About Me (Archived Academic Website)
I am a doctoral candidate in philosophy at UMass, Amherst. I research a wide variety of topics from the perspective of an abiding commitment to methodological and metaphysical naturalism.
My dissertation builds theoretical connections between the philosophy of well-being and the sciences of well-being as practiced by psychologists, economists, health scientists, and others. Following Michael Bishop (The Good Life, 2015), I argue that the well-being of individuals and super-individuals (e.g. institutions, organizations, ecosystems) should be construed as extended and complex causal networks rather than as intrinsic properties. In support of this view, I examine the methods and assumptions of both traditional philosophical theories of well-being and the many fields of well-being science, which seem to be in insoluble tension both within themselves and with each other.
Despite those tensions, scientists have still made abundant progress in measuring and intervening on well-being in numerous fields. I take it that we have accumulated some objective knowledge of human, animal, and environmental well-being in both our current global context and within specific contexts (e.g. cultural, climatological, organizational, economic). However, the sciences of well-being have grown to include new branches and fields, each with different subjects and methods, and each with its own internal branches. The prevailing view in much of well-being science is that, because "well-being" is used to mean different things by different scientists and scientific fields, there is nothing interesting to be said about well-being as a whole, or as a unified phenomenon. I show that this view is false. By understanding well-being as a matter of complex networks, we can draw important connections and generalizations between very disparate sciences.
Drawing on developments in naturalistic philosophy, I outline in detail an alternative method for philosophical well-being theory that avoids those tensions. Application of this method to well-being science reveals that well-being scientists generally treat well-being as a causal network and aim to measure complex causal relations between factors that make for well-being. I go on to refine and expand this view in light of new developments in well-being science since the publication of Bishop's book. Developments in the past ten years of well-being science have pushed scientists in many fields toward the understanding that health and well-being for individuals is bound up in all manner of interactions at every scale, from the molecular to the global economic and climatological.
My current focus is an application of this view in an analysis of native seed distribution networks in the northeastern United States. Through a case study, I show that a causal network view is built into the ways in which seed networks are organized, developed, and maintained. Seed networks are sensitive to causal interactions between a very large number of factors. Balancing seed distribution with maintaining and expanding seed production, while also building the network's resiliency to disruption, involves modeling the relationships between factors one might expect such as climate conditions, precipitation, and soil health. But it also requires modeling (among many other things) cashflow, the reproductive rates of seed production facilities and planted seeds, the interaction between plants used as roadside drainage and air quality in the surrounding area, the incursion of non-native plant and animal species, the availability of vehicles for distribution, the cost of fuel, and the available workforce.
To make that long story short, this is exactly what the network view of well-being predicts we should expect. There are conditions that are objectively conducive to native seed production and conditions that are objectively disruptive. To understand those conditions, seed networks are modeled as a network of complex causation between factors at many different scales and of many different kinds.
When I'm not working on philosophy, or labor organizing, you can find me winning at trivia, playing the guitar and other instruments, watching Star Trek, and listening to The Boss.
My dissertation builds theoretical connections between the philosophy of well-being and the sciences of well-being as practiced by psychologists, economists, health scientists, and others. Following Michael Bishop (The Good Life, 2015), I argue that the well-being of individuals and super-individuals (e.g. institutions, organizations, ecosystems) should be construed as extended and complex causal networks rather than as intrinsic properties. In support of this view, I examine the methods and assumptions of both traditional philosophical theories of well-being and the many fields of well-being science, which seem to be in insoluble tension both within themselves and with each other.
Despite those tensions, scientists have still made abundant progress in measuring and intervening on well-being in numerous fields. I take it that we have accumulated some objective knowledge of human, animal, and environmental well-being in both our current global context and within specific contexts (e.g. cultural, climatological, organizational, economic). However, the sciences of well-being have grown to include new branches and fields, each with different subjects and methods, and each with its own internal branches. The prevailing view in much of well-being science is that, because "well-being" is used to mean different things by different scientists and scientific fields, there is nothing interesting to be said about well-being as a whole, or as a unified phenomenon. I show that this view is false. By understanding well-being as a matter of complex networks, we can draw important connections and generalizations between very disparate sciences.
Drawing on developments in naturalistic philosophy, I outline in detail an alternative method for philosophical well-being theory that avoids those tensions. Application of this method to well-being science reveals that well-being scientists generally treat well-being as a causal network and aim to measure complex causal relations between factors that make for well-being. I go on to refine and expand this view in light of new developments in well-being science since the publication of Bishop's book. Developments in the past ten years of well-being science have pushed scientists in many fields toward the understanding that health and well-being for individuals is bound up in all manner of interactions at every scale, from the molecular to the global economic and climatological.
My current focus is an application of this view in an analysis of native seed distribution networks in the northeastern United States. Through a case study, I show that a causal network view is built into the ways in which seed networks are organized, developed, and maintained. Seed networks are sensitive to causal interactions between a very large number of factors. Balancing seed distribution with maintaining and expanding seed production, while also building the network's resiliency to disruption, involves modeling the relationships between factors one might expect such as climate conditions, precipitation, and soil health. But it also requires modeling (among many other things) cashflow, the reproductive rates of seed production facilities and planted seeds, the interaction between plants used as roadside drainage and air quality in the surrounding area, the incursion of non-native plant and animal species, the availability of vehicles for distribution, the cost of fuel, and the available workforce.
To make that long story short, this is exactly what the network view of well-being predicts we should expect. There are conditions that are objectively conducive to native seed production and conditions that are objectively disruptive. To understand those conditions, seed networks are modeled as a network of complex causation between factors at many different scales and of many different kinds.
When I'm not working on philosophy, or labor organizing, you can find me winning at trivia, playing the guitar and other instruments, watching Star Trek, and listening to The Boss.