arbiter
JournalsPricingAccount

Base Towns: Local contestation of the U.S. Military in Korea and Japan, by Claudia Junghyun Kim

Ra Mason

Social Science Japan Journal2025https://doi.org/10.1093/ssjj/jyaf024article
ABDC C
Weight
0.50

What the paper says

Critical discussion of American overseas military basing is an overcrowded topic area. However, in Base Towns, Claudia Junghyun Kim makes a decisive intervention into the field—through six diverse chapters—to develop a theoretically grounded and empirically persuasive discussion of US basing in Korea and Japan. The book provides a valuable reinterpretation of how complex local agency acts to substantively affect the framing, governance, and statuses of Washington’s extensive network of bases in both countries. In so doing, Kim advances the consistent argument that ‘contentious base politics, despite the prevalent scepticism, deserve attention as a social force shaping domestic and international politics’ (4). Moreover, unlike competing texts, this single volume skilfully constructs the argument through three novel frames that focus on the subnational: status quo disruption, movement framing, and local elite allies (9–12).

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1093/ssjj/jyaf024

Or copy a formatted citation

@article{ra2025,
  title        = {{Base Towns: Local contestation of the U.S. Military in Korea and Japan, by Claudia Junghyun Kim}},
  author       = {Ra Mason},
  journal      = {Social Science Japan Journal},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1093/ssjj/jyaf024},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Base Towns: Local contestation of the U.S. Military in Korea and Japan, by Claudia Junghyun Kim

Flags are reviewed by the Arbiter methodology team within 5 business days.

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.