Wetenschappelijk begrijpen: structureren en conceptualiseren

Aha! Zo zit het in elkaar! Nu begrijp ik het! Waarom heb ik dat niet eerder gezien?’ ‘Kwantummechanica is niet te begrijpen, het is onvoorstelbaar, maar je kunt er wel goed mee rekenen.’ Twee even herkenbare als spiegelbeeldige uitspraken over begrijpen in de wetenschap. Begrijpen lijkt een psychologische toestand te zijn die wordt opgeroepen als we door de dingen kunnen heen kijken. De metafoor van zien verwijst naar een invloedrijke Platonistische notie: het schouwen van een diepere, echtere realiteit. Wetenschappelijk begrijpen is dan het ‘voor ogen krijgen’ van de wereld achter de verschijnselen. Deze voorstelling van zaken heeft verwantschap met gewone intuïties, maar er zitten toch een aantal haken en ogen aa

The role of disciplinary perspectives in an epistemology of scientific models

The purpose of this article is to develop an epistemology of scientific models in scientific research practices, and to show that disciplinary perspectives have crucial role in such an epistemology. A transcendental (Kantian) approach is taken, aimed at explanations of the kinds of questions relevant to the intended epistemology, such as “How is it possible that models provide knowledge about aspects of reality?” The approach is also pragmatic in the sense that the questions and explanations must be adequate and relevant to concrete scientific practice. First it is explained why the idea of models as representations in terms of similarity or isomorphism between a model and its target is too limited as a basis for this epistemology. An important finding is that the target-phenomenon is usually not something that can be observed in a straightforward manner, but requires both characterization in terms of measurable variables and subsumption under (scientific) concepts. The loss of this basis leads to a number of issues, such as: how can models be interpreted as representations if models also include conceptually meaningful linguistic content; how can researchers identify non-observable real-world target-phenomena that are then represented in the model; how do models enable inferential reasoning in performing epistemic tasks by researchers; and, how to justify scientific models. My proposal is to deal with these issues by analyzing how models are constructed, rather than by looking at ready-made models. Based on this analysis, I claim that the identification of phenomena and the construction of scientific models is guided and also confined by the disciplinary perspective within which researchers in a scientific discipline have learned to work. I propose a Kuhnian framework by which the disciplinary perspective can be systematically articulated. Finally, I argue that harmful forms of subjectivism, due to the loss of the belief that models objectively represent aspects of reality, can be overcome by making the disciplinary perspective(s) in a research project explicit, thereby enabling its critical assessment, for which the proposed Kuhnian framework provides a tool