Download 10 Thinking Philosophically Across the Sciences: Analogies, Models

2017 Hawai`i Meeting
Symposium Abstracts
10 Thinking Philosophically Across the Sciences: Analogies, Models, and Mechanisms
Appropriate Use of Analogy and Pacific Archaeology and Anthropology, MADS RAVN (Vejle Museums, 7100
Vejle, Denmark and Kon-Tiki Museum, 0286 Oslo, Norway; [email protected]).
Ethnographic and archeological studies of Pacific societies of the past have often been drawn upon as sources in
interpreting finds on other archeological sites. However, some scholars have questioned the appropriateness of
analogy in making use of ethnographic studies of post-contact Pacific societies to study pre-contact societies in other
parts of the world. Critics have charged "denial of history" and "pacification of the European Neolithic." This paper
is on the use of analogy in archaeology and anthropology more generally, but reveals how such concerns about the
use of Pacific ethnographic studies are due to an outdated view of analogy. Starting with very concrete finds from
the past and present, looking very similar, it is argued that a better definition of analogy, emphasizing not only
similarities but also differences and relevance, does not have the weaknesses that critics of the use of analogy so
often allege. This definition, which I propose should be used instead of ones that emphasize only similarities, allows
one to modify analogies when confronted with an increasing amount of high-resolution archaeological data. Thus,
we need not abolish the use of analogy, we need only use analogy in a more case-specific way, allowing for the
ethnographic and archaeological record to modify the analogy where it is relevant to do so, and including the
progress of knowledge already reached through the study of analogy and similar models of interpretation over the
last sixty years. Some examples of the use of analogy to interpret concrete finds are provided to illustrate.
Models and Conceptual Frameworks in Forest Regeneration Studies, WALTER P. CARSON1 and SUSAN G.
STERRETT2* (1Department of Biological Sciences, University of Pittsburgh, 212A Clapp Hall, 4249 Forbes
Avenue, Pittsburgh, PA 15260, [email protected]; 2Department of Philosophy, Wichita State University, Susan G.
Sterrett, Department of Philosophy, 1845 North Fairmount, Campus Box 74, Wichita State University, Wichita, KS
67260-0074, [email protected]).
On what bases can the regeneration of a forest following a disturbance such as a hurricane or a volcanic
eruption be predicted? One source of knowledge is the kind of natural experiment in which a forest has regenerated
after a disturbance. Natural experiments have occurred with disturbances ranging from massive windfalls due to
hurricanes that downed large areas of a forest and commercially motivated clearcutting of large areas of woodland,
to small tree gaps resulting from the falling of a tree or limb. We first describe results of previous work: a critical
assessment of the application of models drawn from such natural experiments. Some applications of forest models
based on natural experiments were found wanting due to not accounting for features of the forest's history that are
particularly relevant to regeneration after a disturbance: "(1) the size (area) of the stand prior to the disturbance and
(2) the time elapsed since the previous large-scale disturbance." An important characteristic -- propagule availability
-- was identified as the relevant concept on the basis of which a new conceptual model was developed, proposed,
and evaluated against data from natural experiments. In this paper, we articulate the analogical reasoning used in
that previous work. We then describe newer work on another kind of natural experiment in forest ecology: boulders
and treefall mounds as refugia from deer, and compare that methodology with the use of artificial experiments of
refugia from deer (fencing). We examine the philosophical bases that all this work has in common.
Experiments Using Analogue Models: The Common Conceptual Basis and the Wide Variety of Examples, SUSAN
G. STERRETT (Department of Philosophy, Wichita State University, Wichita, KS 67260-0074;
[email protected]).
Over 150 years ago, the philosopher-scientist Hermann von Helmholtz considered the quandary of analyzing
situations so complicated that the governing equations are intractable. We can sometimes learn from other, different,
cases we have observed, he wrote. The question then is how to translate from something we have observed to
something we have not. He gave a deep account of similarity of situations in hydrodynamics. The insights he
articulated about using observed cases to reason with rigor about unobserved ones are the basis for a methodology
for analogue models: situations specially constructed to be appropriately similar to, and thus informative about,
another situation that one wishes to learn about. In past work, I examined the progress in similarity methods to the
present, citing a wide variety of examples. In Earth Science, there are analogue models of the behavior of volcanoes,
earthquakes, fires, lakes, streams and rivers. At first glance, the papers on experimental forests and archeological
sites presented in this symposium may not seem to have much in common with each other, much less these
examples of analogue models. I will argue that the methodologies employed in interpreting them do: analogy and
similarity encompass them all. In fact, seeing how the role of history and context in forest
experimental/observational sites (disturbance history, forest age, seedbank composition, herbivore exclusion) and
archeological sites (e.g., pre-contact/post-contact; accompanying artifacts; land/water sites) are dealt with in
appropriate accounts of analogy can deepen our understanding of the methodology of analogue models.
Reimagining the Unity of Science in the 21st Century: Discovering Mechanisms Across the Sciences, STUART
GLENNAN (Department of Philosophy, Religion and Classics, Butler University, 4600 Sunset Avenue,
Indianapolis IN 46208; [email protected]).
The heyday of the unity of science movement was the mid-twentieth century, when logical empiricist
philosophers of science sought to show that different scientific fields could at least ideally be bound together by
axiomatized theories linked through relations of intertheoretic reduction. Failures of that research program led many
to give up on the idea of unity of science, a philosophical move that comported with increasing balkanization of
scientific disciplines. In this talk I argue that a philosophy of sciences that focuses on how scientific disciplines
discover, represent and explain mechanisms provides a more realistic and informative view of why and to what
extent unity of science is possible. This unity is both ontological and methodological – ontological because the
mechanisms examined within one scientific field depend upon or feed into mechanisms from other domains, and
methodological, because mechanisms at work in many domains may share material or organizational similarities
that allow for the use of common tools for discovery and representation. Recent work on applications of dynamical
systems theory and network analysis provide cases in point. The unity of science promised by this mechanistic
picture falls short of the aspirations of Popper or Carnap or Neurath, and it does not clearly delineate science from
non-science, but it does give an account of why and to what extent the disparate sciences hang together.
Dissolving Tensions Between Architectural Claims in Cognitive Science, ZOE DRAYSON (Department of
Philosophy, University of California, Davis, CA 95616; [email protected]).
In cognitive science, there are various approaches to the ‘architecture’ of cognition: the relatively fixed aspects
of an information-processing structure which constrain the way that the cognitive system works. Fine-grained
architectural questions might concern whether the kinds of computations involved are classical or connectionist, for
example, while coarser-grained architectural questions concern how the different computational processes interact:
whether information flow from the top down or from the bottom up, for example, and whether perceptual processes
have access to information in cognitive processes.
In this paper, I focus on predictive approaches to the mind, which propose that our cognitive architecture should
be understood as a hierarchy of Bayesian computational mechanisms. Cognitive information higher in the hierarchy
is used to generate predictions about lower-level sensory information, and information about prediction errors is
passed back up the hierarchy. Proponents of predictive approaches often claim that these architectures are in tension
with modular architectures. Modular architectures emphasize the functional independence of certain cognitive
processes, and draw a clear distinction between perceptual processing and cognitive processing.
I argue that we do not have to see predictive and modular architectures as being in tension in this way, once we
accept that continuity at one level of a cognitive architecture is compatible with discontinuity at a different level.
Furthermore, there are ways of understanding modular architectures on which predictive approaches seem to require
a sort of modularity.
Using Models to Understand Near-Earth Object Impact Hazards, ERIK M CONWAY (Jet Propulsion Laboratory,
California Institute of Technology, 4800 Oak Grove Ave., Pasadena, CA, 91109; [email protected]).
One of the major realizations of the late 20th century is the “impact hazard,” the possibility that a “Near-Earth
Object,” a comet or asteroid, of sufficient size could strike the Earth and cause significant-to-catastrophic levels of
damage. The reinterpretation of Chicxulub Crater under the Yucatan Peninsula as an impact remnant in 1990 and the
impacts of the Shoemaker-Levy 9 comet fragments in 1994 on Jupiter are often interpreted as the twin “wake-up
calls” at the policy level of the American government that impacts were a real possibility.
But how large is the actual threat? In 1989, 90 “Earth crossing asteroids,” as they are sometimes called, were
known to exist, out of many thousands of asteroids in the solar system. Assessing the likelihood of impacts by these
objects—and the many more expected to exist but had not yet been detected--was a matter of extrapolation from a
very small base of evidence. Two decades later, automated sky surveys had identified many thousands of Near-Earth
asteroids, enabling far better population statistics. In this presentation, I will review the use of population models
and statistics in the context of evolving US policy towards asteroid hazards.
The Citizen Science Movement According to Feyerabend: Taking Advice from a Madman, SARAH M. ROE
(Department of Philosophy, Southern Connecticut State University, 501 Crescent Street New Haven CT 06515;
[email protected]).
The slogan ‘anything goes’ first appears in Paul Feyerabend’s book Against Method. Many have speculated on
what exactly was meant by the slogan and even more philosophers and scientists have quickly discarded
Feyerabend’s antidote as the obvious ramblings of a madman. Within this paper, I utilize Feyerabend’s work to
better understand the new citizen scientist movement, namely the utilization of nonscientists for certain scientific
tasks. I argue that Feyerabend would champion a more radicalized citizen science, one that allows for the possibility
of integrating citizens into every level of the scientific process.
Feyerabend teaches us that while the current citizen science movement is primarily focused on what the citizen
can do for science and what the citizen can learn from science, the movement should also focus on what science can
do for the citizen and what science can learn from the citizen. Feyerabend may offer us a better understanding of
how citizen science can best promote scientific education, offer broader knowledge to participants, increase citizen
interest in conservation and policy, increase both citizen local and national engagement, and promote a rewarding
experience for both the expert and citizen. As such, I argue that Feyerabend would have championed citizen science
on a more nuanced and multileveled continuum, where the benefits of citizens could be properly amplified within
the sciences.