Community Identity:
Peer Prestige & Academic Hiring
in the iSchools
Andrea Wiggins, Mick McQuaid, & Lada Adamic
iConference 2008
2/28/2008
Problem Statement
• iSchools are defining an intellectual
community identity as a new breed of
• interdisciplinary researchers.
• Members of the community must align
individual identities with the iSchool
community identity.
Practical Problems of Identity
• From 2005 iConference Survey:
– Academic legitimacy
• Organizational survival
– Student recruitment
– Student placement
– Development of scholarly community
• Publication
• Funding
• Interdisciplinary research
What is an iSchool?
• Interdisciplinary focus on information,
technology and people, with diverse
institutional characteristics
• Common roots in computer science, library
science,
• information studies, and more
• 19 schools form the I-Schools Caucus
– Members are expected to have substantial sponsored
research activity, engagement in the training of future
researchers, and a commitment to progress in the
information field.
Survival & Emergence
• The prevalent survival strategies for LIS
schools in the 1980’s: merger with a larger
partner or expansion into IT-related fields
(Hildreth & Koenig, 2002)
• Over half of the iSchools are represented as
LIS school mergers or realignments
– Merger: Rutgers, UCLA
– Realignment: Syracuse, Pittsburgh, Drexel, Florida
State, Michigan, Washington, Illinois, Indiana
Identity, Legitimacy &
Prestige
• Academic survival strategy to achieve
organizational legitimacy and stability
underlies the way an emergent intellectual
enterprise develops its identity (Small, 1999)
• Academic institutions undergoing strategic
change often use prestige ratings to indirectly
influence identity (Gioia & Thomas, 1996)
Prestige in Academic Hiring
• Departmental prestige is shown to be an
effect of the department’s position in PhD
hiring networks in:
– Management (Bedeian & Feild, 1980)
– Finance (Bair, 2003)
– Sociology, history & political science (Burris,
2004)
– Sociology (Baldi, 2005)
– Political science (Fowler et al, 2007)
Research Question
• What is the relationship between peer
prestige ratings and hiring network measures
in iSchools and in Computer Science (CS)
departments?
Network Data
• Census of 693 identifiable full-time faculty of
iSchools with manual data collection from
Internet resources in January 2007
– 674 PhD degrees with 100% complete data
– Year of degree not available for other terminal
degrees (MLS, JD, MD, etc.)
• Similar data collected by Drago Radev and
associates for top CS departments
• Ranking data from US News & World Report
(2006)
Network Construction
• Combined each iSchool’s individual ego
network into one community ego network
– An ego is an iSchool, for which we gathered data
on faculty degrees; an alter is an institution from
which iSchool faculty were hired
– Indiana’s 2 schools were merged to maintain the
institution as the unit of analysis
• Directed 2-mode network reduced to 1-mode
– Was: School A -> Person -> School B
– Now: School A -> School B, with edge weights
Comparing CS & iSchools
Network
Characteristic
CS Network
iSchools Network
Nodes
123
152
Egos
29
18
Alters
94
134
Edges
572
429
Average Degree
4.7
2.8
Total PhD Degrees
1121
674
Density
0.038
0.019
Betweenness
0.021
0.019
2.2
2.3
5 (random = 7)
4 (random = 11)
0.23 (random = 0.05)
0.15 (random = 0.08)
Average Distance
Diameter
Clustering Coefficient
Visual Comparison
Prestige & CS Hiring
• Regressed USNWR rankings on network
characteristics, both node-based (eg. degree)
and topologically derived (eg. PageRank)
• CS:
– Weighted PageRank, betweenness & indegree
explain 79% of the variance in USNWR ratings
– F = 31.7, p << 0.0001, all 3 variables reach at least
p ≤ 0.01
– Negative coefficient for indegree lowers ratings for
schools with diverse hiring sources
Prestige & iSchool Hiring
• iSchools:
– Smaller subgroup has USNWR LIS ratings, 11 of 18
– Weighted PageRank, betweenness, hiring diversity
(information entropy) & output (number of
graduates in the network) explain 77% of the
variance in USNWR ratings (F = 9.3, p < 0.01)
– Positive coefficient for hiring diversity rewards
schools with faculty from a wider selection of
institutions
Self-Hiring
• 26 of 29 CS egos, and 17 of 18 iSchools, have
hired graduates of their own institution
• On average, 13% of faculty in iSchools are
self-hires; 64% of those (approximately 8%
overall) graduated from the program that now
employs them
• In most cases, self-hires from an iSchool
involved faculty in library science
Discussion of Self-Hiring
• Several reasons for self-hiring in iSchools
– Network structure (PhD -> iSchool) does not
reflect intermediary employment
– Limited availability of PhDs with specific
expertise; data suggest this is more often the case
for LIS faculty
– University as the unit of analysis may hide greater
interdisciplinarity due to hires from other
departments (e.g. PSU)
Faculty Areas of Study
Disciplinary Diversity
• Faculty size matters
– < 25 faculty represent 5 or fewer disciplines
– 25+ faculty represent 8 - 12 disciplines
• Information entropy measure of distribution
of faculty areas of study for each iSchool
– Most diverse: Michigan, Syracuse
– Most focused: Toronto, North Carolina, Georgia
Tech, UC Irvine
– May differentiate hiring strategies that favor
disciplinary diversity versus subject focus
Conclusions
• Hiring network statistics reflect some aspects
of peer prestige captured in USNWR
rankings, more strongly in CS than iSchools
– More data, more established field
• In iSchools, balancing hiring from within the
community and from a diversity of other
sources may improve perceptions of prestige
• Diversity in faculty pedigree may be part of
the iSchools’ “special sauce”
Thank you!
• Questions?
References
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Bair, J. H. (2003). Hiring Practices in Finance Education. Linkages Among Top-Ranked
Graduate Programs. American Journal of Economics and Sociology, 62(2), 429-433.
Baldi, S. (1995). Prestige Determinants of First Academic Job for New Sociology Ph.D.s
1985-1992. The Sociological Quarterly, 36(4), 777-789.
Bedeian, A. G. & Field , H. S. (1980). Academic Stratification in Graduate Management
Programs: Departmental Prestige and Faculty Hiring Patterns. Journal of Management,
6(2), 99-115.
Burris, V. (2004). The Academic Caste System: Prestige Hierarchies in PhD Exchange
Networks. American Sociological Review, 69(2), 239.
Fowler, J. H. et al (2007). Social Networks in Political Science: Hiring and Placement of
Ph.D.s, 1960–2002. PS: Political Science & Politics, 40(4), 729-739.
Gioia, G. A. & Thomas, J. B. (1996). Identity, Image and Issue Interpretation: Sensemaking
During Strategic Change in Academia. Administrative Science Quarterly, 41(3), 370 - 403.
Hildreth, C. R. & Koenig, M. E. D. (2002). Organizational Realignment of LIS Programs:
From independent standalone units to incorporated programs. Journal of Education for
Library and Information Science, 43(2), 126-133.
Small, M. L. (1999). Departmental Conditions and the Emergence of New Disciplines: Two
cases in the legitimation of African-American studies. Theory and Society, 28(5), 559 - 607.
CS Regression Table
B
SE B
t
11.223359
4.294460
2.613 *
0. 006258
csbetweenness
0.000670
9.340 ***
cs-indegree
0.011898
-5.733 ***
cs-weighted
pagerank
-0.068210
* p < .05, *** p < .001
R2 = .8121, Adj. R2 = .7865, F(3,22) = 31.7 ***
iSchool Regression Table
B
-0.004923
SE B
0.001131
t
0.00481 **
lis-weighted 12.604780
pagerank
2.966607
0.00539 **
lis-output
0.010957
0.00279 **
lisbetweenness
0.053361
lis-hiring
0.574079
0.247805
0.05972 .
entropy
. p < .1, ** p < .01
R2 = .8605, Adj. R2 = .7675, F(4,6) = 9.251 ***