Literature DB >> 33058024

Emergence of scientific understanding in real-time ecological research practice.

Luana Poliseli1,2,3.   

Abstract

Scientific understanding as a subject of inquiry has become widely discussed in philosophy of science and is often addressed through case studies from history of science. Even though these historical reconstructions engage with details of scientific practice, they usually provide only limited information about the gradual formation of understanding in ongoing processes of model and theory construction. Based on a qualitative ethnographic study of an ecological research project, this article shifts attention from understanding in the context of historical case studies to evidence of current case studies. By taking de Regt's (Understanding scientific understanding. Oxford University Press, New York, 2017) contextual theory of scientific understanding into the field, it confirms core tenets of the contextual theory (e.g. the crucial role of visualization and visualizability) suggesting a normative character with respect to scientific activities. However, the case study also shows the limitations of de Regt's latest version of this theory as an attempt to explain the development of understanding in current practice. This article provides a model representing the emergence of scientific understanding that exposes main features of scientific understanding such as its gradual formation, its relation to skills and imagination, and its capacity for knowledge selectivity. The ethnographic evidence presented here supports the claim that something unique can be learned by looking into ongoing research practices that can't be gained by studying historical case studies.

Keywords:  Imagination; Knowledge selectivity; Model building; Philosophy of science in practice; Skills; Visualization

Mesh:

Year:  2020        PMID: 33058024     DOI: 10.1007/s40656-020-00338-7

Source DB:  PubMed          Journal:  Hist Philos Life Sci        ISSN: 0391-9714            Impact factor:   1.205


  1 in total

1.  Descriptive understanding and prediction in COVID-19 modelling.

Authors:  Johannes Findl; Javier Suárez
Journal:  Hist Philos Life Sci       Date:  2021-09-21       Impact factor: 1.205

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.