect. This paper uses surveys and pre-registered experiments with representative and convenience samples (n = 9,405) to valida...
Replication Data for: Linking Datasets on Organizations Using Half a Billion Open-Collaborated Records Sep 3, 2024 Jerzak, Connor; Libgober, Brian, 2024, "Replication Data for: Linking Datasets on Organizations Using Half a Billion Open-Collaborated Records", https://doi.org/10.7910/DVN/APXALF, Harvard Dataverse, V1, UNF:6:FUCCyYKaCwmnd19icoeabg== [fileUNF] Abstract: Scholars studying organizations often work with multiple datasets lacking shared unique identifiers or covariates. In such situations, researchers usually use approximate string (fuzzy) matching methods to combine datasets. String matching, although useful, faces fundamental challenges. Even when two strings appear similar to humans, fuzz...
Replication Data for: ecolRxC: Ecological inference estimation of R×C tables using latent structure approaches Sep 3, 2024 Pavia, Jose M., 2024, "Replication Data for: ecolRxC: Ecological inference estimation of R×C tables using latent structure approaches", https://doi.org/10.7910/DVN/KOZI2C, Harvard Dataverse, V1, UNF:6:1rb0BEl8pCi37aju51SwKg== [fileUNF] Ecological inference is a statistical technique used to infer individual behaviour from aggregate data. A particularly relevant instance of ecological inference involves the estimation of the inner cells of a set of R×C related contingency tables when only their aggregate margins are known. This problem spans multiple disciplines, including quantit...

Replication Data for: Yellow Peril or Model Minority? Measuring Janus-Faced Prejudice toward Asians in the United States

Nov 4, 2024

Kim, Daegyeong; Han, Enze, 2024, "Replication Data for: Yellow Peril or Model Minority? Measuring Janus-Faced Prejudice toward Asians in the United States", https://doi.org/10.7910/DVN/897CMJ, Harvard Dataverse, V1

There are two prominent but seemingly contradictory symbols of how Asians are racialized domestically within the United States: “yellow peril” and “model minority.” How do these two racial tropes relate to each other? What effects do they have on the formation of support for race-targeted public policy? In this paper, we propose and empirically tes...

Replication Data for: Multidimensional Conflicts over Disarmament and International Security: Analyzing Speeches in the First Committee of the UN General Assembly

Oct 29, 2024

Finke, Daniel; Risse, Tobias, 2024, "Replication Data for: Multidimensional Conflicts over Disarmament and International Security: Analyzing Speeches in the First Committee of the UN General Assembly", https://doi.org/10.7910/DVN/WV0ECC, Harvard Dataverse, V2, UNF:6:mqn+y1xZdLE8m89bW1Ogpw== [fileUNF]

In this article, we explore the rhetorical space structuring the debates in the UN General Assembly’s (UNGA) Committee on Disarmament and International Security. To this end, we unfold states’ speeches by combining three established methods. First, we estimate terms’ relevance for latent topics structuring the debates with Structural Topic Modeling...

Replication Data for: How To Train Your Stochastic Parrot: Large Language Models for Political Texts

Oct 22, 2024

Ornstein, Joseph T.; Blasingame, Elise N.; Truscott, Jake S., 2024, "Replication Data for: How To Train Your Stochastic Parrot: Large Language Models for Political Texts", https://doi.org/10.7910/DVN/DZZ0OM, Harvard Dataverse, V1, UNF:6:h+hsdYDBd4erQlJSAX1SRw== [fileUNF]

Large language models pretrained on massive corpora of text from the Internet have transformed the way that computer scientists approach natural language processing over the past five years. But such models have yet to see widespread adoption in the social sciences, partly due to their novelty and upfront costs. In this paper, we demonstrate how fe...

Replication Data for: Europeans’ attitudes toward the EU following Russia’s invasion of Ukraine

Oct 22, 2024

Unan, Asli; Klüver, Heike, 2024, "Replication Data for: Europeans’ attitudes toward the EU following Russia’s invasion of Ukraine", https://doi.org/10.7910/DVN/WRLXWI, Harvard Dataverse, V1, UNF:6:4rq7KNmPImQavlZeBGJOag== [fileUNF]

The Russian invasion of Ukraine in February 2022 has had profound effects on the stability and security of Europe. This study examines the attitudes of Europeans toward the European Union (EU) in the aftermath of the invasion of Ukraine. Using Special Eurobarometer data collected between February and April 2022 with a representative sample of the E...

Replication Data for: Advocacy campaigns and gender bias in media coverage of elections

Oct 17, 2024

Gessler, Theresa; Gilardi, Fabrizio; Kubli, Maël, 2024, "Replication Data for: Advocacy campaigns and gender bias in media coverage of elections", https://doi.org/10.7910/DVN/UQ5R7L, Harvard Dataverse, V1, UNF:6:oeX4Mro4u/ADMe/oKG8Wvg== [fileUNF]

An important feature of women's underrepresentation in politics are differences in the media portrayal of female candidates. This paper studies how advocacy campaigns may affect such bias, leveraging the 2019 Swiss federal elections, which were shaped by two nation-wide, cross-party campaigns advocating for gender equality. The empirical analysis c...

Replication Data for: "Are Solidarity and Identification as People of Color Distinct? Validating New Measures Across Asian, Black, Latino, and Multiracial Americans"

Oct 2, 2024

PEREZ, EFREN, 2024, "Replication Data for: "Are Solidarity and Identification as People of Color Distinct? Validating New Measures Across Asian, Black, Latino, and Multiracial Americans"", https://doi.org/10.7910/DVN/X4YIDO, Harvard Dataverse, V1

Mounting U.S. research suggests many non-White individuals feel solidarity with, and identify as, people of color (PoC). Yet measurement limitations prevent scholars from testing whether these constructs are empirically different. We explain why these concepts diverge and evaluate our claims with an expanded battery of measures across U.S. Asian, B...

Replication Data for: Do External Threats Increase Bipartisanship in the United States? An Experimental Test in the Shadow of China's Rise

Sep 25, 2024

Yeung, Eddy S. F.; Weifang, Xu, 2024, "Replication Data for: Do External Threats Increase Bipartisanship in the United States? An Experimental Test in the Shadow of China's Rise", https://doi.org/10.7910/DVN/I43DNF, Harvard Dataverse, V1

Do external threats increase American bipartisanship? While previous scholarship suggests they do, recent research argues that security threats from foreign adversaries may further polarize Americans amid hyperpartisanship, as information about external threats is often filtered through partisan lens. We subject these competing perspectives to an e...

Replication Data for: American Partisans Vastly Under-Estimate the Diversity of Other Partisans’ Policy Attitudes

Sep 24, 2024

Dias, Nicholas C.; Lelkes, Yphtach; Pearl, Jacob, 2024, "Replication Data for: American Partisans Vastly Under-Estimate the Diversity of Other Partisans’ Policy Attitudes", https://doi.org/10.7910/DVN/RX37FT, Harvard Dataverse, V3

A popular explanation for America's democratic ills is that Republicans and Democrats misperceive one another to hold extreme attitudes. However, Americans may also misperceive the diversity of partisans' attitudes to ill effect. This paper uses surveys and pre-registered experiments with representative and convenience samples (n = 9,405) to valida...

Replication Data for: Linking Datasets on Organizations Using Half a Billion Open-Collaborated Records

Sep 3, 2024

Jerzak, Connor; Libgober, Brian, 2024, "Replication Data for: Linking Datasets on Organizations Using Half a Billion Open-Collaborated Records", https://doi.org/10.7910/DVN/APXALF, Harvard Dataverse, V1, UNF:6:FUCCyYKaCwmnd19icoeabg== [fileUNF]

Abstract: Scholars studying organizations often work with multiple datasets lacking shared unique identifiers or covariates. In such situations, researchers usually use approximate string (fuzzy) matching methods to combine datasets. String matching, although useful, faces fundamental challenges. Even when two strings appear similar to humans, fuzz...

Replication Data for: ecolRxC: Ecological inference estimation of R×C tables using latent structure approaches

Sep 3, 2024

Pavia, Jose M., 2024, "Replication Data for: ecolRxC: Ecological inference estimation of R×C tables using latent structure approaches", https://doi.org/10.7910/DVN/KOZI2C, Harvard Dataverse, V1, UNF:6:1rb0BEl8pCi37aju51SwKg== [fileUNF]

Ecological inference is a statistical technique used to infer individual behaviour from aggregate data. A particularly relevant instance of ecological inference involves the estimation of the inner cells of a set of R×C related contingency tables when only their aggregate margins are known. This problem spans multiple disciplines, including quantit...

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