Carnapian explication, formalisms as cognitive tools, and the paradox of adequate formalization

Catarina Dutilh Novaes*, Erich Reck

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Explication is the conceptual cornerstone of Carnap’s approach to the methodology of scientific analysis. From a philosophical point of view, it gives rise to a number of questions that need to be addressed, but which do not seem to have been fully addressed by Carnap himself. This paper reconsiders Carnapian explication by comparing it to a different approach: the ‘formalisms as cognitive tools’ conception (Formal languages in logic. Cambridge University Press, Cambridge 2012a). The comparison allows us to discuss a number of aspects of the Carnapian methodology, as well as issues pertaining to formalization in general. We start by introducing Carnap’s conception of explication, arguing that there is a tension between his proposed criteria of fruitfulness and similarity; we also argue that his further desideratum of exactness is less crucial than might appear at first. We then bring in the general idea of formalisms as cognitive tools, mainly by discussing the reliability of so-called statistical prediction rules (SPRs), i.e. simple algorithms used to make predictions across a range of areas. SPRs allow for a concrete instantiation of Carnap’s fruitfulness desideratum, which is arguably the most important desideratum for him. Finally, we elaborate on what we call the ‘paradox of adequate formalization’, which for the Carnapian corresponds to the tension between similarity and fruitfulness. We conclude by noting that formalization is an inherently paradoxical enterprise in general, but one worth engaging in given the ‘cognitive boost’ it affords as a tool for discovery.

Original languageEnglish
Pages (from-to)195-215
Number of pages21
Issue number1
Publication statusPublished - 1 Jan 2017
Externally publishedYes


  • Carnap
  • Cognitive artifacts
  • Enlightenment
  • Explication
  • Formalization
  • Statistical Prediction Rules


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