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

Abstract

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.

Detecting Large Concept Extensions for Conceptual Analysis

“…Multi-word expressions were excluded because detecting whether they are in the text or not would be complicated. 6 Experts' annotations were ignored because there were too few annotation instances where the queried concept's keyword was in the textual segment, and, as a result, values for the "Keyword in segment" condition were uninformative. Table 4.…”

Carnapian explication and ameliorative analysis: a systematic comparison

“…The objection by Jenkins highlights an important element of the framework, namely that ameliorative analysis is best seen as an open-ended project; proposed reconceptualizations may then be further revised if it turns out that additional improvement can be made. This is a feature that ameliorative analysis shares with Carnapian explication (Carus 2008;Dutilh Novaes and Reck 2017), which is also an open-ended process that can be iterated: the explicatum (the result) of one explication can then become the explicandum (the starting point) for a different explication.…”

“…3). 8 This section draws from the more detailed exposition of Carnapian explication in Dutilh Novaes and Reck (2017). ical concept became that of explication, 9 which is not exclusively tied to constructed languages and formalization, 10 but often does take the form of applications of artificially constructed languages. Explication is a process whereby a vague, informal concept, either from everyday life or from more regimented contexts such as scientific contexts (but in earlier stages of development), is given a more exact, often formalized formulation.…”

“…(3) Fruitfulness is the crucial requirement for a successful explication (as argued in Carus 2008;Dutilh Novaes and Reck 2017), and yet Carnap says surprisingly little on what he means by fruitfulness. Here is one of his few relevant remarks:…”

Does Experimental Philosophy Have a Role to Play in Carnapian Explication?

“…(Haslanger does not explicitly use the term ‘explication’. But, if we allow fruitfulness to incorporate political and social ends, as do Carus () and Dutilh Novaes and Reck (), then Haslanger's project is clearly an example of explication.) The explicandum is a good candidate for being vague (there are borderline cases of man and woman ), pluralistic (it is sometimes used to mean sex ), subject to bias, etc.…”