Assessing Causality Structures learned from Digital Text Media

In this paper we describe a framework to uncover potential causal relations between event mentions from streaming text of news media. This framework relies on a dataset of manually labeled events to train a recurrent neural network for event detection. It then creates a time series of event clusters, where clusters are based on BERT contextual word embedding representations of the identified events. Using these time series dataset, we assess four methods based on Granger causality for inferring causal relations. Granger causality is a statistical concept of causality that is based on forecasting. It states that a cause occurs before the effect, and the cause produces unique changes in the effect, so past values of the cause help predict future values of the effect. The four analyzed methods are the pairwise Granger test, VAR(1), BigVar and SiMoNe. The framework is applied to the New York Times dataset, which covers news for a period of 246 months. This preliminary analysis delivers important insights into the nature of each method, identifies differences and commonalities, and points out some of their strengths and weaknesses.Fil: Maisonnave, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Delbianco, Fernando Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Economía; ArgentinaFil: Tohmé, Fernando Abel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Economía; ArgentinaFil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Milios, Evangelos E.. Dalhousie University. Faculty of Computer Science; CanadáDocEng '20: ACM Symposium on Document Engineering 2020New YorkEstados UnidosAssociation for Computing Machiner

Artisans Angkor: Reclaiming Cambodian silk crafts under French patronage (1992–2017)

Following the 1991 Paris Peace Accords that granted a return to a relative political stability in Cambodia, the non-profit organization Les Chantiers Ecoles was launched with the support of the European Union to revive local traditional crafts and sericulture that had nearly vanished under the Khmer Rouge regime. This vocational institute was the result of a cooperation between the French and the Cambodian government. It provided training to disadvantaged young villagers of Siem Reap’s area in polychromic woodwork, stone carving, metal, lacquerware, and silk weaving. Eventually, the project turned into a social enterprise under the French name Artisans Angkor. Drawing its inspiration from the surrounding archaeological splendors of Angkor Wat, the company emphasizes its authentic making processes. Artisans Angkor welcomes tourists in its silk farm near Siem Reap, using this production site as a showcase for sericulture from silkworms breeding to weaving, promoting the revival of indigenous golden silk while selling a wide range of souvenirs goods. Relying on the performative value of silk craft practices, Artisans Angkor has developed an engaging storytelling, an educational and marketing tool which elevates crafts as tokens of Cambodian cultural identity. Praised by the Cambodians who consider the brand as a national success, the enterprise has however kept a French leadership. Tracing the company’s history, this paper examines to which extent Artisan Angkor follows the definition of a Transnational Artisan Partnership developed by anthropologist Susan Falls and how it pertains to a form of soft power for the French. Through the analysis of its aesthetic and discourses, this case study highlights the project’s hybrid nature and demonstrates how it relates to the colonial model of the School of Cambodian Arts implemented in 1920 under the French Protectorate to promote Cambodian crafts

Development of a European Multi-Model Ensemble System for Seasonal to Inter-Annual Prediction (DEMETER)

A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole