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Cited by 273

The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.

The Force of Face-to-Face Diplomacy: Mirror Neurons and the Problem of Intentions

Holmes, Marcus·2013·International Organization

Abstract

Face-to-face diplomacy has long been the lynchpin of international politics, yet it has largely been dismissed as irrelevant in theories of cooperation and conflict—as “cheap talk” because leaders have incentives to dissemble. However, diplomats and leaders have argued for years that there is often no substitute for personally meeting a counterpart to hash out an agreement. This article argues that face-to-face diplomacy provides a signaling mechanism that increases the likelihood of cooperation. Face-to-face meetings allow individuals to transmit information and empathize with each other, thereby reducing uncertainty, even when they have strong incentives to distrust the other. The human brain has discrete architecture and processes devoted to parsing others' intentions via cues in face-to-face interaction. These processes enable actors to directly access the intentions of others with a higher degree of certainty than economic and game-theoretic models of bargaining predict.

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Metadata

Authors
Holmes, M.
Venue
International Organization
Published
2013-10
Volume
67
Issue
4
Pages
829-861
ISSN
  • 0020-8183 (ISSN-L)
  • 1531-5088
OpenAlex
W2061640646
Cited by
273
References
75
FWCI
51.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Force of Face-to-Face Diplomacy: Mirror Neurons and the Problem of Intentions. https://app.cochat.ai/papers/10.1017/s0020818313000234
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Holmes, M. (2013). The Force of Face-to-Face Diplomacy: Mirror Neurons and the Problem of Intentions. International Organization. https://doi.org/10.1017/s0020818313000234

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.