Community Identity: Peer Prestige & Academic

Hiring in the iSchools

Community Identity: Peer Prestige & Academic

Hiring in the iSchools

Andrea Wiggins, Mick McQuaid, & Lada Adamic

iConference 20082/28/2008

Problem StatementProblem Statement

• iSchools are defining an intellectual community identity as a new breed of

• Members of the community must align individual identities with the iSchool community identity.

• interdisciplinary researchers.

Practical Problems of 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?What is an iSchool?

• Interdisciplinary focus on information, technology and people, with diverse institutional characteristics

• Common roots in computer science, library science,

• 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.

• information studies, and more

Survival & EmergenceSurvival & 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

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

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 QuestionResearch Question

• What is the relationship between peer prestige ratings and hiring network measures in iSchools and in Computer Science (CS) departments?

Network DataNetwork 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 ConstructionNetwork 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 & iSchoolsComparing CS & iSchoolsNetwork 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

Average Distance 2.2 2.3

Diameter 5 (random = 7) 4 (random = 11)

Clustering Coefficient 0.23 (random = 0.05) 0.15 (random = 0.08)

Visual ComparisonVisual Comparison

Prestige & CS HiringPrestige & 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 HiringPrestige & 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-HiringSelf-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-HiringDiscussion 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 StudyFaculty Areas of Study

Disciplinary DiversityDisciplinary 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

ConclusionsConclusions

• 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!Thank you!

• Questions?

ReferencesReferences• 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 TableCS Regression Table

B SE B t

cs-weighted pagerank

11.223359 4.294460 2.613 *

cs-betweenness

0. 006258 0.000670 9.340 ***

cs-indegree

-0.068210 0.011898 -5.733 ***

* p < .05, *** p < .001R2 = .8121, Adj. R2 = .7865, F(3,22) = 31.7 ***

iSchool Regression TableiSchool Regression Table

B SE B t

lis-betweenness

-0.004923 0.001131 0.00481 **

lis-weighted pagerank

12.604780 2.966607 0.00539 **

lis-output 0.053361 0.010957 0.00279 **

lis-hiring entropy

0.574079 0.247805 0.05972 .

. p < .1, ** p < .01R2 = .8605, Adj. R2 = .7675, F(4,6) = 9.251 ***