This paper begins by distinguishing intrinsic and extrinsic contributions of mathematics to scientific representation. This leads to two investigations into how these different sorts of contributions relate to confirmation. I present a way of accommodating both contributions that complicates the traditional assumptions of confirmation theory. In particular, I argue that subjective Bayesianism does best accounting for extrinsic contributions, while objective Bayesianism is more promising for intrinsic contributions.

Generalisation, universal knowledge claims, and recommendations within disaster studies are problematic because they lead to miscommunication and the misapplication of actionable knowledge. The consequences and impacts thereof are not often considered by experts; forgone as irrelevant to the academic division of labour. There is a disconnect between expert assertions for disaster risk reduction (DRR) and their practical suitability for laypersons. Experts currently assert independently of the context within which protective action measures (PAMs) are to be used, measures unconnected to the (...) people for whom they are developed. This has knock-on effects for DRR: much expert-generated science and policy remains unused, unimplemented, and sometimes misapplied. I use philosophical accounts of assertion and epistemic blame to highlight the epistemic relationship between experts and laypersons. This relationship includes responsibilities and agreements between epistemic agents. Since multilevel DRR knowledge still transfers top-down from experts to laypersons, if experts impair the epistemic relationship, they can be held epistemically blameworthy. To address the pervasiveness of top-down systems, I analyse the epistemic framings and narratives currently shaping DRR, and more specifically PAMs and campaigns. I deconstruct universal perspectives that dominate the epistemic processes of generating, disseminating, and implementing DRR knowledge and specifically for co-seismic landslide PAMs for Nepal. I argue for more inclusive, contextual, and epistemically responsible DRR. Co-production of knowledge should begin from the standpoints of marginalised persons who may have an epistemic advantage due to their socio-politically marginalised positions. Often these epistemic contributions are left out of DRR efforts because marginalised persons are rarely afforded equal, if any, epistemic agency, which results in epistemic gaps and a large pool of relevant knowledge remaining unincorporated and unused in DRR research and policy. (shrink)

I offer an explicit account of the underdetermination thesis as well as of the many challenges it poses to scientific realism; a way to answer to these challenges is explored and outlined, by shifting attention to the content of theories. I argue that, even if we have solid grounds (as I contend we do) to support that some varieties of the underdetermination thesis are true, scientific realism can still offer an adequate picture of the aims and achievements of science.

In der neueren Erkenntnistheorie wird der Bayesianismus immer populärer. In diesem Ansatz werden Überzeugungen mit Glaubensgraden versehen. Dazu möchte ich der Frage nachgehen, ob wir den klassischen Ansatz in der Erkennnistheorie mit seinen kategorischen Überzeugungen komplett durch einen bayesianischen mit einem probabilistischen Überzeugungssystem ersetzen könnten. Um das zu klären, rekonstruiere ich zunächst beide Modelle unserer Überzeugungssysteme und vergleiche sie dann im Hinblick darauf, wie leistungsfähig sie jeweils dafür sind, erkenntnistheoretische Probleme zu lösen und als Grundlage für Entscheidungen zu dienen. Dabei (...) zeigt sich eine gewisse Inkommensurabilität der beiden Ansätze und außerdem erweist sich keine der Konzeptionen als eindeutig überlegen. Deshalb argumentiere ich schließlich für eine bestimmte Hybridkonzeption aus beiden Ansätzen, die die Vorteile beider Konzeptionen vereinen kann. (shrink)