Online research in philosophy

One of the core debates concerning equity in the response to the threat of anthropogenic climate change is how the responsibility to reduce greenhouse gas emissions should be allocated, or, correspondingly, how the right to emit greenhouse gases should be allocated. Two alternative approaches that have been widely promoted are, first, to assign obligations to the industrialized countries on the basis of both their ability to pay (wealth) and their responsibility for the majority of prior emissions, or, second, to assign (...) emissions rights on a (possibly modified) equal per capita basis. Both these proposals ignore intra-national distributional equity. Instead, we develop a policy framework we call 'Greenhouse Development Rights' (GDRs) which allocates obligations to pay for climate policies (both mitigation and adaptation) on the basis of an individually quantified metric of capacity (ability to pay) and responsibility (prior emissions). Crucially, the GDRs framework looks at the distribution of income within countries and treats people of equal wealth similarly, whatever country they live in. Thus even poor countries have obligations proportional to the size and wealth of their middle and upper classes, defined relative to a 'development threshold'. While this method nominally identifies the 'right to development' as applying to people, not countries, as a proposal for a treaty among sovereign nations, there is no obvious way to give legal meaning to that right. In this paper, then, we raise some of the philosophical and political questions that arise in trying to quantify capacity and responsibility and to use the 'right to development' as a principle for allocating costs.*. (shrink)

Much of what we need to plan for our survival is already known, but what we know, how we know, and who knows is divided up between disciplines. Thus much of the problem of ensuring our survival is a matter of learning across the disciplines. We identify four modes through which we bring disciplinary knowledge together: the unity of science, integrated assessment, heuristic models, and distributed learning networks. Although none of them are perfect, we can learn how to put our (...) knowledge together across the disciplines much better than we do. (shrink)