Global regulation of the knowledge-based economy: The rise of standards in educational services

This article examines the extent and limits of non-state forms of authority in international relations. It analyses how the information and communication technology (ICT) infrastructure for the tradability of services in a global knowledge-based economy relies on informal regulatory practices for adjustment of ICT-related skills. Companies and associations provide training and certification programmes as part of a growing market for educational services setting their own standards. The existing literature on non-conventional forms of authority in the global political economy has emphasised that the consent of actors subject to informal rules and explicit or implicit state recognition remains crucial for the effectiveness of those new forms of power. However, analyses based on a limited sample of actors tend toward a narrow understanding of the issues and fail to fully explore the differentiated space in which non-state authority is emerging. This paper examines the form of authority underpinning the global knowledge-based economy within the broader perspective of the issues likely to be standardised by technical ICT specification, the wide range of actors involved, and the highly differentiated space where standards become authoritative. The empirical findings highlight the role of different private actors in establishing international educational norms in this field. They also pinpoint the limits of profit-oriented standard-settings, notably with regard to generic norms.

Transnational authority in the knowledge-based economy: Who sets the standards of ICT training and certification?

This article examines the extent and limits of nonstate forms of authority in international relations. It analyzes how the information and communication technology (ICT) infrastructure for the tradability of services in a global knowledge-based economy relies on informal regulatory practices for the adjustment of ICT-related skills. By focusing on the challenge that highly volatile and short-lived cycles of demands for this type of knowledge pose for ensuring the right qualification of the labor force, the article explores how companies and associations provide training and certification programs as part of a growing market for educational services setting their own standards. The existing literature on non-conventional forms of authority in the global political economy has emphasized that the consent of actors, subject to informal rules and some form of state support, remains crucial for the effectiveness of those new forms of power. However, analyses based on a limited sample of actors tend toward a narrow understanding of the issues concerned and fail to fully explore the differentiated space in which non state authority is emerging. This article develops a three-dimensional analytical framework that brings together the scope of the issues involved, the range of nonstate actors concerned, and the spatial scope of their authority. The empirical findings highlight the limits of these new forms of nonstate authority and shed light on the role of the state and international governmental organizations in this new context.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Occupational UV exposure in French outdoor workers.

OBJECTIVES: Occupational ultraviolet (UV) exposure was evaluated in a population-based sample in France. METHODS: A random survey was conducted in 2012 in individuals aged 25 to 69 years. The median daily standard erythemal UV dose (SED) was estimated from exposure time and place and matched to satellite UV records. RESULTS: A total of 889 individuals were exposed to solar UV with highest doses observed among gardeners (1.19 SED), construction workers (1.13 SED), agricultural workers (0.95 SED), and culture/art/social science workers (0.92 SED). Information and communication technology, industry, and transport workers were highly exposed (>0.70 SED). Significant factors associated with high occupational UV exposure were sex (P < 0.0001), phototype (P = 0.0003), and taking lunch outdoors (P < 0.0001). CONCLUSIONS: This study identified not only expected occupations with high UV exposure but also unexpected occupations with high exposures. This could serve as a basis for future prevention.