Abstract
Angela Potochnik’s Idealization and the Aims of Science (Chicago) defends an ambitious and systematic account of scientific knowledge: ultimately science pursues human understanding rather than truth. Potochnik argues that idealization is rampant and unchecked in science. Further, given that idealizations involve departures from truth, this suggests science is not primarily about truth. I explore the relationship between truths about causal patterns and scientific understanding in light of this, and suggest that Potochnik underestimates the importance and power of highly particular narrative explanations.
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Notes
See, for instance, debates between structuralists and fictionalists about modelling (e.g., Weisberg 2012).
You might worry that this relies on arcane questions concerning the relationship between know-how and know-that: if ultimately know-how may be collapsed into know-that—if all knowledge is ultimately propositional—does this undermine the difference? And is the view beholden to that debate? I don’t think so. Potochnik is interested in science as conducted by limited human agents and, as such, whether or not abilities are ultimately just sets of propositions is irrelevant.
Such narratives are themselves at least as incomplete as other scientific explanations: a history which recounts the history of each particle is a terrible history, at least for limited agents such as ourselves. As such, a historical narrative—just like a causal pattern—is indexed to our explanatory interests. However because they are not recurrent I think they shouldn’t be considered ‘causal patterns’ in Potochnik’s sense.
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Acknowledgements
Many thanks to Kirsten Walsh and Angela Potochnik for generous help with earlier drafts.
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Currie, A. Big dragons on small islands: generality and particularity in science. Biol Philos 33, 20 (2018). https://doi.org/10.1007/s10539-018-9631-5
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DOI: https://doi.org/10.1007/s10539-018-9631-5