More than the Sum of Its Parts: Advancing Women at NJIT through Collaborative Research Networks

1. More than the Sum of Its Parts: Advancing Women at NJIT through Collaborative Research Networks The NJIT ADVANCE Project Funded by a grant from The National Science Foundation

2. “To know who we are, we must understand how we are connected.”* PROJECT OVERVIEW

3. The NJIT ADVANCE Project pioneers the use of social network analysis to affect institutional change and ensure the full participation of women in academic science and engineering.

4. NJIT ADVANCE Objectives • enlarge women faculty’s professional networks • improve information flow • stimulate social capital formation • assess the relationship between network structure & career advancement • create new data visualization tools to help faculty manage their networks • transfer sustainable network analysis methods to academic administrators

5. Universities are more than buildings…. and organization charts….

6. …They are WEBS of human interaction and perception whose complex structure is largely invisible to the people embedded in them.

8. We make the invisible visible.

9. "The Old Boys Network used to be a metaphor. Now it is a MAP…. a highway on which we can track the flow of social capital from one human node to another.”

10. Leveraging Social Network Data to Support Faculty Mentoring: Best Practices from NJIT Advance

11. THE GOOD NEWS ABOUT WOMEN IN STEM • “For the most part, men and women faculty in science, engineering, and mathematics have enjoyed comparable opportunities within the university.” –NAS Report, 2010 • "Overall, men and women are retained and promoted at the same rate.“ -Kaminski and Geisler, 2012 • “At NJIT,there are no statistically significant differences between female and male retention. Men and women are promoted in rank at essentially the same rate as well.” • -NJIT ADVANCE 2012

12. THE NOT-SO-GOOD NEWS: The Arrow is Not Moving Toward Parity The gender composition of the academic STEM workforce is still profoundly different from the human population it serves. And likely to remain so.

13. IMPACT OF RETENTION FAILURES National Data Despite slightly improved hiring rates for women (up from 25% to 27%) retention failures for both men and women are so frequent…that "it may take 100 years before women are 50% of the faculty in STEM departments.” -Kaminski and Geisler, 2012

14. NJIT DATA Tenure-Track STEM Faculty 2000: 22 women (9%) By 2010, 9 of those 22 women had left: 41% attrition rate 7 of the 9 (78%) left for reasons other than retirement 2010: 24 women (11%) 10 Year Progress? n= +2

15. WHY IS ACHIEVING PARITY IMPORTANT? • Because trying to solve important problems using only half of the collective human brain is not smart! • A recent NSF-funded study shows that the collective intelligence of a group is positively correlated with the proportion of females in the group. -Wooley, 2010 • That is, the problem-solving ability of a group diminishes as the number of women decreases.

16. RETENTION AND THE BOTTOM LINE Academic hiring is expensive, especially in STEM where start-up packages are large. Failed retention costs money… something that universities have very little of these days.

17. TRACKING STEM FACULTY CAREERS A DECADE OF DATA FROM THE NJIT ADVANCE PROJECT

18. BASIC RESEARCH QUESTIONS Does supporting collaboration support women STEM faculty? What is the relationship among collaboration productivity retention advancement in rank ?

19. ULTIMATE RESEARCH PROJECT GOAL To develop sustainable, scalable methods of collecting & analyzing bibliometric data that can be used to create PREDICTIVE MODELS of faculty career success (and failure)

20. METHODOLOGICAL TACTIC Using COAUTHORSHIP DATA as a proxy for Faculty Research Networks

21. WHY COAUTHORSHIP? Coauthorship data is: • Public • Objective • Can be scraped from the internet or captured from faculty CVs • Coauthorship requires a working relationship, unlike citations or other publication measures • Publications are time-stamped… so we can track the evolution of the faculty network over time.

22. Collecting Coauthorship Data • NJIT ADVANCE researchers text-mined the Scopus digital library to capture STEM faculty data • Built a web crawler to search Scopus • Retrieved 8395 faculty publications produced from 2000-2010—including 3608 coauthored publications • Also captured counts of publications of NJIT faculty with external faculty and grad students • Compiled attributes from HR

23. Significant issues: • NJIT faculty having same name as external faculty/grad students (“Common Name Problem”) • Mislabeling of affiliations • Different databases having slightly different publication titles (e.g. using the word “beta” as opposed to “β”) Collecting Coauthorship Data

24. New Tool to Help Researchers Identify & Resolve Common Name & Duplication Problems http://www.cs.umd.edu/projects/linqs/ddupe/

25. Faculty at NJIT now required to enter yearly publications into Digital Measures software (“Activity Insight”) • Entering this data is tied to merit-based awards for faculty • Tactic: • Use collected data to populate historical publications • Retrieve new publications from Digital Measures Sustainability Collecting Coauthorship Data

26. NJIT ADVANCE Database • 514 tenured/ tenure-track faculty who worked at NJIT from 2000-2010--including a subset of 327 STEM faculty. • Attributes:department • gender NJIT: 77 females, 437 males • NJIT STEM: 38 females, 289 males • rank progression • tenure status • hire date • separation date (if any) • retention status (left/stayed) • years at NJIT • years in the study • total number of publications • total number of coauthored publications • number of publications coauthored with other NJIT faculty • number of publications coauthored with Non-NJIT faculty • number of publications coauthored with NJIT grad students

27. Analytical Tools Used • For standard statistical tests: • SAS • ANOVA • To analyze network structure: • Organizational Risk Analyzer (ORA) software from Carnegie Mellon • UCINET, a social network analysis program distributed by Analytic Technologies

28. Analyzing the Relationship between PRODUCTIVITY and CAREER ADVANCEMENT 2000-2010 “Productivity” defined as number of publications and rate of publication “Career Advancement” defined as retention and promotion in rank.

29. Hypothesis Testing H1. STEM faculty who publish more are more successful in terms of rank increase. POPULATION: All tenured/tenure track STEM faculty (n=327) RESULT: Strongly Supported POPULATION: A cohort of STEM faculty hired as assistant professors from 2000-2003 RESULT: Strongly Supported

30. Hypothesis Testing H1. STEM faculty who publish more are more successful in terms of rank increase. Publication Rate & Advancement POPULATION: A cohort of STEM faculty hired as assistant professors from 2000-2003 RESULT: Strongly Supported Those who did not move up in rank: average (mean) publication rate of 5.73 publications per year (SD=3.36). Those who were promoted from assistant to associate: average (mean) publication rate of 8.67 publications per year (SD=0.91)

31. Hypothesis Testing H1. STEM faculty who publish more are more successful in terms of rank increase. Publication Rate & Retention POPULATION: A cohort of STEM faculty hired as assistant professors from 2000-2003 RESULT: Strongly Supported Those who left: average (mean) publication rate of 3.46 publications per year (SD=2.33). Those who were retained: average (mean) publication rate of 8.78 publications per year (SD=0.94)

32. Analyzing the Relationship among COLLABORATION, PRODUCTIVITY and CAREER ADVANCEMENT 2000-2010 “Collaboration” defined as coauthorship “Productivity” defined as number of publications and rate of publication “Career Advancement” defined as retention and promotion in rank.

33. COLLABORATION, PRODUCTIVITY and CAREER ADVANCEMENT National/ International Data "When publishing productivity is measured by... a scientist's total number of publications, collaboration is a strong predictor of publishing productivity.” - Lee and Bozeman (2005)

34. COLLABORATION & PRODUCTIVITY NJIT ADVANCE Hypothesis Testing H3. STEM faculty who coauthor more will publish more than faculty who coauthor less. POPULATION: All tenured/tenure track STEM faculty (n=327) RESULT: Strongly Supported POPULATION: A cohort of STEM faculty hired as assistant professors from 2000-2003 RESULT: Strongly Supported

35. COLLABORATION & RETENTION/ PROMOTION NJIT ADVANCE Hypothesis Testing H4. STEM Faculty who co-author more are more successful in terms of rank increase. POPULATION: A cohort of STEM faculty hired as assistant professors from 2000-2003 RESULT: Supported

36. Analyzing the Relationship among NETWORK STRUCTURE, PRODUCTIVITY and CAREER ADVANCEMENT 2000-2010

37. NETWORK “CENTRALITY” MEASURES Degree Centrality— The number of connections (“ties”) a person (“node”) has. High degree centrality indicates well-connected people who can directly reach many people in the network. Degree

38. NETWORK “CENTRALITY” MEASURES Betweenness Centrality— reflects the extent to which an individual has the ability to broker the flow of information in the network. Betweenness

39. NETWORK “CENTRALITY” MEASURES Eigenvector Centrality— reflects the extent to which an individual is connected to well-connected people in the network. Eigenvector

40. Hypothesis Testing H5. Faculty with higher Betweenness Centrality will publish more than faculty with lower Betweenness Centrality. POPULATION: All tenured/tenure track STEM faculty (n=327) RESULT: Strongly Supported

41. SUMMARY OF RESULTS: For NJIT STEM Faculty (2000-2010) Collaboration (co-authorship) Was positively correlated with Productivity Retention Promotion

42. SUMMARY OF RESULTS: • For NJIT STEM Faculty (2000-2010), the most important  predictors of productivity were: • co-authoring with non-NJIT researchers (“cosmopolitan collaboration”); • co-authoring with NJIT graduate students (the “worker bee connection”); • co-authoring with NJIT colleagues; • Betweenness Centrality.

43. Preferential Attachment & The Worker Bee Connection • The Case of Assistant Professor Y • Publication rate for successful assistant professors • = 8.67 papers per year • Publication rate for Assistant Professor Y • = 39 papers a year! • His secret? • Y was a post-doc—and now junior colleague--to one of NJIT’s most prolific and well-funded researchers, “Professor Z,” a man who from 2000-2010 produced over 150 publications, including more than 100 co-authored with one or more of his large stable of graduate students.

44. PRODUCTIVITY AND GENDER • The Case of Professor Y helps to explain one seemingly anomalous result in our data analysis: • THE GENDER PUBLICATION GAP • NATIONAL DATA: • "Women publish between 70% and 80% as many articles as men." - Lariviere, 2011 • NJIT STEM FACULTY DATA (2000-2010): • Female mean publication rate: 12.08 (SD=8.83) • Male mean publication rate: 19.19 (SD=13.34) • i.e. The female pub rate was only 63% of the male rate.

45. NO GENDER DIFFERENCE IN P&T NJIT 2000-2003: No statistically significant difference in retention and P&T rates for female & male STEM faculty Assistant Professor Cohort Hired 2000-2003: No statistically significant difference in publication rates for successful assistant professors. The most productive assistant professors, both male and female, tended to collaborate more--and to co-author more papers with graduate students. SO, WHY THE OVERALL GENDER PUBLICATION GAP?

46. ONE ANSWER: HYPERPRODUCTIVITY AT THE TOP: The Worker Bee Connection NJIT T/TT STEM Faculty 2000-2010 20 men --5.7% of the total STEM faculty-- produced 33% of all publications A majority of these Top 20 Males are directors of one of NJIT's large funded research centers (like "Professor Z") or Associated with a research center (like "Professor Y“)

47. HYPERPRODUCTIVITY AT THE TOP: • The Worker Bee Connection • All Top 20 Males are full or distinguished professors. • A majority already held that rank in 2000. • All NJIT Research Center directors are male. • 55% of the Top 20 Males‘ papers • had NJIT grad students as co-authors. • If we include both genders, only one woman appears in the Top 20 list of highest producers.

48. WHAT WE CAN DO Leverage the mechanism of "preferential attachment" ("the rich get richer") IN MENTORING: Connect new and marginalized faculty to graduate students (and undergrads looking for research experience)--and to senior colleagues who have large worker bee colonies IN GRANT FUNDING: Fund clusters of women researchers, post-docs, and graduate students, building the network around existing "stars"--senior faculty who have high centrality values.

49. Leveraging the Benefits of COLLABORATION

50. The Benefits of Collaboration • Increased productivity and advancement! • Division of labor; • Partnership with colleagues who have complimentary expertise; • Access to expensive equipment; • Access to graduate student RAs; • Intellectual stimulation; • Collaboration among people with different intellectual tool kits drives knowledge creation and innovation; • Access to new and novel information; • Access to tacit knowledge; • Devil's advocacy; • Internal referring weeds out unfruitful approaches; • Safe reality checking; • Diminished social isolation; • Increased social capital.