Precision Index in the Multivariate Context

General multivariate quantiles are employed to extend the classic univariate process precision index to the multivariate context under very mild conditions. Using halfspace depth regions for this purpose is especially recommended because it leads to both computational simplicity and natural generalizations to the tool-wear setup thanks to some recent advances in multiple-output and projectional quantile regression. A few examples are included to illustrate how the methodology might work in practice.     

Discrimination among bivariate beta-generated distributions

Some properties of the general families of bivariate distributions generated by beta dependent random variables are derived and discussed here. Some classic measures of dependence and information are derived, and their behaviours and properties are discussed as well. Finally, a discrimination procedure within this general family of bivariate distributions is proposed based on Shannon entropy. A real-life example is presented to illustrate the model as well as the inferential results developed here.     

Strengthening the science–policy interface in the climate migration field

The question of how climatic changes and hazards affect human mobility has increasingly gained prominence in public debates over the past decade. Despite improvements in the scientific understanding of the subject and advancements in policy, major gaps remain in addressing the humanitarian and socio-economic challenges related to climate migration. In this perspectives article, we argue for a holistic approach and a closer integration of science and policy involving diverse stakeholders in the process of knowledge generation and implementation. We identify five key challenges characteristic for improving the science–policy interface: (i) conflictual political contexts and the securitization of human migration, (ii) simplistic narratives and framing of the subject, (iii) the uneven production and dissemination of knowledge, (iv) limited data and analytical capacities and (v) a selective topical and methodological focus. To address these diverse challenges, there is a need for more bridging initiatives at the science–policy interface that integrate diverse disciplines, approaches and stakeholders. A closer engagement of researchers and policymakers in the form of multi-stakeholder exchanges, capacity-building activities, co-development and co-implementation processes and integrative scientific assessments can help bridge the gap to support the inclusive generation of knowledge and the development of comprehensive policies.