Modeling Innovations: Levels of Complexity in the Discovery of Novel Scientific Methods
Year: 2024
Type: article
Abstract: Scientists often disagree on the best theory to describe a scientific event. While such debates are a natural part of healthy scientific discourse, the timeframe for scientists to converge on an ideal method may not always align with real-life knowledge dynamics. In this article, I use an event from the history of chemistry as inspiration to develop Agent-Based Models of epistemic networks, exploring method selection within a scientific community. These models reveal several situations where incorrect, simpler methods can persist, even when substantial evidence supports a more complex method. This becomes particularly evident when different evidence-sharing timeframes are analyzed. The network structure connecting the scientists plays a crucial role in determining how and when convergence on the correct method is achieved, guided by real-world evidence. This framework provides a foundation for further exploration of scientists’ behavior in past and future discoveries, as well as how agents internalize scientific information.
Source: Philosophies
Author: José Ferraz-Caetano
Institutions: Universidade do Porto, Rede de Química e Tecnologia
Language: English
Subfield: History and Philosophy of Science
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,591
OpenAlex ID: W4405921429