The Personal Touch: Leaders’ Impressions, Costly Signaling, and Assessments of Sincerity in International Affairs1
Bibliographic record
Abstract
What counts as evidence that the other side is sincere? Within mainstream international relations literature, scholars have focused on costly signals. We argue, however, that in the real world leaders do not simply look at costly signals, but they rely to an important extent on their personal impressions of other leaders, taking these as credible indicators of sincerity. Our approach thus builds both upon the literature on interstate communication and perceptions and upon more recent research in the field of neuroscience regarding affective information. To probe the plausibility of our theory, we focus on the indicators British Prime Minister Neville Chamberlain used to evaluate Germany sincerity in the late 1930s and Ronald Reagan employed to make sincerity judgments about Soviet intentions in the late 1980s. Additionally, we briefly discuss the 1961 Vienna Summit between Kennedy and Khrushchev as an illustration of how personal impressions can also result in negative assessments of sincerity. Our findings suggest that personal impressions are an important, but up until now relatively ignored, source of evidence for leaders of their counterparts’ sincerity with significant implications for threat assessments and policy choices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".