Modelling Scientific Communities

This Element will overview research using models to understand scientific practice. Models are useful for reasoning about groups and processes that are complicated and distributed across time and space, i.e., those that are difficult to study using empirical methods alone. Science fits this picture. For this reason, it is no surprise that researchers have turned to models over the last few decades to study various features of science. The different sections of the element are mostly organized around different modeling approaches. The models described in this element sometimes yield take-aways that are straightforward, and at other times more nuanced. The Element ultimately argues that while these models are epistemically useful, the best way to employ most of them to understand and improve science is in combination with empirical methods and other sorts of theorizing.

Sommario

1. Introduction; 2. The credit economy; 3. The natural selection of science; 4. Social networks and scientific knowledge; 5. Epistemic landscapes; 6. The replication crisis and methodological reform; 7. The replication crisis and methodological reform; Bibliography.

Dettagli sul prodotto

• Autori: Cailin O'Connor, Cailin (University of California O''connor
• Editore: Cambridge University Press ELT
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 21.12.2023
• EAN: 9781009359542
• ISBN: 978-1-0-0935954-2
• Pagine: 94
• Serie: Elements in the Philosophy of Science
• Categorie: Scienze naturali, medicina, informatica, tecnica > Scienze naturali, tematiche generali; SCIENCE / Philosophy & Social Aspects, Philosophy of Science, Labour / income economics, Labour Economics, Philosophy: epistemology & theory of knowledge, Philosophy: epistemology and theory of knowledge, Credit and credit institutions, Credit & Credit Institutions