[Seminar] Methods for measuring social and conceptual dimensions of Convergence Science
Friday, July 21, 2023
11:00 am - 12:00 pm
Speaker
Alex
Petersen
University of California - Merced
Host
Prof.
Ioannis
Pavlidis
Location
Online
via
Abstract
Convergence
science
is
an
intrepid
form
of
interdisciplinarity
defined
by
the
US
National
Research
Council
as
鈥渢he
coming
together
of
insights
and
approaches
from
originally
distinct
fields鈥
to
strategically
address
grand
challenges.
This
paradigm
has
been
promoted
extensively
in
the
last
decade,
becoming
a
model
for
designing
flagship
research
programs
that
strategically
address
grand
challenges.
Despite
its
increasing
relevance
to
science
policy
and
institutional
design,
there
is
still
no
practical
framework
for
measuring
convergence.
We
address
this
gap
by
developing
a
measure
of
disciplinary
distance
based
upon
disciplinary
boundaries
delineated
by
hierarchical
ontologies.
We
apply
this
approach
using
two
widely
used
ontologies
鈥
the
Classification
of
Instructional
Programs
(CIP)
and
the
Medical
Subject
Headings
(MeSH)
鈥
each
comprised
of
thousands
of
entities
that
facilitate
classifying
two
distinct
research
dimensions,
respectively.
The
social
dimension
codifies
the
disciplinary
pedigree
of
individual
scholars,
connoting
core
expertise
associated
with
traditional
modes
of
mono-disciplinary
graduate
education.
The
conceptual
dimension
codifies
the
knowledge,
methods,
and
equipment
fundamental
to
a
given
target
problem,
which
together
may
exceed
the
researchers鈥
core
expertise.
Considered
in
tandem,
this
decomposition
facilitates
measuring
social-conceptual
alignment
and
optimizing
team
assembly
around
domain-spanning
problems
鈥
a
key
aspect
that
eludes
other
approaches.
We
demonstrate
the
utility
of
this
framework
in
a
case
study
of
the
human
brain
science
(HBS)
ecosystem,
a
relevant
convergence
nexus
that
highlights
several
practical
considerations
for
designing,
evaluating,
institutionalizing
and
accelerating
convergence.
Econometric
analysis
of
655,386
publications
derived
from
9,121
distinct
HBS
scholars
reveals
a
11.4%
article-level
citation
premium
attributable
to
research
featuring
full
topical
convergence,
and
an
additional
2.7%
citation
premium
if
the
social
(disciplinary)
configuration
of
scholars
is
maximally
aligned
with
the
topical
configuration
of
the
research.
About
the
Speaker
Alex
Petersen
is
Associate
Professor
in
the
Management
of
Complex
Systems
department
and
a
founding
member
of
the
Ernest
and
Julio
Gallo
Management
of
Innovation
Sustainability
and
Technology
(MIST)
program
at
the
University
of
California
鈥
Merced,
where
he
leads
data-oriented
research
focusing
on
the
evolution
of
large
multiscale
socio-economic
systems
by
applying
concepts
and
methods
from
complex
systems,
statistical
physics,
management
and
innovation
science.
Teaming
up
with
collaborators
from
a
variety
of
disciplines,
his
innovation
research
has
been
published
in
various
multi-disciplinary
journals
such
as
Science,
PNAS
and
Research
Policy.
