The terms ``objectivity'''' and ``objective'''' are among the mostused yet ill-defined terms in the philosophy of science and epistemology. Common to all thevarious usages is the rhetorical force of ``I endorse this and you should too'''', orto put it more mildly, that one should trust the outcome of the objectivity-producing process.The persuasive endorsement and call to trust provide some conceptual coherenceto objectivity, but the reference to objectivity is hopefully not merely an attemptat persuasive endorsement. What, in addition to epistemological endorsement,does (...) objectivity carry with it? Drawing on recent historical and philosophical work,I articulate eight operationally accessible and distinct senses of objectivity.While there are links among these senses, providing cohesion to the concept, I argue thatnone of the eight senses is strictly reducible to the others, giving objectivity itsirreducible complexity. (shrink)

Climate change assessments rely upon scenarios of socioeconomic developments to conceptualize alternative outcomes for global greenhouse gas emissions. These are used in conjunction with climate models to make projections of future climate. Specifically, the estimations of greenhouse gas emissions based on socioeconomic scenarios constrain climate models in their outcomes of temperatures, precipitation, etc. Traditionally, the fundamental logic of the socioeconomic scenarios—that is, the logic that makes them plausible—is developed and prioritized using methods that are very subjective. This introduces a fundamental (...) challenge for climate change assessment: The veracity of projections of future climate currently rests on subjective ground. We elaborate on these subjective aspects of scenarios in climate change research. We then consider an alternative method for developing scenarios, a systems dynamics approach called ‘Cross-Impact Balance’ (CIB) analysis. We discuss notions of ‘objective’ and ‘objectivity’ as criteria for distinguishing appropriate scenario methods for climate change research. We distinguish seven distinct meanings of ‘objective,’ and demonstrate that CIB analysis is more objective than traditional subjective approaches. However, we also consider criticisms concerning which of the seven meanings of ‘objective’ are appropriate for scenario work. Finally, we arrive at conclusions regarding which meanings of ‘objective’ and ‘objectivity’ are relevant for climate change research. Because scientific assessments uncover knowledge relevant to the responses of a real, independently existing climate system, this requires scenario methodologies employed in such studies to also uphold the seven meanings of ‘objective’ and ‘objectivity.’. (shrink)

This is an important book precisely because there is none other quite like it.

Biased research occurs frequently in the sciences. In this paper, I will focus on one particular kind of biased research: research that is subject to sponsorship bias. I will address the following epistemological question: what precisely is epistemically wrong with biased research of this kind? I will defend the evidential account of epistemic wrongness: that is, research affected by sponsorship bias is epistemically wrong if and only if the researchers in question make false claims about the evidential support of some (...) hypothesis H by data E. I will argue that the evidential account captures the epistemic wrongness of three paradigmatic types of sponsorship bias. (shrink)