Objectivity in the sciences is a much-touted yet problematic concept. It is sometimes held up as characterising scientific knowledge, yet operational definitions are diverse and call for such paradoxical genius as the ability to see without a perspective, to predict repeatability, to elicit nature’s own self-revelation, or to discern the structure of reality with inerrancy. Here we propose a positive and general definition of objectivity based on work in the Reformational philosophy tradition. We recognise a suite of relation-frames–ways in which (...) things function and relate to each other, which can be analytically distinguished in the process of conceptual abstraction. These relation-frames also ground the diverse aspects of scientific analysis within which relationships and properties may be abstracted from entities and systems. We argue that objectivity can be understood as characteristic of representations that attempt to portray a subject in an earlier relation-frame than that in which it characteristically functions. In short, objectivity is projection. This proposal is exemplified from mathematics and the natural sciences and some possible objections to it are considered, as well as its extension to the social sciences. (shrink)

The applied discipline of agroecological design provides a useful case study for examining broader philosophical questions about the existence and importance of ecological generalizations or “laws.” Recent developments in the availability and use of formal meta-analyses have led to the discovery of many resilient generalizations in ecology (Linquist et al. 2016). However, these “laws” face numerous challenges when it comes to their practical application. Concerns about their reliability and scope might stem from unclear logical and epistemic connections to more foundational (...) or “unifying” generalizations (Lean in Philos Top 47(1), 2019) which, in ecology, tend to be derived from first principles and in association with highly abstract models. This raises questions about the nature of those foundational generalizations themselves. In particular, how resilient are they compared to the generalizations uncovered by empirically driven methods? Here we propose a procedure for evaluating the resilience of generalizations across five ecologically relevant dimensions. This procedure was applied to seven well known foundational generalizations in ecology. Surprisingly, it turned out to be impossible to estimate the resilience of these foundational generalizations based on the available literature. This points to the need for a more centralized repository of information about ecological generalizations, created with the explicit aim of evaluating such important dimensions as causal mechanism and predictive power. (shrink)