Automated Author ProfileYoung, Joseph K.
American University
Young, Joseph K.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author'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: 2.7 (sum of 7 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
What explains the variation in terrorism within and across political regimes? We contend that terrorism is most likely to occur in contexts in which governments cannot credibly restrain themselves from abusing their power in the future. We consider a specific institutional arrangement, whether a state has an independent judiciary, and hypothesize that independent judiciaries make government commitments more credible, thereby providing less incentive for the use of terrorism. Using a recently released database that includes transnational and domestic terrorist events from 1970 to 1997, we estimate a set of statistical analyses appropriate for the challenges of terrorism data and then examine the robustness of the results. The results provide support for the credible commitment logic and offer insights into the different ways that political institutions increase or decrease terrorism.
Authors
- Findley, Michael G. ;
- Young, Joseph K.
Conventional wisdom suggests that reports of terrorism should be sparse in dictatorships, both because such violence is unlikely to result in policy change and because it is difficult to get reliable information on attacks. Yet, there is variance in the number of terrorist attacks reported in autocracies. Why? We argue that differences in the audience costs produced by dictatorships explain why some nondemocracies experience more terrorism than others. Terrorists are more likely to expect a response in dictatorships that generate high domestic audience costs. Using data from multiple terrorism databases, we find empirical evidence that dictatorships generating higher audience costs—military dictatorships, single-party dictatorships, and dynastic monarchies—experience as much terrorism as democracies, while autocracies generating lower audience costs—personalist dictatorships and non-dynastic monarchies—face fewer attacks than their democratic counterparts.
Authors
- Conrad, Courtenay R. ;
- Conrad, Justin ;
- Young, Joseph K.
Replication materials for Young (2013), Political Research Quarterly
Authors
- Young, Joseph K.
Replication Materials for Young and Findley (2011) Public Choice
Authors
- Young, Joseph K.
Replication materials for Mullins and Young (2011), Crime & Delinquency
Authors
- Young, Joseph K.
Replication materials for Kingstone and Young (2009), Political Research Quarterly
Authors
- Young, Joseph K.