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Carlo Debernardi

202011171127th debernardi

 

Topic of the thesis: The division of cognitive labor: a quantitative model proposal of the social structure of science.

Abstract: In recent years growing concerns have arisen within the scientific community. The debate on funding allocation, research evaluation exercises and the replicability crisis are some of the driving factors. In philosophy of science these issues are addressed with models on the division of cognitive labor. The most recent models are inspired by the NK-model, a model of evolution developed in the computational biology field. However, the epistemic landscape assumed by philosophers as the "genotype space" of their models is an abstract structure, without empirical commitment. Furthermore, the current models of division of cognitive labor - limiting themselves to a simplified version of the NK-model - lack generality and fail to represent relevant features of the original model, in particular those that give rise to complex phenomena. The aim of this project is to formulate a new model of division of cognitive labor, able to recover the NK-model generality and to be calibrated on empirical data. Two sources of data are particularly promising: on the one hand bibliometrics, especially fuzzy clustering on citational graphs, on the other the NLP area of claim detection, wich allows to extract theoretical stances from texts. A work of this kind would shed light on the social mechanisms of the scientific community. Furthermore, it would allow decisive progress in the formulation of effective science policies, which can overcome challenges such as maintaining an adequate degree of pluralism and creating suitable incentives for the replication of studies..

Research interests: Sociology of science – Bibliometrics – Generative social sciences – Agent-based modeling – Network analysis - Social epistemology.

Graduated from: University of Turin (BA) – University of Florence (MA).

Degrees obtained: BA in Philosophy – MA in Philosophy and History of Science.

E-mail address: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

 

 

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