My philosophical research is about scientific methodology, and in particular how scientists build mathematical models to acquire knowledge about complex systems in the world. Typical questions I am interested in exploring are: How do scientists identify phenomena of interest? What kind of simplifications are introduced in models of phenomena, and how are they justified?

I use examples from contemporary sciences and their history to answer these questions. My dissertation, for example, draws from case studies in atmospheric science and oceanography to illustrate the challenges that are tied to identifying phenomena, and what kind of assumptions are made in the process of isolating target systems from their environment.

I am also interested in the social and political aspects of climate science, such as issues at the intersection of epistemology, environmental ethics and public policy.

Here is my full dissertation summary.


Baldissera Pacchetti, M. (2018). A role for spatiotemporal scales in modeling. Studies in History and Philosophy of Science Part A, 67, 14-21.

Work in Progress

“Spatiotemporal Scales and Structural Uncertainty”

In this paper I explore the epistemic consequences of the use of scale related assumptions in characterizing phenomena for what some philosophers and climate scientists have called ‘Structural Uncertainty’, which is uncertainty about the form of the equations that represent the phenomenon of interest. I argue that structural uncertainty can arise when there is no clear empirical justification for the use of scale related assumptions. The lack of justification may arise because either the data does not clearly display scale separation, which allows scientists to justify excluding certain smaller scale physics, or because the phenomenon is thought to occur on many different scales.

“Scaling behavior of forest gap structure in deciduous forests”

In this paper I explore the scaling structure of tree-fall disturbance structure in Appalachian forests. This study asks whether small scale structure scales up in a predictable way. The aim of this paper is to investigate whether disturbance structure at different scales is deterministic or stochastic. For this study, I will be sampling disturbances in forests of SE Ohio, and perform statistical analysis to evaluate my hypotheses.