KIN, FRIENDS, and COMMUNITY - PowerPoint PPT Presentation

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KIN, FRIENDS, and COMMUNITY

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Title: SOC 8311 Basic Social Statistics Author: David Knoke Department of Sociology Last modified by: Generic Created Date: 8/9/2000 5:14:15 PM Document presentation ... – PowerPoint PPT presentation

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Title: KIN, FRIENDS, and COMMUNITY


1
KIN, FRIENDS, and COMMUNITY
Anthropologists were among the earliest
developers of social network ideas to study
kinship patterns of pre-industrial societies and
small rural communities. Moreno, of course,
invented sociograms to map childrens friendship
patterns. And many sociological network analysts
studied interpersonal ties within large modern
communities. The ethnographic research tradition
remains a robust contributor to social network
analysis today.
Siegfried F. Nadel argued that the role system of
a society forms the matrix of its social
structure We arrive at the structure of a
society through abstracting from the concrete
population and its behaviour the pattern or
network (or system) of relationships obtaining
between actors in their capacity of playing
roles relative to one another. (Nadel 195712)
2
Kinship Networks
Network approaches to kinship examine the
structure of marriage rules and the strategies
for social bonding across generations.
  • Kinship involves complex interlocked role
    relations, prescribing expected rights duties
    of the actors occupying distinct positions
  • Sexual relations reproduction rights
  • Child-rearing obligations
  • Dowries, land property inheritance
  • Cohesion/solidarity collective action

In Anatomy of Kinship (1963) Harrison White used
matrix algebra to simplify complex classificatory
rules regarding marriage and parentage. These
rules generate clans among people in the same
kinship situation. The resulting classificatory
kinship system operates as an abstract group.
White showed how to classify existing clan
systems into a few basic types, revealing a wider
variety of clan systems than anthropologists had
previously hypothesized.
3
Large Kinship Nets
Anthropologist Douglas Whites PGRAPH program
analyzes large kinship networks. Couples and
their uncoupled children are vertices, while
parent-child lines connect nodes within and
between different nuclear families. Pgraph
handles bounded size, subgraphs, cohesion, social
relations, and groups.
White et al. (1999) applied Pajek to represent
Pgraph genealogies Relinking of families
through marriage, for example, can be formally
defined as sets of bounded groups that are the
cohesive cores of kinship networks, with nodes at
various distances from such cores. The structure
of such cores yields an analytic decomposition of
kinship networks and constituent group and role
relationships.
4
Friendship on Frat Row
Theodore Newcomb (1953) started a fraternity at
Bennington College in the 1930s. In return for
free room and board, 17 fratmen filled out weekly
sociometric rankings. These 15 NEWFRAT matrices,
stored in UCINET, are a classic dataset on the
evolution of friendship choices.
The usual story about Newcombs fraternity is
that structural convergence occurred as those
transferring college students met and formed
friendships. That interpretation comes from
network summary measures, or aggregated
blockmodels, indicating that structural change
operates through structurally equivalent actors. 
However, convergence remains a controversial
conclusion, because as much as one-fifth of the
friendship ties changed during in the final
weeks. Moody et al. (2004) use network movies
to argue that the overall structure does not
converge on a single form, and that the process
of change is heterogeneous with some actors
forming stable relations while others dance
between friends throughout the observation
period.
5
An Evolving Network
Two groups follow a simple convergence story --
with their nominations getting progressively more
stable as time passes. The first of these groups
has 7 members, including the cluster at the
right of the movie (1,6,13,8) and presents a
gradual convergence of nomination patterns, while
the second (with 6 members) does not converge on
stable nomination patterns until week 5. Finally,
group 3 (with 4 members, including hanger-on
nodes 10 15) never seems to settle on a
particular nomination pattern, but changes
nominations steadily over the observation period.
6
?? All My Friends Are So Small Town
Community network analysts explore the small
worlds inside huge urban agglomerations that keep
anomie at bay. Two early exemplars were Claude
Fischers study of personal networks in Northern
CA Barry Wellmans project in East York,
Toronto.
Small-town respondents tended to be more
involved with relatives, city respondents with
nonkin. urban residence apparently discouraged
involvement with kin, especially extended kin.
Urbanism seemed to similarly discourage
involvement and encourage selectivity with
neighbors. (Fischer 1982258)
Wellman found half of intimates were relatives,
with kin and nonkin spread over a wide area. Most
ties were to people living in the city, but very
few were based in East York. Communal links
were neither solidaristic nor localized. People
had sparsely knit (low density) networks
lacking in cross-linkages, so support and help in
everyday matters and in emergencies was limited.
East Yorkers can almost always count on help
from at least one of their intimates, but they
cannot count on such help from most of them
(Wellman 19791217).
7
Name Generators
Instruments that measure ego-centric networks in
community or national surveys must use an
open-ended name generator rather than an
enumerated checklist. The 1985, 1987 2004 GSS
quex From time to time, most people discuss
important matters with other people. Looking back
over the last six months, who are the people with
whom you discussed matters important to you. Just
tell me their names or initials.
For each pair of alters Are (Name) and (Name)
total strangers? Especially close? After asking
about every alters gender, race, age,
occupation, etc. Here is a list of some of the
ways in which people are connected to each other.
Some people can be connected to you in more than
one way. For example, a man could be your brother
and he may belong to your church and be your
lawyer. When I read you a name, please tell me
all the ways that person is connected to you.
????
Spouse, parent, sibling, child, other family,
coworker, member of group to which you belong,
neighbor, friend, professional advisor or
consultant, other
8
Just the Facts, Mam
The 1985 GSS module uncovered many factoids about
the social composition of adult Americans
egocentric discussion networks
  • Median size 3 alters 25 have 0-1 alters, 25
    have 5-6
  • Half of alters are egos kin only 20 have no
    kin in their networks
  • Alters know one another mean density 0.61
    only 5 all strangers
  • High race/ethnic homogeneity only 8 have any
    alter diversity
  • Substantial sex diversity 78 have at least one
    alter of opposite sex (most often a spouse,
    sibling, or parent)

The GSS survey network data describe relatively
small, kin-centered, dense, homogeneous social
environments surrounding Americans. To the
extent that success of networking as an
instrumentally oriented pursuit depends on access
to diverse others, those best situated to make
use of it are the young and middle-aged, the
well-educated, and those living in larger places

(Marsden 1987130). The
2004 GSS survey found significantly smaller
ego-nets more isolates.
9
Networking, Chinese Style
Guanxi personal relations or connections.
Ones guanxi network is seen as an appropriate
response to the uncertainties posed by Chinas
cumbersome bureaucracy (Yi Ellis 2000)
Guanxi is based on strong ties of blood relations
social group identities. Outsiders gain entry
only when a mutual friend vouches. Key drivers
saving face and accumulating favors owed
(renqing) a never-in-balance personal ledger
of debits and credits rather than prompt
repayment of outstanding debts.
By relying on unequal personal obligations,
guanxi networks reduce transaction costs,
mistrust, and deceitful opportunism. Thus,
efficient economic exchanges can occur outside
formal organizations and social institutions,
helping China to make its transition to a market
economy. Guanxi benefits business opportunities
information on changes in governmental policies
resources such as land or import licenses. But,
without a strong rule-of-law, corruption remains
a constant threat.
10
Clientalistic Cultures
Clientalistic systems are prevalent in
Mediterranean, Asian, and Latin American cultures
having heavily collectivist conceptions of social
organization, such as Catholic or Confucian
ethics.
Patron-client systems combine strong emotional,
particularistic ties with simultaneous but
unequal exchanges of different types of
resources. Clients exchange personal loyalty,
deference, and awe for the protection,
understanding, and material benefits provided by
their patrons.
(Knoke 1990142).
Most cliques and entourages surrounding a patron
are modeled after patriarchal clans and extended
families. Kinship forms the inner hub, grounded
in familial intimacy and trust. The spokes are
friends and acquaintances who perform brokerage
services, manipulating others resources for
their own profit. The result is a hierarchical
status structure connecting higher and lower
strata.
11
References
Fischer, Claude. 1982. To Dwell Among Friends
Personal Networks in Town and City. Berkeley, CA
University of California Press. Knoke, David.
1990. Political Networks. New York Cambridge
University Press. Marsden, Peter V. 1987. Core
Discussion Networks of Americans. American
Sociological Review 52122-131. Moody, James,
Daniel McFarland, Skye Bender-de Moll. 2004.
Dynamic Network Visualization Methods for
Meaning with Longitudinal Network Movies.
(Downloaded October 2, 2004) ltwww.sociology.ohio-s
tate.edu/jwm/NetMovies/Sub_CD/dynamic_nets_public.
htmlgt Nadel, S. F. 1957. The Theory of Social
Structure. London Cohen West. Wellman, Barry.
1979. The Community Question The Intimate
Networks of East Yorkers. American Journal of
Sociology 841201-1231. White, Douglas R.,
Vladimir Batagelj and Andrej Mrvar 1999.
Anthropology Analyzing Large Kinship and
Marriage Networks with Pgraph and Pajek. Social
Science Computer Review 17(3)245-274. White,
Harrison C. 1963. An Anatomy of Kinship
Mathematical Models for Structures of Cumulated
Roles. Englewood Cliffs, NJ Prentice-Hall. Yi,
Lee Mei and Paul Ellis. 2000. Insider-Outsider
Perspectives of Guanxi. Business Horizons
4325-30.
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