Simulating Peace Operations: New Digital Possibilities for Training and Public Education
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
Background and Motivation. A plethora of warfighting games exist commercially, but there is a lack of digital games that deal with peace processes. Furthermore, none simulate actual peacekeeping. The United Nations currently deploys about 100,000 peacekeepers to some of the world’s most dangerous zones, where peacekeepers save lives, alleviate suffering, and help create conditions for peace. The United Nations and national militaries lack peacekeeping simulations to help train their soldiers. Additionally, the public needs to learn more about the way peacekeeping works. Thus, peacekeeping simulation and gaming are worth exploring, especially in the rapidly evolving digital space, which offers new avenues and benefits. Methods. We review the meager literature on the subject and observe that there are few digital games to directly draw from. We build on previous work that argued the need for such development, but we now assess important design principles and parameters. We draw upon peacekeeping tabletop exercises that are already well developed. Results. We conclude that excellent scenarios and simulation technologies exist that could be combined quite easily for effective peacekeeping training and public education. We find key materials and scenarios in exercises of the United Nations and of the Pearson Peacekeeping Centre. Highlighted areas for future digital design are the inclusion of non-military avatars, emphasis on soft skills development (especially empathy), and realistically complex links between actions and consequences. Conclusion. While describing some UN exploration at a proof-of-concept stage, we suggest that both the United Nations and the gaming industry should explore the idea further to achieve synergies between institutional and entertainment applications. The growing capacity of digital technology allows significant innovation, yielding results that could be useful, ethical, enjoyable, and potentially profitable.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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