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   https://doi.org/http://dx.doi.org/10.18653/v1/2020.nlpcss-1.13  

   Keith, Katherine ; Teichmann, Christoph ; O'Connor, Brendan ; Meij, Edgar ( January 2020 , Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science)

   null (Ed.)

   Methods and applications are inextricably linked in science, and in particular in the domain of text-as-data. In this paper, we examine one such text-as-data application, an established economic index that measures economic policy uncertainty from keyword occurrences in news. This index, which is shown to correlate with firm investment, employment, and excess market returns, has had substantive impact in both the private sector and academia. Yet, as we revisit and extend the original authors’ annotations and text measurements we find interesting text-as-data methodological research questions: (1) Are annotator disagreements a reflection of ambiguity in language? (2) Do alternative text measurements correlate with one another and with measures of external predictive validity? We find for this application (1) some annotator disagreements of economic policy uncertainty can be attributed to ambiguity in language, and (2) switching measurements from keyword-matching to supervised machine learning classifiers results in low correlation, a concerning implication for the validity of the index. 

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2. Quantifying Uncertainty in Ecotoxicological Risk Assessment: MUST, a Modular Uncertainty Scoring Tool

   https://doi.org/10.1021/acs.est.0c02224  

   Kostal, Jakub ; Plugge, Hans ; Raderman, Will ( October 2020 , Environmental Science & Technology)

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   https://doi.org/10.1103/PhysRevPhysEducRes.19.020139  

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4. Studies of systematic uncertainty effects on IceCube's real-time angular uncertainty

   https://doi.org/10.22323/1.395.1045  

   Abbasi, Rasha ; Ackermann, Markus ; Adams, Jenni ; Aguilar, Juanan ; Ahlers, M. ; Ahrens, Maryon ; Alispach, Cyril Martin ; Alves Junior, Antonio Augusto ; Amin, Najia Moureen ; An, Rui ; et al ( July 2021 , ICRC2021)
5. Dynamic Ensembles versus Cones of Uncertainty: Visualizations to Support Understanding of Uncertainty in Hurricane Forecasts

   https://doi.org/10.1177/1071181320641399  

   Witt, Jessica K. ; Clegg, Benjamin A. ; Wickens, Christopher D. ; Smith, C.A.P. ; Laitin, Emily L. ; Warden, Amelia C. ( December 2020 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Visualizations attempt to convey the uncertain track of an approaching hurricane. The current experiment contrasted decision characteristics that resulted from observing hurricane paths presented using cones of uncertainty versus a new form of dynamic ensemble. Participants made judgments about whether to evacuate a town at different eccentricities to the central predicted path of a storm. Results showed that dynamic ensembles have different properties to cone displays. Presentations of dynamic ensembles encouraged greater consideration of evacuation at locations further from the most probable path, but that were still at risk. However, dynamic ensembles resulted in lower evacuation rates at the center of the distribution, consistent with a probabilistic sense of the risk but nonetheless a potentially undesirable strategy. In addition, perceptions of the evacuation need with dynamic ensemble presentations were more strongly influenced by the amount of variability than with cones. The implications for use of dynamic ensembles are discussed. 

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