Dimanche, Udem – 11h à 11h45
Central banks are organizations responsible for the monetary policy of a given currency zone. They were given a high degree of operational independence in the 90s, and they provide most of the academic research the matter (Claveau et Dion 2018).
The fact that we (socially) recognize central banks as epistemically superior agents (Claveau et Prud’homme 2018) should not compel us to blind trust. This talk falls within a larger effort of critically evaluating experts and experts organizations (e.g.: Tetlock 2017; Goldman 2001; Dietsch, Claveau, et Fontan 2018). We have evidence that central banks are engaged in epistemological reflections on their own research practices but, unfortunately, the precise characteristics of this reflection are unknown. The field of System-oriented social epistemology (Goldman 2010; Goldman et Whitcomb 2011) can help us conceptualize the central banks as socio-epistemic systems. Now, fortunately, there is some research that can be found in social epistemology and in STS (Science, Technology and Society) about beneficial characteristics of socio-epistemic systems. Therefore, if only we could have a better picture of the epistemological reflection of the central banks, we could challenge it with those beneficial characteristics.
This talk aims to provide such a picture for the Bank of Canada (BoC). Computer assisted text analysis methods (Aggarwal et Zhai 2012; Poudat et Landragin 2017; Berry et Kogan 2010) were exploited to gather and analyse a corpus of official documents (e.g. speeches from officials, research papers, evaluation reports) originating from the bank. Efforts were targeted at conceptualizing a “grid of analysis” of the epistemological reflection at the BoC. That grid allows for an empirically informed conceptual analysis of the research done at the BoC. These are the preliminary steps for a larger scale evaluation of the epistemological reflection of the Bank.
Aggarwal, Charu C, et ChengXiang Zhai, éd. 2012. Mining Text Data. New York: Springer.
Berry, Michael W., et Jacob Kogan, éd. 2010. Text mining: applications and theory. Chichester, U.K: Wiley.
Claveau, François, et Jérémie Dion. 2018. « Quantifying Central Banks’ Scientization: Why and How to Do a Quantified Organizational History of Economics ». Journal of Economic Methodology, octobre, 1‑18.
Claveau, François, et Julien Prud’homme, éd. 2018. Experts, sciences et sociétés. Montréal: Presses de l’Université de Montréal.
Goldman, Alvin I. 2001. « Experts: Which Ones Should You Trust? » Philosophy and Phenomenological Research 63 (1): 85–110.
———. 2010. « Systems-Oriented Social Epistemology ». In Oxford Studies in Epistemology, édité par T.S Gendler et J. Hawthorne, 3:189‑214.
Goldman, Alvin I., et Dennis Whitcomb, éd. 2011. Social Epistemology: Essential Readings. New York: Oxford University Press.
Longino, Helen E. 1990. Science as Social Knowledge. Princeton: Princeton University Press.
———. 2002. The Fate of Knowledge. Princeton: Princeton University Press.
Poudat, Céline, et Frederic Landragin. 2017. « Dégager les spécificités des parties d’un corpus ». In Explorer des données textuelles: méthodes – pratiques – outils, 1re. édition, 154‑81. Champs linguistiques, Recherches. Paris: De Boeck supérieur.
Tetlock, Philip E. 2017. Expert Political Judgment: How Good Is It? How Can We Know? Princeton University Press.