RESUMO
O'Malley et al. (2009) and Haufe (2013) suggest that the philosophical idea of science as hypothesis testing generates a pernicious bias towards hypothesis-driven research and against exploratory research in the review process of research proposals and the allocation of resources. This paper addresses a conceptual objection to the argument by O'Malley et al. (2009) and Haufe (2013). We argue that the funding agencies' concepts of good science do not belong to epistemological or philosophical contexts but to political and institutional contexts. This means that correcting (potential) biases in research funding does not entail correcting funding agencies' (supposed) philosophies of science. To illustrate this point, we provide an in-depth historical case study: the granting of funds to neuroscientist Pedro Maldonado by the Chilean funding programme FONDECYT. This is a relevant comparison as FONDECYT's guidelines explicitly promote hypothesis-driven research and endorse a view of "good science" as hypothesis testing. However, we will see that the overall influence of the philosophical idea of science as hypothesis testing over this funding programme, the research project, and the actual practice of hypothesis testing is somewhat limited. The concept of science as hypothesis testing seems to play a crucial institutional or political (not philosophical) role in allowing the conceptual articulation of social expectations and researchers' expectations.
Assuntos
Filosofia , Políticas , Chile , Filosofia/história , Conhecimento , Projetos de PesquisaRESUMO
Data production in experimental sciences depends on localised experimental systems, but the epistemic properties of data transcend the contingencies of the processes that produce them. Philosophers often believe that experimental systems instantiate but do not produce the epistemic properties of data. In this paper, we argue that experimental systems' local functioning entails intrinsic capacities to produce the epistemic properties of data. We develop this idea by applying Derrida's model of arche-writing to study a case of theory-oriented experimental practice. Derrida's model relativises or dissolves the conceptual distinction between the moment of data production and a subsequent moment of data dissemination. It thus has consequences for understanding both data production (despite being intrinsically local, data production a priori generates transferrable and modellable information) and data dissemination (when modelling information, researchers needs to refer this information to the context of its production). We study a case of data production in a non-exploratory experimental system designed to test a pre-existing hypothesis in visual neuroscience. A case of theory-oriented experimental practice should allow us to identify the autonomous functioning of experimental systems in data production more clearly, insofar as it allows us to study the limits of pre-existing theory in the activities of these systems. We suggest that pre-existing concepts, hypotheses and theories condition the relevance but not the production of experimental data.
Assuntos
Disseminação de Informação , Fenômenos Fisiológicos do Sistema Nervoso , Fala , Percepção Visual , Redação , HumanosRESUMO
Theory-free characterizations of experimental systems miss normative and conceptual components that sometimes are crucial to understanding their historical development. In the following paper, we show that these components may be part of the intrinsic capacities of experimental systems themselves. We study a case of non-exploratory and theory-oriented research in experimental neuroscience that concerns the construction of free-viewing as an experimental system to test one particular pre-existing hypothesis, the Temporal Correlation Hypothesis (TCH), at a laboratory in Santiago de Chile, during 2002-2008. We show that the system does not take well-formulated pre-existing predictions or hypotheses to test them directly, but re-creates them and re-signifies them in terms that are not implied by the theoretical background from which they originally derived. Therefore, we conclude that there is a sui generis way in which experimental systems produce proper theoretical knowledge.