The 2023/24 VIEWS Prediction Challenge: Predicting the Number of Fatalities in Armed Conflict, with Uncertainty

• Published in: arXiv.org
• Main Authors: Hegre, Håvard, Vesco, Paola, Colaresi, Michael, Vestby, Jonas, Timlick, Alexa, Noorain Syed Kazmi, Becker, Friederike, Binetti, Marco, Bodentien, Tobias, Bohne, Tobias, Brandt, Patrick T, Chadefaux, Thomas, Drauz, Simon, Dworschak, Christoph, D'Orazio, Vito, Fritz, Cornelius, Hannah, Frank, Gleditsch, Kristian Skrede, Häffner, Sonja, Hofer, Martin, Klebe, Finn L, Macis, Luca, Malaga, Alexandra, Mehrl, Marius, Metternich, Nils W, Mittermaier, Daniel, Muchlinski, David, Mueller, Hannes, Oswald, Christian, Pisano, Paola, Randahl, David, Rauh, Christopher, Rüter, Lotta, Schincariol, Thomas, Seimon, Benjamin, Siletti, Elena, Tagliapietra, Marco, Thornhill, Chandler, Vegelius, Johan, Walterskirchen, Julian
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 08.07.2024
• Subjects: Fatalities; Predictions
• ISSN: 2331-8422

This draft article outlines a prediction challenge where the target is to forecast the number of fatalities in armed conflicts, in the form of the UCDP `best' estimates, aggregated to the VIEWS units of analysis. It presents the format of the contributions, the evaluation metric, and the procedures, and a brief summary of the contributions. The article serves a function analogous to a pre-analysis plan: a statement of the forecasting models made publicly available before the true future prediction window commences. More information on the challenge, and all data referred to in this document, can be found at https://viewsforecasting.org/research/prediction-challenge-2023.