In this note we present a three-valued intensional logic, which is an extension of both Montague's intensional logic and ukasiewicz three-valued logic. Our system is obtained by adapting Gallin's version of intensional logic (see Gallin, D., Intensional and Higher-order Modal Logic). Here we give only the necessary modifications to the latter. An acquaintance with Gallin's work is pressuposed.

Upshot: In our response we focus on five questions that point to important common themes in the commentaries: why start in wicked problems, what kind of system is a scientific perspective, what is the nature of second-order research processes, what does this mean for understanding interdisciplinary work, and how may polyocular research help make real-world decisions.

Upshot: In our response we focus on how different types of systems are related from a constructivist perspective, and specifically on the relation between communicational social systems and embodied agency.

Open peer commentary on the article “Social Autopoiesis?” by Hugo Urrestarazu. Upshot: We agree on the need to explore a concept of social autopoiesis that goes beyond a strictly human-centered concept of social systems as autopoietic communicative systems. But both Hugo Urrestarazu and Niklas Luhmann neglect the importance of semiosis in understanding communication, and this has important implications for the question of a more general approach to social systems.

This article proposes a geostatistical solution for area-to-point spatial prediction (downscaling) taking into account boundary effects. Such effects are often poorly considered in downscaling, even though they often have significant impact on the results. The geostatistical approach proposed in this article considers two types of boundary conditions (BC), that is, a Dirichlet-type condition and a Neumann-type condition, while satisfying several critical issues in downscaling: the coherence of predictions, the explicit consideration of support differences, and the assessment of uncertainty regarding the (...) point predictions. An updating algorithm is used to reduce the computational cost of area-to-point prediction under a given BC. In a case study, area-to-point prediction under a Dirichlet-type BC and a Neumann-type BC is illustrated using simulated data, and the resulting predictions and error variances are compared with those obtained without considering such conditions. (shrink)