To clarify the proper role of values in science, focusing on controversial expert responses to Covid-19, this article examines the status of (in)convenient hypotheses. Polarizing cases like health experts downplaying mask efficacy to save resources for healthcare workers, or scientists dismissing “accidental lab leak” hypotheses in view of potential xenophobia, plausibly involve modifying evidential standards for (in)convenient claims. Societies could accept that scientists handle (in)convenient claims just like nonscientists, and give experts less political power. Or societies could hold scientists to (...) a higher bar, by expecting them not to modify evidential standards to avoid costs only incidentally tied to error. (shrink)

Over the last twenty-five years, climate scientists working on the attribution of climate change to humans have developed increasingly sophisticated statistical models in a process that can be understood as a kind of calibration: the gradual changes to the statistical models employed in attribution studies served as iterative revisions to a measurement(-like) procedure motivated primarily by the aim of neutralizing particularly troublesome sources of error or uncertainty. This practice is in keeping with recent work on the evaluation of models more (...) generally that views models as tools for particular tasks: what drives the process is the desire for models that provide more reliable grounds for inference rather than accuracy to the underlying mechanisms of data-generation. (shrink)

Conciliationism is the family of views that rationality requires agents to reduce confidence or suspend belief in p when acknowledged epistemic peers (i.e. agents who are (approximately) equally well-informed and intellectually capable) disagree about p. While Conciliationism is prima facie plausible, some have argued that Conciliationism is not an adequate theory of peer disagreement because it is self-undermining. Responses to this challenge can be put into two mutually exclusive and exhaustive groups: the Solution Responses which deny Conciliationism is self-undermining and (...) attempt to provide arguments which demonstrate this; and the Skeptical Responses which accept that Conciliationism is self-undermining but attempt to mitigate this result by arguing this is either impermanent and/or not very worrisome. I argue that, by Conciliationism’s own lights, both kinds of responses (almost certainly) fail to save Conciliationism from being self-undermining. Thus, Conciliationism is (almost certainly) permanently self-undermining. This result is significant because it demonstrates that Conciliationism is likely hopeless: there is likely nothing that can save Conciliationism from this challenge. I further argue that Conciliationism, like any view, should be abandoned if it is (almost certainly) hopeless. (shrink)

I examine error diagnosis (model-model disagreement) in climate model intercomparisons including its difficulties, fruitful examples, and prospects for streamlining error diagnosis. I suggest that features of climate model intercomparisons pose a more significant challenge for error diagnosis than do features of individual model construction and complexity. Such features of intercomparisons include, e.g., the number of models involved, how models from different institutions interrelate, and what scientists know about each model. By considering numerous examples in the climate modeling literature, I distill (...) general strategies (e.g., employing physical reasoning and using dimension reduction techniques) used to diagnose model error. Based on these examples, I argue that an error repertoire could be beneficial for improving error diagnosis in climate modeling, although constructing one faces several difficulties. Finally, I suggest that the practice of error diagnosis demonstrates that scientists have a tacit-yet-working understanding of their models which has been under-appreciated by some philosophers. (shrink)