Aline Potiron,
"Data, Measurement, and Causality: Challenges from Modern Microbiology"
, 8-2024
Original Titel:
Data, Measurement, and Causality: Challenges from Modern Microbiology
Sprache des Titels:
Englisch
Original Kurzfassung:
This dissertation adopts a practice-oriented approach to explore the intersection of philosophy and microbiology. Through a series of case studies rooted in microbial
ecology and microbiome research, I scrutinize, challenge, and eventually refine existing philosophical frameworks in data, diversity measurement, and
causality.
By examining current practices in microbiology, I distinguish a new category of data ? biological samples ? and develop criteria to delineate them, which is
essential for scientific knowledge construction. I also offer an alternative view on diversity measurement, shifting the focus from conceptual definition to practical measurement. Instead, I suggest using the purpose of inquiry to guide the choice
of diversity indices. Additionally, I propose the model-based account of measurement for microbial ecology and advocate for a shift towards a systems worldview
in microbiome studies. Finally, I use the inferentialist theory of causation, which provides a more flexible and context-dependent framework for understanding causal relationships in microbiome studies.
Overall, this research demonstrates how the study of scientific practice can inform philosophical inquiry and vice versa. Engaging with philosophical concepts and methods can help scientists develop a deeper understanding of their field?s complexities and design more effective strategies for scientific inquiry. Finally,
my work contributes to our understanding of scientific objects, measurement, and causality and opens up new avenues for future research in the philosophy of science.
Forschungs-