The Political Geography of Sanctions Support: Evidence From Kazakhstan

Shannon P. Carcelli & Margaret Hanson

Journal of Conflict Resolution2026https://doi.org/10.1177/00220027261427300article
AJG 3ABDC A*
Weight
0.50

Abstract

Economic sanctions have become an increasingly prominent tool in twenty first-century statecraft. However, it is relatively easy for third-party states to undermine their effectiveness. This vulnerability makes it important to understand how and why their local publics support or oppose sanctions. Drawing from the case of Kazahkstan’s response to the global sanctions regime against Russia, we find that support for the sanctions varies based on ethnicity and geography. Specifically, ethnic Russians view the sanctions far more negatively than ethnic Kazakhs. Surprisingly, however, ethnic Russians located in non-traditional border regions express approval levels on par with ethnic Kazakhs. We argue that this difference stems from economic interest: due to their geographical proximity and informal ties with co-ethnics across the border, this group is well-positioned to benefit economically from sanctions evasion. Income reporting data offer further support for this argument. Our findings suggest that those developing sanctions regimes would benefit from considering how political geography and identity interact to shape support for sanctions—and their efficacy.

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https://doi.org/https://doi.org/10.1177/00220027261427300

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@article{shannon2026,
  title        = {{The Political Geography of Sanctions Support: Evidence From Kazakhstan}},
  author       = {Shannon P. Carcelli & Margaret Hanson},
  journal      = {Journal of Conflict Resolution},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00220027261427300},
}

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The Political Geography of Sanctions Support: Evidence From Kazakhstan

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.