| 1. |
- Hegre, Håvard, 1964-, et al.
(författare)
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Forecasting armed conflict in the Sahel : Forecasts for November 2021–October 2024
- 2022
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Rapport (populärvet., debatt m.m.)abstract
- Preventing armed conflict is key to promoting development and well-being in the Sahel. To strengthen its work to promote peace globally, the United Nations have recently stressed the importance of early action and early warning about impending conflict. This report presents the ViEWS system, a systematic, data-driven conflict early-warning system developed for Africa and the Middle East. Designed to complement expert assessments drawing on qualitative methods, the system produces estimates of the probability that armed conflict events will occur in countries and sub-national locations during each of the next 1–36 months. The report outlines the main features of the system, discusses the uncertainties involved and how well the system handles these, and presents the latest forecasts for the UNISS countries of the Sahel. The ViEWS forecasts are updated on a monthly basis and made available in full through an API, and in summarised form on the ViEWS website. The report also outlines some possible future developments and improvements of the system.
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| 2. |
- Hegre, Håvard, 1964-, et al.
(författare)
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Forecasting fatalities
- 2022
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Rapport (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Hegre, Håvard, 1964-, et al.
(författare)
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ViEWS : A political violence early-warning system
- 2019
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Ingår i: Journal of Peace Research. - : SAGE Publications. - 0022-3433 .- 1460-3578. ; 56:2, s. 155-174
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Tidskriftsartikel (refereegranskat)abstract
- This article presents ViEWS – a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnational level for 36 months into the future and all three UCDP types of organized violence: state-based conflict, non-state conflict, and one-sided violence in Africa. The article presents the methodology and data behind these forecasts, evaluates their predictive performance, provides selected forecasts for October 2018 through October 2021, and indicates future extensions. ViEWS is built as an ensemble of constituent models designed to optimize its predictions. Each of these represents a theme that the conflict research literature suggests is relevant, or implements a specific statistical/machine-learning approach. Current forecasts indicate a persistence of conflict in regions in Africa with a recent history of political violence but also alert to new conflicts such as in Southern Cameroon and Northern Mozambique. The subsequent evaluation additionally shows that ViEWS is able to accurately capture the long-term behavior of established political violence, as well as diffusion processes such as the spread of violence in Cameroon. The performance demonstrated here indicates that ViEWS can be a useful complement to non-public conflict-warning systems, and also serves as a reference against which future improvements can be evaluated.
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| 4. |
- Hegre, Håvard, 1964-, et al.
(författare)
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ViEWS(2020) : Revising and evaluating the ViEWS political Violence Early-Warning System
- 2021
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Ingår i: Journal of Peace Research. - : Sage Publications. - 0022-3433 .- 1460-3578. ; 58:3, s. 599-611
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Tidskriftsartikel (refereegranskat)abstract
- This article presents an update to the ViEWS political Violence Early-Warning System. This update introduces (1) a new infrastructure for training, evaluating, and weighting models that allows us to more optimally combine constituent models into ensembles, and (2) a number of new forecasting models that contribute to improve overall performance, in particular with respect to effectively classifying high- and low-risk cases. Our improved evaluation procedures allow us to develop models that specialize in either the immediate or the more distant future. We also present a formal, 'retrospective' evaluation of how well ViEWS has done since we started publishing our forecasts from July 2018 up to December 2019. Our metrics show that ViEWS is performing well when compared to previous out-of-sample forecasts for the 2015-17 period. Finally, we present our new forecasts for the January 2020-December 2022 period. We continue to predict a near-constant situation of conflict in Nigeria, Somalia, and DRC, but see some signs of decreased risk in Cameroon and Mozambique.
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| 5. |
- Theisen, Ole Magnus, et al.
(författare)
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Understanding the potential linkages between climate change and conflict in the Arab region : E/ESCWA/CL6.GCP/2021/TP.9
- 2021
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Rapport (populärvet., debatt m.m.)abstract
- The Arab States are affected by a wide range of environmental challenges exacerbated by current and projected impacts of climate change, including, among others, depletion of scarce natural resources such as water and arable land, increasing pollution levels, and the growing number and magnitude of extreme weather events. At the same time, the Arab region has been a hotspot for conflicts during the last decades. This highlights the need among policymakers and practitioners of conflict prevention and peacebuilding to better understand how climate change might contribute to current or future dynamics of conflict. This report provides a conceptual framework for analysts and policymakers in the region that shows how the loss of livelihood, economic contraction, resource competition, migration, poor governance, and other social processes (mechanisms) spurred by climate risk are more likely to increase conflict risk when occurring in certain contexts.
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| 6. |
- Vesco, Paola, 1990-, et al.
(författare)
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United they stand : findings from an escalation prediction competition
- 2022
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Ingår i: International Interactions. - : Taylor & Francis. - 0305-0629 .- 1547-7444. ; 48:4, s. 860-896
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Tidskriftsartikel (refereegranskat)abstract
- This article presents results and lessons learned from a prediction competition by ViEWS to improve collective scientific knowledge on forecasting (de-)escalation on the African continent. The competition call asked participants to forecast changes in state-based violence for the true future (October 2020 – March 2021) as well as for a held-out test partition. An external scoring committee, independent from both the organizers and participants, was formed to evaluate the models based on both qualitative and quanti- tative criteria, including performance, novelty, uniqueness and replicability. All models contributed to advance the research frontier by providing novel methodological or theo- retical insight, including new data, or adopting innovative model specifications. While we discuss several facets of the competition that could be improved moving forward, the collection passes an important test. When we build a simple ensemble prediction model – which draws on the unique insights of each contribution to differing degrees – we can measure an improvement in the prediction from the group, over and above what the average individual model can achieve. This wisdom of the crowd effect suggests that future competitions that build on both the successes and failures of ours, can contribute to scientific knowledge by incentivising diverse contributions as well as focusing a group’s attention on a common problem.
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