The division of cognitive labor: two missing dimensions of the debate
- 84 Downloads
The question of the division of cognitive labor (DCL) has given rise to various models characterizing the way scientists should distribute their efforts. These models often consider the scientific community as a self-governed sphere constituted by rational agents making choices on the basis of fixed rules. Such models have recently been criticized for not taking into account the real mechanisms of science funding. Hence, the question of the utility of the DCL models in guiding science policy remains an open one. In this paper, we show that two unconsidered dimensions would have to be taken into account. First, DCL studies miss the existence of distinct levels of epistemic objectives organizing the research process. Indeed, the scientific field is structured as a system of hierarchical, interconnected practices which are defined both by their inherent purposes and by various superposed external functions. Second, I criticize the absence of ontological considerations, since the epistemological significance of pluralism is highly dependent on the nature of the object under study. Because of these missing dimensions, current DCL models might have a limited usefulness to identify good practices of research governance.
KeywordsResearch policy Research funding Division of cognitive labor Social epistemology
- Avin, S. (2018a). Policy considerations for random allocations of research funds. Roar Transactions, 6(1).Google Scholar
- Avin, S. (2018b). Centralized fundings and epistemic exploration. The British Journal for the Philosophy of Science. https://doi.org/10.1093/bjps/axx059.
- Chang, H. (2014). Epistemic activities and Systems of Practice: Units of analysis. In L. Soler, S. Zwart, M. Lynch, & V. Israel-Jost (Eds.), Philosophy of science after the practice turn. New York: Routledge.Google Scholar
- Gillies, D. (2014). Selecting applications for funding. Why random choice is better than peer-review. RT. A Journal on Research Policy and Evaluation, 2(1). https://riviste.unimi.it/index.php/roars/article/view/3834. Accessed 24 Sept 2018.
- Goldman, A., & Blanchard, T. (2016). Social epistemology. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy, winter 2016 edition. https://plato.stanford.edu/entries/epistemology-social/. Accessed 24 Sept 2018.
- Hacking, I. (1983). Representing and intervening. Cambridge: Cambridge University Press.Google Scholar
- Kitcher, P. (1993). The advancement of science. New York: Oxford University Press.Google Scholar
- Soto, A. M., & Sonnenschein, C. (2011). The tissue organization field theory of cancer: A testable replacement for the somatic mutation theory. BioEssays, 33(5), 332–340.Google Scholar
- Viola, M. (2015). Some remarks on the division of cognitive labor. Roar Transactions., 1, 1–14.Google Scholar
- Viola, M. (2018). Social epistemology at works: From philosophical theory to policy advice. Roar Transactions, 6(1). https://riviste.unimi.it/index.php/roars/article/view/9828. Accessed 24 Sept 2018.
- Wilholt, T. & Glimell, H. (2011). Conditions of science: The three-way tension of freedom, accountability and utility. In M. Carrier, & A. Norman (Eds.), Science in the context of application. Boston studies in the philosophy of science (Vol. 274, pp. 351–370). Berlin: Springer.Google Scholar
- Woody, A.-I. (2014). Chemistry’s periodic law: Rethinking representation and explanation after the turn to practice. In L. Soler, S. Zwart, M. Lynch, & V. Israel-Jost (Eds.), Science after the practice turn in the philosophy, history, and social studies of science. New York: Routledge.Google Scholar