WhatsApp with Diplomatic Practices in Geneva? Diplomats, Digital Technologies, and Adaptation in Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Diplomats in embassies and permanent representations are increasingly using the messaging application WhatsApp to communicate with their peers. They use WhatsApp groups to coordinate initiatives at multilateral forums, communicate more rapidly with headquarters and stay in touch with organizational developments at home, as well as form more personal working relations among their peers. To make sense of this phenomenon, our analysis looks at adaptation in practice. Instead of separating digital practices from offline/traditional ways of doing things, we build on the practice turn in International Relations and develop a nuanced framework in which improvising agents in a transformed context adapt to new realities while continuously being influenced by past ways of doing things—a phenomenon called “hysteresis” by practice turners. We analyze how traditional practices are supplemented by new technologies (complementarities) as well as how offline and online relationships are shaped by similar practical logics (similarities). We apply these micro-lenses to understand multilateral diplomacy at the United Nations Human Rights Council in Geneva. Building on twenty-three interviews with practitioners, we find that WhatsApp redefines the meaning of face-to-face interactions among ambassadors and permanent representatives and makes physical meetings between diplomats more—rather than less—important.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it