[PhilPhys] Upcoming Hybrid Talks at the Center for Philosophy of Science

[Center for Phil Sci]

The Center for Philosophy of Science at the University of Pittsburgh
invites you to join us for our upcoming Lunch Time Talks and Annual Lecture
Series presentation.  All lectures will be live streamed on YouTube at
https://www.youtube.com/channel/UCrRp47ZMXD7NXO3a9Gyh2sg.
<https://www.youtube.com/channel/UCrRp47ZMXD7NXO3a9Gyh2sg>


LTT– Nina Atanasova
Friday, September 12th @ 12:00 pm - 1:30 pm EDT
Room 1117 on the 11th floor of the Cathedral of Learning
This talk will be available online through Zoom:
https://pitt.zoom.us/j/91293273230
*Title: The Surreality of Pain*
Abstract:
Throughout the reductionist debates of the twentieth-century philosophy of
mind and science, non-reductionists often referred to pain as irreducible
mental state par excellence. Notwithstanding, reductionists have remained
unmoved in their conviction that mental states are exhaustively physical in
nature. Pain eliminativism, arguably the most radical form of reductionism,
has recently seen a revival in popularity (Baetu 2020, Corns 2020, Coninx
2021, Hardcastle 2024, Gligorov 2025). According to pain eliminativism, the
commonsense notion of pain as an irreducible subjective experience is
deeply flawed. Thus, it is to be eliminated from our vocabulary and
replaced with the terms of a mature science of pain.
The claim of eliminativism can be interpreted descriptively as a
*prediction* of what happens when the science of pain matures. However, it
can also be interpreted normatively as a *prescription* of what should
happen when the science of pain matures. Considering that the science of
pain has matured significantly since the early days of pain eliminativism
(Dennett 1978), the renewed interest in the topic is not surprising.
However, the verdicts on pain eliminativism delivered by different
philosophers are often contradictory and inconclusive. I attribute much of
the disagreement to the equivocation between predictive and prescriptive
interpretations of eliminativism.
In this talk, I aim to show that pain eliminativism has been successful
*predictively* in the case of neuroscience pain education (NPE). NPE is an
approach to chronic pain management that allows patients to reconceptualize
pain from a sign of tissue damage to a functional/dysfunctional state of
the nervous system. I argue that the success of this method suggests that
pain eliminativism can be justified *prescriptively* in other contexts
beyond the scope of science.


Featured Former Fellow* – Wayne Myrvold*
Tuesday, September 16th - *Canceled*


LTT – *Aydin Mohseni*
Friday, September 19th @ 12:00 pm - 1:30 pm EDT
Room 1117 on the 11th floor of the Cathedral of Learning
This talk will be available online through Zoom:
https://pitt.zoom.us/j/98127984221

Title:  *A Bayesian Reduction of Causation in Causal Models*
*Abstract:*
The ontological status and explanatory role of causation has been a
perennial puzzle. In recent work, Pearl and Mackenzie (2018) advance the
thesis of a causal hierarchy (PCH) and posit the irreducibility of causal
claims to purely probabilistic ones. Bareinboim et al. (2022) claim to have
proven this irreducibility in the context of structural causal models
(SCMs). We challenge this claim and demonstrate a general reduction of
interventional propositions to probabilistic ones within the same context
of SCMs and proffer a de Finetti-style representation theorem for causal
learning and reasoning.


Lunchtime Talk – William GoodwinTuesday, September 23 @ 12:00 pm - 1:30 pmRoom
1117 on the 11th floor of the Cathedral of LearningThis talk will be
available online:  Zoom: https://pitt.zoom.us/j/93124340892
Title: Kuhn’s Speciation Metaphor and the Birth of BiochemistryAbstract:

Biochemistry is an intersectional field: it, “arose by division and
recombination of specialties already matured.”  This means that standard
Kuhnian models of discipline formation cannot be expected to apply in the
case of biochemistry.  Kuhn’s later account of discipline formation is by
analogy to acts of evolutionary speciation, with ‘incommensurability’
playing the role of an isolating mechanism.  Since ‘incommensurability’
seems to play no role in the formation of biochemistry, this paper attempts
to generalize and extend Kuhn’s speciation analogy thus making a
considerably more interesting and plausible general account of discipline
formation and eliminating any essential appeal to ‘incommensurability’ in
that account.



*Annual Lecture Series - Andrea Loettgers*

Friday, September 26th at 3:30

This talk will be available online:  Zoom:
https://pitt.zoom.us/j/93042700398

*Title: Model Templates and Model-Based Unification*

Abstract:

Contemporary science is increasingly shaped by models that travel far
beyond their original disciplinary homes. The Hopfield model, born in
statistical physics and reimagined as a neural network, now informs fields
as diverse as machine learning, gene regulation, and sociology. Scale-free
networks, originating in graph theory and statistical mechanics, capture
the hub-like structure of the internet, social networks, cellular
metabolism, and citation patterns. The Kuramoto model, developed to study
coupled oscillators, now illuminates phenomena ranging from circadian
rhythms to power-grid stability.

These cases exemplify what we call *model-based unification*: the
integration of diverse research domains not through universal laws, but
through the dissemination and adaptation of shared model templates. Such
models unify by functioning as conceptual and computational scaffolds that
guide reasoning, reveal regularities, and enable cross-domain
inference—while also accumulating differences in meaning and use across
contexts.

Drawing on case studies from physics, biology, and the humanities, this
talk examines the epistemic power and risks of this mode of unification. It
considers whether network models and other transdisciplinary templates are
uncovering deep structural commonalities or simply projecting a familiar
mathematical form onto disparate systems. By tracing how models are
transformed in new domains, I will argue for a practice-centered
understanding of scientific unity—one that embraces diversity and friction
as productive forces in building connections across disciplines.
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