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State power and elite autonomy in a networked civil society: The board interlocking of Chinese non-profits

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Abstract and Figures

In response to failures of central planning, the Chinese government has experimented not only with free-market trade zones, but with allowing non-profit foundations to operate in a decentralized fashion. A network study shows how these foundations have connected together by sharing board members, in a structural parallel to what is seen in corporations in the United States and Europe. This board interlocking leads to the emergence of an elite group with privileged network positions. While the presence of government officials on non-profit boards is widespread, government officials are much less common in a subgroup of foundations that control just over half of all revenue in the network. This subgroup, associated with business elites, not only enjoys higher levels of within-elite links, but even preferentially excludes government officials from the NGOs with higher degree. The emergence of this structurally autonomous sphere is associated with major political and social events in the state–society relationship. Cluster analysis reveals multiple internal components within this sphere that share similar levels of network influence. Rather than a core-periphery structure centered around government officials, the Chinese non-profit world appears to be a multipolar one of distinct elite groups, many of which achieve high levels of independence from direct government control.
Content may be subject to copyright.
Social
Networks
54
(2018)
291–302
Contents
lists
available
at
ScienceDirect
Social
Networks
jo
ur
nal
homepage:
www.elsevier.com/locate/socnet
State
power
and
elite
autonomy
in
a
networked
civil
society:
The
board
interlocking
of
Chinese
non-profits
Ji
Maa,b,
Simon
DeDeoc,d,
aIndiana
University
Lilly
Family
School
of
Philanthropy,
301
N.
University
Boulevard,
Indianapolis,
IN
46202,
USA
bIntetix
Institute,
Beijing
100875,
PR
China
cDepartment
of
Social
and
Decision
Sciences,
Carnegie
Mellon
University,
5000
Forbes
Avenue,
Pittsburgh,
PA
15213,
USA
dSanta
Fe
Institute,
1399
Hyde
Park
Road,
Santa
Fe,
NM
87501,
USA
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Available
online
31
October
2017
Keywords:
Board
interlock
NGO
Civil
society
Elites
State
corporatism
State
power
State–society
relationship
Social
network
People’s
Republic
of
China
Non-profit
foundations
Common
knowledge
a
b
s
t
r
a
c
t
In
response
to
failures
of
central
planning,
the
Chinese
government
has
experimented
not
only
with
free-market
trade
zones,
but
with
allowing
non-profit
foundations
to
operate
in
a
decentralized
fashion.
A
network
study
shows
how
these
foundations
have
connected
together
by
sharing
board
members,
in
a
structural
parallel
to
what
is
seen
in
corporations
in
the
United
States
and
Europe.
This
board
inter-
locking
leads
to
the
emergence
of
an
elite
group
with
privileged
network
positions.
While
the
presence
of
government
officials
on
non-profit
boards
is
widespread,
government
officials
are
much
less
common
in
a
subgroup
of
foundations
that
control
just
over
half
of
all
revenue
in
the
network.
This
subgroup,
associated
with
business
elites,
not
only
enjoys
higher
levels
of
within-elite
links,
but
even
preferentially
excludes
government
officials
from
the
NGOs
with
higher
degree.
The
emergence
of
this
structurally
autonomous
sphere
is
associated
with
major
political
and
social
events
in
the
state–society
relation-
ship.
Cluster
analysis
reveals
multiple
internal
components
within
this
sphere
that
share
similar
levels
of
network
influence.
Rather
than
a
core-periphery
structure
centered
around
government
officials,
the
Chinese
non-profit
world
appears
to
be
a
multipolar
one
of
distinct
elite
groups,
many
of
which
achieve
high
levels
of
independence
from
direct
government
control.
©
2017
The
Authors.
Published
by
Elsevier
B.V.
This
is
an
open
access
article
under
the
CC
BY
license
(http://creativecommons.org/licenses/by/4.0/).
1.
Introduction
1.1.
Board
interlock
and
state
power
When
the
boards
of
different
organizations
have
members
in
common—when
their
boards
interlock—they
can
synchronize
both
their
values
and
behaviors
in
the
absence
of
explicit
central
control
(Fennema
and
Schijf,
1978;
Mintz
and
Schwartz,
1981;
Mizruchi,
1996;
Davis
and
Greve,
1997;
Michael
Dreiling,
2011).
Organiza-
tions
that
share
key
members
in
this
fashion
can
reap
the
benefits
of
network
connections
and
solve
coordination
problems
(Pombo
and
Gutié,
2011;
Faulk
et
al.,
2015).
Board
interlock
is
widespread
in
free-market
societies,
where
it
emerges
in
the
business
sector
as
means
for
coordinating
decisions
and
building
social
influence
(Davis,
1996).
In
many
countries,
it
Corresponding
author
at:
Department
of
Social
and
Decision
Sciences,
Carnegie
Mellon
University,
5000
Forbes
Avenue,
Pittsburgh,
PA
15213,
USA.
E-mail
addresses:
ma47@indiana.edu
(J.
Ma),
sdedeo@andrew.cmu.edu
(S.
DeDeo).
spans
multiple
sectors,
and
links
together
the
nonprofit,
commer-
cial,
and
political
worlds
(Moore
et
al.,
2002;
Barnes,
2017).
In
the
donation-based
charity
sector,
board
interlock
helps
coordinate
of
efforts
and
share
of
information
(Galaskiewicz
et
al.,
2006),
and
enhances
both
a
nonprofit’s
perceived
legitimacy
and
its
capac-
ity
to
acquire
resources
(Esparza
and
Jeon,
2013).
Among
ethnic
associations,
the
“broker
function”
of
board
interlock
generates
and
spreads
political
trust,
helping
to
build
stronger
civic
communities
and
strengthening
trust
towards
government
(Fennema
and
Tillie,
2001).
Much
less
is
known
about
the
political
implications
of
board
interlock
under
authoritarian
governments.
For
a
government
con-
cerned
with
the
dangers
of
independent
agents,
interlock
may
be
a
benefit,
because
the
resulting
coordination
reduce
the
indepen-
dence
between
organizations
and
make
non-government
agents
easier
to
control.
However,
these
benefits
exist
only
if
the
govern-
ment
maintains
control
of
the
most
central
organizations
in
the
resulting
network.
If
it
does
not,
board
interlock
may
shift
from
an
opportunity
to
a
threat:
organizations
may
not
only
reap
the
benefits
of
coordination,
but
now
do
so
by
coordinating
around
an
independent
agent.
https://doi.org/10.1016/j.socnet.2017.10.001
0378-8733/©
2017
The
Authors.
Published
by
Elsevier
B.V.
This
is
an
open
access
article
under
the
CC
BY
license
(http://creativecommons.org/licenses/by/4.0/).
292
J.
Ma,
S.
DeDeo
/
Social
Networks
54
(2018)
291–302
Board
interlock
is
crucial
to
understanding
“infrastructural”
forms
of
state
power
(Mann,
1984).
Infrastructural
power
refers
to
the
capacity
of
the
state
to
act
through
civil
society,
by
pen-
etrating,
and
thereby
influencing,
its
institutions.
Infrastructural
power
is
often
contrasted
with
despotic
power:
the
ability
of
state
elites
to
act
without
formal
negotiations
with
civil
society,
through
top-down,
unilateral
action.
The
coordination
enabled
by
board
interlock
provides
an
important
means
by
which
a
state
might
amplify
infrastructural
power—or,
conversely,
a
means
by
which
non-governmental
actors
may
reduce
it.
The
world
of
non-profit
foundations
in
the
People’s
Republic
of
China
provides
a
key
test
case
for
how
a
central
authority
confronts
the
challenges
of
an
emergent
network
of
non-governmental
orga-
nizations.
In
short:
how
does
an
authoritarian
regime
deal
with
the
counter-power
that
may
develop
when
agents
of
a
putative
civil
society
connect
together?
1.2.
How
much
autonomy?
A
brief
introduction
to
civil
society
and
the
Chinese
nonprofit
sector
While
charities
and
“social
organizations”
appear
early
in
China’s
history,
the
majority
were
closed
down
during
the
Cultural
Revolution
in
the
1960s
and
1970s
(Ye,
2003).
The
nonprofit
sec-
tor
only
re-emerged
during
the
reform
era
of
the
1980s,
as
part
of
the
government’s
push
to
decentralize
and
devolve
power
away
from
direct
state
control
(Ma,
2002;
Teets,
2013).
In
the
following
decades,
the
sector
has
expanded
so
rapidly
that
scholars
today
ask
whether
or
not
it
represents
the
rise
of
a
Chinese
civil
society:
a
dense
network
of
groups
that
bring
together
citizens
to
accomplish
activities
outside
of
government
control.
That
concept,
civil
society,
has
its
origin
in
the
19th
Century,
when
Alexis
de
Tocqueville
connected
the
early
stages
of
Ameri-
can
democracy
to
the
growth
of
voluntary
associations
of
ordinary
citizens
for
everything
from
the
promotion
of
temperance
to
the
founding
of
schools
(de
Tocqueville,
2000).
Ever
since,
political
theorists
and
sociologists
have
tried
to
understand
the
role
that
these
associations
might
play
in
the
liberalization
of
authoritarian
regimes
and
the
early
stages
of
democratic
rule
(Walzer,
1992).
The
concept
of
civil
society
has
continued
to
evolve;
in
a
recent
study
of
the
“illegal”
NGO
sector
within
China,
Spires
(2011)
p.
4
quotes
Foley
and
Edwards
(1996)
p.
46
to
describe
a
neo-Tocquevillian
concept
of
civil
society
as
“an
autonomous
sphere
of
social
power
within
which
citizens
can
pressure
authoritarians
for
change,
pro-
tect
themselves
from
tyranny,
and
democratize
from
below”.
For
these
reasons,
hard-line
members
of
the
Chinese
government
are
liable
to
view
the
very
concept
of
civil
society
as
a
“trap”
(Keith
Zhai,
2017).
A
central
theme
of
research
on
the
Chinese
nonprofit
world
is
thus
how
autonomous
organizations
can
be
in
presence
of
state
control
(Ma,
2002;
Hsu,
2010).
Yet
the
existence
of
non-governmental
associations
does
not
necessarily
imply
a
civil
society
in
the
Tocquevillian
mode
or
even
a
threat
to
authoritarian
rule.
While
countries
in
the
West
have
accepted
nonprofits
that
operate
independent
of
government
con-
trol,
foundations
in
China
must
contend
with
a
one-party
system
potentially
intolerant
of
organizations
that
might
hold
it
account-
able
or
draw
attention
to
its
deficiencies,
and
that
therefore
strives
to
control
and
monitor
it.
Concerns
about
the
lack
of
autonomy
in
the
nonprofit
sector
have
led
many
observers
to
talk
in
terms
of
state-corporatism
(Whiting,
1991;
Ma,
2002),
where
the
non-
profit
sector
is
an
auxiliary
and
dependent
system
of
the
state.
In
the
classic
definition
of
Schmitter
(1974)
pp.
99–100,
the
relevant
organizations
in
state-corporatism
parallel
those
of
government
agencies,
being
“singular,
noncompetitive,
hierarchically
ordered,
sectorally
compartmentalized,
interest
associations
exercising
rep-
resentational
monopolies”.
In
general,
civil
society
can
be
understood
through
a
paradigm
focused
either
on
conflict,
or
on
contingent
cooperation.
Theories
that
focus
on
conflict
assume
that
the
state
and
non-state
organi-
zations
have
goals
that
are
in
fundamental
tension.
These
theories
leave
little
room
for
extensive
cooperation
between
the
two
sec-
tors.
The
neo-Tocquevillian
conception
of
civil
society
is
the
most
explicit
form
of
this
conception,
while,
in
the
particular
case
of
Chi-
nese
non-profits,
the
idea
of
civil
society
as
a
challenge
to
state
power
can
be
found
in
Kang
and
Han
(2008)
which
describes
a
“sys-
tem
of
graduated
control”
where
the
state
exerts
different
control
strategies
over
different
types
of
nonprofits,
depending
on
the
level
of
threat
these
extra-government
organizations
are
seen
to
pose.
By
contrast,
the
contingent
cooperation
paradigm
sees
non-
profits
as
potential
service
arms
of
the
state,
at
times
able
to
implement
the
state’s
goals
in
a
more
efficient
and
effective
fash-
ion.
Spires’
2011
paper
(Spires,
2011)
popularized
an
account
of
this
form,
based
around
the
idea
of
a
“contingent
symbiosis”
between
government
and
civil
society,
in
which
illegal
NGOs
are
allowed
to
operate
as
long
as
they
relieve
the
state’s
responsibilities
for
social
welfare.
Another
example
is
provided
by
Teets
(2013)
p.
36,
which
describes
a
“consultative
authoritarianism”
that
promotes
at
one
and
the
same
time
an
“operationally
autonomous
civil
society”
and
a
“sophisticated
authoritarianism
that
uses
more
indirect
tools
of
social
control”.
1.3.
Networked
civil
society
Because
of
the
power
of
the
Chinese
state,
research
into
its
nonprofit
world
tends
to
focus
on
how
much
autonomy
can
exist
in
the
presence
of
state
control
(Ma,
2002;
Kang
and
Han,
2008;
Hsu,
2010;
Hsu
et
al.,
2017).
Previous
studies
have
documented
the
strategies
and
tactics
of
individual
nonprofits,
either
through
case
studies
or
the
identification
of
qualitative
patterns
of
behavior
across
multiple
cases
(Estes
R.J.,
2017;
Saich,
2000;
Lu
2007;
Teets,
2013).
Civil
society,
however,
is
more
than
just
the
existence,
and
even
the
autonomy,
of
non-governmental
organizations.
It
is
how
these
organizations
connect
together,
in
a
horizontal
fashion,
to
form
something
more
than
a
catalog
of
distinct
endeavors
(Salmenkari,
2013):
organized
“multiple
overlapping
and
intersecting
sociospa-
tial
networks
of
power”
(Mann,
1986
p.1).
To
understand
civil
society
in
China,
in
other
words,
we
must
study
not
only
how
the
state
acts
on
individual
foundations,
but
also
how
it
interacts
with
the
networks
through
which
these
foundations
share
personnel,
information,
and
resources.
The
infrastructural
power
the
state
exercises
may
be
both
enhanced,
and
dissipated,
by
the
horizontal
connections
between
the
orga-
nizations
it
penetrates.
Board
interlock
is
one
of
the
primary
mechanisms
for
this
self-organization
to
take
place,
and
yet
we
know
next
to
nothing
about
how
this
process
has
unfolded,
and
the
implications
of
this
evolution
for
civil
society
in
twenty-first
century
China.
We
will
study
the
Chinese
state–society
relationship
by
looking
at
the
evolution
of
the
non-profit
board
interlock
network.
To
do
this,
we
draw
on
a
large
dataset
of
officially-registered
nonprofit
foundations.
This
dataset
records
not
only
important
information
about
each
foundation,
but
also
the
list
of
board
members,
enabling
us
to
construct
the
board
interlock
network.
Our
analysis
can
then
operate
at
two
levels
simultaneously:
(1)
at
the
level
of
the
indi-
vidual
foundation,
and
(2)
at
the
level
of
the
network,
where
edges
between
foundations
are
defined
by
the
sharing
of
board
members.
At
the
level
of
individual
foundations,
our
data
show
the
high
level
of
presence
of
government
officials
on
foundation
boards.
Examination
of
how
the
number
of
government
officials
varies
by
working
areas
and
foundation
type
shows
how
the
presence
of
gov-
J.
Ma,
S.
DeDeo
/
Social
Networks
54
(2018)
291–302
293
ernment
officials
correlates
with
activities,
and
legal
status,
that
the
government
is
expected
to
be
most
concerned
to
control.
At
the
network
level,
we
find
that
board
appointments
connect
together
a
significant
fraction
of
legal
Chinese
foundations
into
a
single
network.
Our
results
show
the
existence
of
network
elites,
associated
with
business
entrepreneurs
and
their
foundations,
that
form
preferential
ties
to
each
other.
This
subnetwork
appears
to
preferentially
exclude
government
officials
from
its
most
central
nodes,
providing
evidence
that
the
network
acts
in
part
to
frustrate
the
magnification
of
state
control
that
might
be
expected
to
arise
in
the
presence
of
board
interlock.
The
sharing
of
board
members
not
only
connects
foundations
together,
it
also
appears
to
preferentially
connect
them
into
clus-
ters:
groups
of
nodes
that,
taken
together,
tend
to
preferentially
connect
to
each
other
rather
than
the
other
nodes
in
the
network.
This
phenomenon
has
been
studied
quantitatively
by
Heemskerk
and
Takes
(2016),
for
the
case
of
the
board
interlock
network
among
large
corporations.
In
that
study,
the
authors
were
particularly
interested
to
determine
whether
the
interlock
network
showed
either
a
classical
“core-periphery”
structure
based
around
a
sin-
gle
hegemon,
or
evidence
for
a
the
existence
of
a
more
“multipolar
global
order”.
Such
an
analysis
has
a
natural
analog
to
the
question
of
the
extent
of
civil
society
within
a
nation:
do
foundations
interlock
with
a
government-controlled
core,
or
do
they
associate
into
inde-
pendent
structures
with
central
positions
that
rival
that
of
any
putative
hegemonic
core?
We
find
strong
evidence
for
the
latter,
detecting
distinct
clusters
at
the
very
center
of
the
network.
These
clusters
show
a
strong
bimodaility
in
levels
of
government
control,
either
preferentially
excluding,
or
including,
government
officials.
The
Chinese
non-profit
world
is
a
multipolar
one,
with
different
groups
at
the
center
showing
distinct
relationships
to
government
control.
Taken
together,
our
findings
suggest
the
emergence
of
a
form
of
network
autonomy
that
exists
despite
high
levels
of
individual-
level
government
appointments
to
nonprofit
boards.
At
the
same
time,
the
association
of
this
network
autonomy
with
the
business
elite—rather
than
“ordinary”
citizens—means
that
this
autonomy
may
not
lead
to
the
kind
of
pluralism
associated
with
a
Tocquevil-
lian
civil
society.
2.
Methods
2.1.
Dataset
and
network
construction
Our
primary
dataset
is
the
Research
Infrastructure
of
Chinese
Foundations
(RICF;
data
available
at
Ma
et
al.,
2017,
and
additional,
processed
files
including
the
networks
derived
for
this
analysis
are
available
at
DeDeo
and
Ma,
2017).
The
RICF
database
contains
the
records
of
the
3344
legally-registered
foundations
within
mainland
China
between
1981
and
2013.
Information
about
each
foundation
is
drawn
from
six
different
sources,
including
both
official
gov-
ernment
reports
and
information
submitted
to
the
government,
or
reported
on
websites,
by
the
foundations
themselves.
Comparing
RICF’s
counts
to
other
reference
sources,
the
RICF’s
data
appears
to
be
at
least
90%
complete.
The
data
is
restricted
to
foundations
allowed
to
conduct
fundraising;
while
these
foundations
are
out-
numbered
by
the
much
larger
number
of
less
formal
“associations”,
they
are
the
most
developed
form
of
non-profit
institution,
and
control
just
over
76%
of
all
non-profit
funding
in
the
nation.1
1The
3344
foundations
in
the
RICF
database
control
approximately
35.3
billion
RMB
(B¥);
this
amounts
to
a
large
fraction
of
the
45.9
B¥
of
non-profit
funding,
tracked
by
the
Ministry
of
Civil
Affairs
of
China
in
2013,
for
all
“associations”
and
related
classifications
(Ministry
of
Civil
Affairs
of
China,
2016).
RICF
strives
to
be
as
comprehensive
as
possible;
it
includes
foun-
dations
that
may,
for
example,
may
be
essentially
defunct.
Within
RICF
data
is
a
subset
of
foundations
that
have
undergone
an
eval-
uation
process,
which
rates
the
foundations
according
to
a
set
of
criteria
including
governance
structure,
financial
transparency,
and
program
effectiveness.
Foundations
which
receive
a
“3A”
or
above
(3A+)
are
considered
to
have
passed
this
evaluation.
Because
the
3A+
evaluation
includes
checks
on
transparency
and
reporting,
we
expect
the
data
associated
with
3A+
foundations
to
be
more
reliable;
because
it
also
includes
checks
on
effectiveness
and
gov-
ernance,
we
expect
these
foundations
to
be
more
active.
Comparing
our
analyses
with
the
3A+
set
allows
us
to
test
for
unexpected
sen-
sitivities
to
both
data
quality,
and
foundation
activity
levels,
in
the
database
as
a
whole.
For
each
foundation,
RICF
logs
the
names,
gender,
and
date
of
birth
of
the
board
members.
This
allows
us
to
resolve
name
collision
and
therefore
construct
the
board
interlock
network:
two
founda-
tions
are
connected
when
they
share
one
(or
more)
board
members.
For
simplicity
in
this
analysis,
our
network
is
unweighted:
we
con-
sider
only
the
presence
or
absence
of
at
least
one
shared
member,
and
do
not
distinguish
whether
links
are
created
by
sharing
presi-
dents,
secretaries,
or
ordinary
members.
Extensions
to
the
study
of
weighted
ties
are
certainly
possible:
one
could,
for
example,
con-
sider
weighting
the
edge
by
the
number
of
board
members
shared.
Such
a
weighting
would
add
additional
methodological
complex-
ities,
however,
since
foundations
with
larger
boards
will
have
the
ability
to
form
stronger
ties
with
each
other.
This
may
or
may
not
correctly
represent
the
underlying
social
dynamics:
if
two
founda-
tions
with
very
large
boards
share
two
members,
it
may
not
make
sense
to
represent
them
has
having
stronger
ties
to
each
other
com-
pared
to
two
foundations
with
very
small
boards
and
only
a
single
member
in
common.
One
could
attempt
to
normalize
the
weights
by
board
size;
in
the
case,
however,
that
the
two
foundations
so
con-
nected
have
different
sizes,
we
now
have
asymmetric
edge
weights.
More
sophisticated
models
yet
could
be
constructed,
on
the
basis
of
a
probabilistic
model
for
connection
formation:
for
example,
one
could
consider
edge
weight
relative
to
a
null
model
where
ties
are
formed
at
random.
In
this
analysis,
for
both
simplicity
and
to
allow
direct
comparison
to
prior
literature
in
other
areas
of
the
world,
we
follow
the
standard
choice
of
unweighted
edges.
The
RICF
data
also
contains
the
date
of
incorporation
for
each
foundation,
allowing
us
to
study
how
the
final
network
assembled
over
time.
Inconsistencies
in
historical
reporting
rates
and
avail-
ability
of
data
make
it
difficult,
if
not
impossible,
to
produce
an
exact
history
of
entrances
and
departures
over
time.
We
can,
how-
ever,
approximate
this
process
by
seeing
how
the
network
would
have
assembled
if
the
foundation’s
board
had
remained
unchanged
to
the
present.
This
is
only
an
imperfect
tracer
of
the
more
detailed
question
that
includes
both
the
formation
of
a
foundation,
and
the
ways
in
which
the
network
might
be
altered
by
the
addition
or
removal
of
board
members.
However,
prior
work
suggests
that
this
approxi-
mation
may
not
be
that
bad.
A
study
of
non-profits
in
Spain
found
that
initial
boards
were
usually
assembled
by
the
founders,
and
that
while
nonprofits
needed
a
period
of
development
to
attract
out-
siders
as
potential
board
members
(de
André
et
al.,
2009),
this
early
growth
appeared
to
stop
when
the
non-profit
reached
maturity.
A
study
in
the
United
Kingdom
found
that
the
majority
of
nonprofit
boards
remained
unchanged
on
timescales
of
three
years,
and
that
it
was
difficult
for
to
recruit
new
board
members
(Cornforth
and
Simpson,
2002).
Little
is
known
about
the
Chinese
case,
however;
where
relevant,
we
draw
attention
to
cases
where
“the
structure
at
time
t,
given
board
compositions
in
2015”
is
only
an
approxima-
tion,
at
best,
to
“the
structure
at
time
t,
given
board
compositions
at
time
t”.
In
general,
our
dynamical
analysis
is
limited
to
asking
294
J.
Ma,
S.
DeDeo
/
Social
Networks
54
(2018)
291–302
Fig.
1.
The
giant
component
of
the
board
interlock
network,
containing
1022
nodes
and
1626
edges;
75%
of
the
nodes
with
non-zero
degree,
and
30%
of
the
full
database.
A
simple
spring
loaded
network
layout
algorithm
allows
us
to
visualize
which
nodes
are
tightly
coupled
to
many
others
(end
up
at
the
center),
and
which
are
connected
to
the
main
network
by
only
a
small
number
of
links
to
peripheral
nodes.
At
the
center
are
a
small
number
of
interlinking
elite
super-connectors
with
high
degree
(Figs.
2
and
3).
Node
size
is
scaled
by
PageRank;
node
colors
label
the
top
ten
largest
clusters
found
using
the
Louvain
algorithm
(see
Table
7).
questions
of
the
form
“when
did
organizations
responsible
for
the
current
trend
join
the
system?”.
2.2.
Variables
Four
critical
variables
help
us
characterize
foundations
at
the
individual
level.
Public
Fundraising
vs.
Non-Public
Fundraising.
The
main
legal
distinctions
in
the
Chinese
nonprofit
sector
governs
the
scope
of
fundraising.
“Public
fundraising”
foundations
are
allowed
to
raise
money
from
the
general
public—for
example,
through
fund
drives
and
advertising—while
“non-public
fundraising”
foundations
may
not
(as
shorthand,
we
refer
to
these
as
“public”
and
“non-public”
hereafter).
Moreover,
public
foundations
are
further
constrained
by
geography;
“central-level”
foundations
may
raise
funds
at
the
national
scale,
while
province-level
and
city-level
foundations
are
restricted
geographically.
The
Chinese
Charity
Law,
effective
from
1
September
2016,
will
nullify
the
distinction
between
public
and
non-public
fundraising;
however,
the
ability
of
organizations
to
raise
funds
from
general
public
will
still
be
controlled
by
license
issued
from
the
state.2
2Xinhua
News
Agency:
NPC
hopes
charity
law
can
help
poverty
fight,
available
at
http://news.xinhuanet.com/english/2016-03/09/c
135172544.htm
(accessed
14.06.16.
Politically
Sensitive
vs.
Politically
Non-Sensitive.
We
supplement
the
RICF
by
hand-coding
the
foundations’
mission
statements
by
whether
or
not
they
are
involved
in
a
potentially
controversial
or
politically
sensitive
area
(“sensitive”
vs.
“non-sensitive”).
Tracking
this
variable
allows
us
to
look
for
systematic
attempts
to
selectively
control
certain
topics.
If
a
foundation
has
one
or
more
of
the
follow-
ing
characteristics
it
is
coded
as
“sensitive,”
otherwise
it
is
coded
as
“non-sensitive”
(Spires,
2011;
Kang
and
Han,
2008;
Dai,
2008;
Jiao,
2001):
1.
Involving
advocacy,
e.g.,
human
rights,
labor
issues,
and
environ-
mental
policy.
2.
Involving
international
affairs,
e.g.,
programs
promoting
inter-
national
cultural
exchanges.
3.
Involving
religious
or
ethnic
issues,
e.g.,
Christian
activities
and
Tibet
issues.
4.
Involving
the
police
or
the
legal
system,
or
related
“social
stabil-
ity”
(weiwen)
issues.
In
order
to
control
the
researchers’
bias
toward
coding,
two
assistants,
who
were
unaware
of
the
research
purpose,
were
asked
to
independently
classify
foundations,
solely
according
to
the
information
provided
in
their
mission
statements.
Discrepancies
between
the
two
assistants
were
finalized
by
a
third
person
who
is
a
doctoral
candidate
in
China
studies.
J.
Ma,
S.
DeDeo
/
Social
Networks
54
(2018)
291–302
295
Table
1
Foundation
status,
activity,
and
yearly
budgets
(in
billions
of
yuan;
1
B
¥
150
M$
in
2016)
for
the
3344
foundations
in
our
database.
The
majority
of
the
foundations
are
concerned
with
neutral
(non-sensitive)
activities,
and
the
majority
are
restricted
to
private
fundraising.
Despite
the
fact
that
non-public
foundations
cannot
raise
money
from
the
general
public,
they
actually
control
the
majority
of
nonprofit
revenue
in
the
network.
Total
numbers
Yearly
income
Non-sensitive
Sensitive
Non-sensitive
Sensitive
Public
954
(28%)
356
(11%)
Public
13.9
B¥
3.2
B¥
Non-public
1913
(57%)
121
(3%)
Non-public
17.5
B¥
0.7
B¥
State
Power.
Our
main
tracker
of
state
penetration
into
the
non-profit
sector
is
the
number
of
government
officials
in
senior
management
positions.
The
presence
of
government
officials
on
a
foundation
board
is
a
clear
mechanism
by
which
the
state
can
exercise
control;
at
the
same
time
the
state,
at
least
explicitly,
for-
bids
government
officials
from
serving
on
these
boards.
Official
law
(Article
23)
is
that
“principals”
(the
board
chair
(president),
deputy
chair,
or
secretary
general)
should
not
be
currently
employed
by
the
state.3
Law
against
direct
government
involvement
are
commonly
vio-
lated.
The
standard
annual
reporting
forms
even
asks
foundations
to
report
the
number
of
principals
who
are
government
staff;
a
non-negligible
fraction
(18%)
report
non-zero
numbers
of
current
government
officials.
As
a
different
measure
of
state
influence,
we
hand-coded
the
3A+
foundations,
noting
whether
or
not
the
board
president
is
a
current
or
retired
government
official.
Hand-coding
is
a
difficult
and
laborious
task;
because
it
can
be
difficult
to
ascertain
the
current
status
of
individual,
our
3A
hand-coding
includes
both
retired
and
currently-serving
government
officials,
and
is
thus
not
directly
comparable
to
the
self-reporting
set.
We
thus
count
the
number
of
government
officials
in
three
dif-
ferent
ways.
The
RICF
counts
the
number
of
current
government
officials
who
serve
as
principals;
it
also
counts
the
number
of
simultaneously
retired
and
senior
government
officials
who
serve
as
principals;
and
(for
a
hand-coded
subset)
it
counts
the
number
of
either
current
or
retired
government
officials
who
serve
as
the
board
president.
Note
that
the
Article
23
law
does
not
forbid
retired
government
officials
from
serving
as
board
principals,
and
these
people
may
well
still
represent
government
influence
(Li,
1998).
Registration
Level.
Depending
on
their
scope
of
operation,
foun-
dations
may
be
registered
at
the
city
level,
the
province
level,
or
the
central
level.
Central-level
registrations
enable
the
foundation
to
operate
on
a
national
scale.
Registration
level
gives
us
informa-
tion
on
both
the
scope
of
foundation
operation,
and
also
allow
us
to
look
for
preferential
interlocking
as
a
function
of
both
scope
(e.g.,
do
central-level
foundations
preferentially
connect
to
each
other)
3“Regulations
on
the
Management
of
Foundations”
(4
February
2004),
Article
23;
original
text
available
at
http://www.mca.gov.cn/article/yw/shjzgl/fgwj/201507/
20150700850200.shtml,
see
English
translation
at
http://www.cecc.gov/resources/
legal-provisions/regulations-on-the-management-of-foundations-chinese-text
(18.04.16).
Table
3
The
fraction
of
nodes
of
each
type
that
share
board
members
with
other
founda-
tions.
The
board
interlock
network
extends
to
a
significant
fraction
of
all
Chinese
non-profits.
Both
public
and
non-public
fundraising
foundations
are
highly
inte-
grated
into
the
overall
network,
with
central-level
foundations
able
to
raise
from
the
general
public
the
most
connected
of
all.
Public
Non-public
Central
82%
±
1%
72%
±
1%
Provincial
47%
±
2%
36%
±
2%
City
67%
±
1% 24%
±
1%
geography
(e.g.,
do
same-city
registrations
connect
preferentially
versus
different-city).
3.
Results
3.1.
Individual-level
statistics
and
the
presence
of
state
power
Table
1
shows
the
breakdown
of
the
foundations
in
the
RICF
data.
Collectively,
the
3344
foundations
in
our
data
have
a
com-
bined
income
of
35.3
billion
RMB;
approximately
5.5
billion
USD
at
current
exchange
rates.
Paralleling
Tocqueville’s
accounts
of
the
diverse
initiatives
of
citizens
in
19th
Century
America,
foundations
in
contemporary
China
range
in
activity
in
everything
from
the
promotion
of
the
board
game
wéiqí
(Go)
to
legal
aid
for
the
indi-
gent.
The
majority
are
restricted
to
non-public
fundraising,
and
work
in
non-sensitive
areas.
These
non-public
foundations
control
just
over
half
of
the
total
yearly
nonprofit
revenue
in
the
coun-
try.
Despite
laws
to
the
contrary,
our
results
confirm
persistent
and
high
levels
of
state
involvement
in
the
governance
of
foun-
dations.
Table
2
shows
the
relationship
between
fundraising
scope
and
activity,
relying
on
both
the
hand-coded
3A
subsample
that
tracks
the
affiliations
of
board
presidents,
and
official
self-reports
in
the
full
database.
Because
the
3A
hand-coding
includes
retired
officials,
the
two
methods
track
slightly
different
phenomena.
Both
methods
confirm
that
the
presence
of
government
offi-
cials
is
less
for
non-public
foundations.
The
government
is
most
involved
in
foundations
that
are
able
to
raise
funds
from
the
gen-
eral
public.
(Self-reports,
but
not
our
hand-coding,
show
additional
supervision
when
the
foundation
itself
is
associated
with
sensitive
activities.
Because
this
signal
does
not
appear
in
the
hand-coded
subset,
it
may
be
best-explained
by
differing
incentives:
public
foundations
involved
with
sensitive
activities
may
be
more
will-
ing
to
report
government
officials
on
their
boards,
despite
the
fact
that
this
violates
Article
23.)
3.2.
Board
interlocking:
super-connectors
and
elites
Board
interlock
is
widespread.
A
significant
fraction
of
the
foun-
dations
are
integrated
into
the
network:
of
the
3344
foundations,
1411
(42%)
share
board
members
with
at
least
one
other
founda-
tion,
for
a
total
of
1863
links.
As
shown
in
Table
3,
foundations
at
the
central
level
are
the
most
likely
to
be
connected.
Both
public
and
private
foundations
show
significant
network
integration.
A
large
Table
2
Government
presence
on
foundation
boards
is
widespread,
but
variable.
Despite
explicit
laws
against
the
practice,
foundations
often
have
government
officials
as
board
principals.
Hand-coding
of
a
subset
of
520
foundation
presidents
(left
panel)
shows
that
the
practice
of
incorporating
current
or
retired
government
officials
is
widespread.
In
both
hand-coded
data,
and
self-reports
in
annual
filings
(right
panel),
foundations
able
to
raise
funds
from
the
general
public,
and
foundations
concerned
with
government
unfavorable
activities,
are
more
likely
to
be
controlled
in
this
fashion.
Official
or
retired-official
president
(hand-coded
subset)
Official
principal
(self-reports)
Non-sensitive
Sensitive
Non-sensitive
Sensitive
Public
74%
±
3%
79%
±
5%
Public
34%
±
1%
54%
±
3%
Non-public
41%
±
3%
29%
±
9%
Non-public
9%
±
2%
19%
±
4%
296
J.
Ma,
S.
DeDeo
/
Social
Networks
54
(2018)
291–302
Fig.
2.
The
degree
distribution
of
the
board
interlock
network.
The
distribution
is
log-normal
(dashed-line
fit),
and
a
small
fraction
of
the
nodes
have
unusually
high
degree.
fraction
of
this
network
is
connects
together,
into
a
single
giant
component
that
contains
1022
foundations
(see
Fig.
1).
While
the
existence
of
board
interlock
parallels
the
dominant
corporate
cases
studied
in
the
West,
there
are
significant
differ-
ences.
Most
notably,
the
network
is
not
small
world:
the
average
path
length
between
nodes
in
the
giant
component
is
7.71,
and
the
network
diameter
is
27;
in
both
cases
much
larger
than
the
corporate
board
interlock
seen
in
the
United
States
(Davis
et
al.,
2003).
The
board
interlock
network
in
Chinese
foundations,
in
other
words,
has
a
tendency
to
isolate
nodes
from
each
other.
Even
if
we
restrict
to
the
77
central-level
foundations
in
the
giant
com-
ponent,
the
diameter
remains
large
(9
steps);
by
comparison,
the
network
of
Fortune
800
firms
in
the
1970s,
nearly
ten
times
larger,
had
a
diameter
of
five
(Levine,
1977).
Chinese
foundations
connect
to
each
other,
but
the
existence
of
these
long
paths
shows
that
board
interlocks
are
fundamentally
limited
in
their
ability
to
coordinate
action
on
the
very
largest
scales.
While
the
network
has
few
shortcuts
and
hubs
that
connect
otherwise
distant
nodes,
it
is
also
the
case
that
a
small
number
of
foundations
have
very
high
degree—they
share
an
unusu-
ally
large
number
of
board
members
with
other
foundations.
We
show
the
network
degree
distribution
in
Fig.
2.
The
exis-
tence
of
these
“super-connectors”
can
be
empirically
confirmed
by
testing
for
heavy-tailed
degree
distributions;
standard
methods
strongly
prefer
a
log-normal
distribution
to
both
an
exponential
(i.e.,
random-graph)
and
power-law
fit
(Clauset
et
al.,
2009;
Alstott
et
al.,
2014).
These
super-connectors
appear
to
preferentially
connect
to
each
other,
suggesting
the
existence
of
highly
connected
elite
groups
(the
“rich-club
phenomenon”,
first
noted
by
Zhou
and
Mondragó
(2004)).
Fig.
3
shows
the
rich-club
coefficient
in
the
full,
the
public,
and
the
non-public
subnetworks.
To
read
this
figure,
first
follow
the
solid
line;
that
this
line
is
rising
as
a
function
of
k
shows
that,
in
the
full
network,
nodes
with
higher
degree
are
more
likely
to
connect
to
each
other
than
in
a
null
model
that
preserves
the
node
degree
distribution
but
otherwise
shuffled
connections.
Now
follow
the
dashed
line,
which
considers
just
the
internal
connec-
tions
of
the
non-public
subnetwork.
This
line
shows
that
this
same
phenomenon,
seen
in
the
full
network,
is
even
stronger
here:
non-
public
elites
are
even
more
likely
to
preferentially
connect
within
this
subnetwork.
Finally,
note
the
(very
short)
dotted
line.
This
shows
at
best
weak
evidence
for
a
rich-club
effect
when
restricting
to
the
public
network.
The
line
is
much
shorter,
because
the
public
network,
considered
in
isolation,
has
few
high-degree
nodes:
if
a
public
foundation
has
high-degree
in
the
full
network,
it
is
usually
because
it
connects
to
non-public
foundations.
If
we
code
nodes
by
the
board
president’s
profession,
we
find
that
the
highest
degree
nodes
include
both
the
government
and
the
Fig.
3.
The
rich-club
coefficient
as
a
function
of
k-core.
High-degree
organizations
(“network
elites”)
preferentially
connect
to
other
network
elites,
particularly
in
the
non-public
network.
This
is
apparent
in
how
the
rich-club
coefficient
grows
as
a
function
of
k-core
level
for
the
full
network
(solid
line),
the
public
network
(dotted
line),
and
the
non-public
network
(dashed
line);
95%
confidence
ranges
are
shown.
Nodes
with
high
degree
are
far
more
likely
to
connect
to
each
other,
compared
to
a
null
model
that
preserves
the
degree
distribution
but
otherwise
breaks
interlock
correlations
(McAuley
et
al.,
2007).
Taken
separately,
the
non-public
network
shows
a
stronger
rich
club
effect
than
the
network
as
a
whole.
Meanwhile,
the
majority
of
high-degree
links
in
the
public
network
are
due
to
cross-links
with
the
non-public
foundations;
the
maximal
degree
for
the
public
network
in
isolation
is
much
smaller.
Table
4
The
number
of
links
found
between
nodes
of
each
type,
compared
to
a
degree-
preserving
null.
Foundations
in
the
same
region,
and
at
the
same
registration
level,
tend
to
cross
link.
Centrally-registered
foundations
are
more
than
twice
as
likely
to
connect
to
each
other
than
in
the
null;
province-level
foundations
connect
to
others
in
the
same
province
at
rates
seven
times
higher
than
the
null,
and
city-level
foundations
are
the
most
cross-linked
of
all,
linking
to
other
city-level
foundations
in
the
same
place
at
rates
14
times
higher
than
expected.
Central
Province
City
Central
×2.1
±
0.1
×0.73
±
0.03
×1.2
±
0.2
Province
(same)
×7.05
±
0.08
×4.7
±
0.5
Province
(different)
×0.42
±
0.01
×0.46
±
0.05
City
(same)
×14.6
±
0.9
City
(different)
0
business
elite.
Of
the
ten
highest-degree
foundations,
six
are
associ-
ated
with
businesses,
four
with
government.
For
example,
the
most
connected
foundation
is
the
YouChange
China
Social
Entrepreneurs
Foundation,
set
up
to
encourage
philanthropic
giving
by
wealthy
entrepreneurs;
the
second
is
the
Forbidden
City
Cultural
Heritage
Conservation
Foundation,
which
manages
the
state-owned
histor-
ical
treasure.
The
top
ten
most
connected
board
members
are
also
a
mixture
of
both
government
and
business
elites;
three
are
busi-
ness
elites,
six
are
current
government
officials,
including
members
of
the
National
People’s
Congress,
the
CPPCC,
and
the
Guangzhou
People’s
Congress;
and
one
is
a
retired
government
official.
Considering
the
public
and
non-public
networks
separately
allows
us
to
see
how
different
groups
dominate.
In
the
public
net-
work,
the
highest-degree
nodes
are
nearly
all
associated
with
the
government:
of
the
top
ten
highest
degree
foundations,
only
two
have
a
president
with
a
non-governmental
background
(a
televi-
sion
celebrity,
and
the
head
of
a
hospital).
By
contrast,
six
of
the
ten
highest
degree
nodes
in
the
non-public
network
are
associ-
ated
with
business
elites.
The
highest
degree
node,
for
example,
the
YouChange
Foundation,
is
run
by
the
businesswoman
Ping
Wang,
whose
background
is
in
international
finance
and
law.
Board
interlock
is
influenced
by
both
geography
and
registra-
tion
level;
see
Table
4,
paralleling
classic
results
for
corporate
networks,
co-located
foundations
are
far
more
likely
to
connect
(Stuart,
1998;
Sorenson
and
Stuart,
2001;
Owen-Smith
and
Powell,
2004).
We
also
find
evidence
for
preferential
connections
between
sensitive
foundations;
there
are
70%
±
10%
more</