Automated Organization ProfileDepartment of Political Science, Stanford University
Department of Political Science, Stanford University
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.7 (sum of 10 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The rate at which states defend their allies in war has dropped from 81% during 1816-1944 to 7% in 1945-2016. I attribute the decline in honored alliances to a dramatic shift in the military capability of alliances. Contrary to the popular belief that alliances have become stronger after 1945, I find that the post-1945 international system also witnessed a significant increase in the number of weaker alliances. This bimodal distribution of alliances produced a pattern where alliances were either violated upon being attacked or never attacked in the first place, leading to a decline in the rate at which alliances were honored. I support my argument using alliance data over two centuries. This research advances our understanding of military alliances by documenting a polarization of alliances in terms of their military capability post-1945 and by providing an explanation for an empirical puzzle—a sharp decline in the rate of honored alliances after 1945.
Authors
- Soyoung Lee
Online supplemental appendix
Authors
- Bonica, Adam
Contributor estimates (.csv)
Authors
- Bonica, Adam
Candidate estimates (.csv)
Authors
- Bonica, Adam
Codebook for contributor file
Authors
- Bonica, Adam
I develop a method to measure the ideology of candidates and contributors using campaign finance data. Combined with a data set of over 100 million contribution records from state and federal elections, the method estimates ideal points for an expansive range of political actors. The common pool of contributors who give across institutions and levels of politics makes it possible to recover a unified set of ideological measures for members of Congress, the President and executive branch, state legislators, governors and other state officials, as well as the interest groups and individuals that make political donations. Since candidates fundraise regardless of incumbency status, the method estimates ideal points for both incumbents and non-incumbents. After establishing measure validity and addressing issues concerning strategic behavior, I present results for a variety of political actors and discuss several promising avenues of research made possible by the new measures.
Authors
- Bonica, Adam
Contributor estimates (.Rdata)
Authors
- Bonica, Adam
R object containing a sparse matrix of contribution amounts and matrices for candidate and contributors.
Authors
- Bonica, Adam
Candidate estimates (.Rdata)
Authors
- Bonica, Adam