Automated Author Profile

Jones, Calvert W.

City College of New York

Current S-Index

0.7

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.7

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

15.4%

Average FAIR Score per dataset

Total Citations

1

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Exploring the Microfoundations of International Community: Toward a Theory of Enlightened Nationalism (Version: 1.0)

This paper challenges conventional wisdom about the drivers of international community at the individual level. Presenting new data and a novel natural experiment approach to the study of cross-border contact and international community, it tests some of the key microfoundations of international relations theory about how a sense of shared international community may arise and evolve among individuals. The hypotheses are tested using survey data from a large sample (n = 571) of American study abroad students in a range of universities across a treatment and a control group. Surprisingly, findings do not support the main hypothesis that cross-border contact fosters a sense of shared international community. However, the second hypothesis drawn from the liberal paradigm, suggesting that cross-border contact lowers threat perceptions, is strongly supported. The “Huntingtonian” hypothesis that cross-border contact heightens nationalism also garners wide support. The paper concludes with a discussion of the implications for theory and future research, especially the potential of rethinking the drivers of international community at the individual level to rely less on a sense of shared identity and essential sameness, and more on a feeling of “enlightened nationalism” and appreciation for difference.

Authors

  • Jones, Calvert W.
1 Citation0 Mentions15% FAIR0.7 Dataset Index
10.7910/dvn/eyce4oJanuary 2017