This document proposes a framework to quantify researcher diversity and its impact on productivity and awards. It suggests measuring diversity using Shannon entropy based on researchers' publication topics classified with MeSH terms. Higher diversity is correlated with lower productivity but higher awards. Future work could involve larger datasets and distinguishing specialists in the "long tail" from generalists at the "head of the tail".

1. Measuring Researcher Diversity
and its Impact on Awards
Tanu Malik Computation Institute
Andrey Rzhetsky Department of Human Genetics
Ian Foster Computation Institute
University of Chicago
Argonne National Laboratory

2. History Leonardo da Vinci
Bohr
Darwin
Renaissance polymath, painter, sculptor, architect,
musician, mathematician, engineer, inventor, anatomist,
Einstein
geologist, cartographer, botanist, and writer

3. Biological species
Short Term: Competition Long Term: Changing Environments
Competition Niche Differences
Adapted from: Levine, J. M. & HilleRisLambers, J. (2012) The Maintenance of Species Diversity. Nature Education Knowledge 3(10):59

4. Biological species:
Specialist/Generalist
Short Term: Competition Long Term: Changing Environments
Competition Niche Differences
Adapted from: Levine, J. M. & HilleRisLambers, J. (2012) The Maintenance of Species Diversity. Nature Education Knowledge 3(10):59

5. Science Research
Short Term: Competition on Topics Long Term: Changing Funding Situation
Competition Niche Differences

6. Why is this important?
• Research articles whose coauthors are in different departments at
the same university receive more citations than those authored in a
single department (Katz et.al, 1997).
• Multi–university collaborations that include a top tier–university
were found to produce the highest–impact research articles (Jones,
et al., 2008).
• It has also been demonstrated that scholarly work covering a range
of fields — and patents generated by larger teams of co–authors —
tend to have greater impact over time (Wuchty, et al., 2007).
• In the area of nanotechnology authors who have a diverse set of
collaborators tend to write articles that have higher impact (Rafols
et. al., 2010).
• Finally, diverse groups can, depending on the type of task,
outperform individual experts or even groups of experts (Page,
2007).

7. Individual Focus
• Some mathematicians are birds, other are frogs.
Birds fly high in the air, frogs live in the mud
below.. (Freeman Dyson, AMS Einstein Lecture,
2008)
• “Foxes”, individuals who know many little things,
tend to make better predictions about future
outcomes than “hedgehogs” who focus on one
big thing (Tetlock, 2005)
• Individuals’ degree of focus is positively
correlated with the quality of their contributions
(Adamic, 2010)

8. Goals and Problems
• Goal: Quantify the ability of each class of
researchers (specialists/generalists) to
competition in near term and adapt to
changing funding requirements in the long
term.
A. How to determine specialist and generalist
researchers?
B. How to quantify the ability to compete/adapt?

9. A. Researcher Diversity
• Based on their publication history, determine
if their interests can be classified into highly
varied interests or focused interests
• Researcher profiles created from PubMed

10. Creating Researcher Profiles
• Author Disambiguation
– Data mining methods
– Microsoft Academic Search
• Automated profiles of users
• Web scraping
• Person’s organization and domain
of interest as disambiguating features
– Harvard Profiles
• Directly links to PubMed
• Also takes an input of publications
claimed by an author.

11. Researcher’s Interests
• Controlled Vocabulary
• Keywords
• Topic Modeling

12. Controlled Vocabulary
• Medical Subject Headings (MeSH)
– poly-hierarchy of 25,186 medical concepts

13. Researcher Diversity
• Shannon’s Entropy
pi: proportion of individual’s contributions in
category i
– Category = MeSH term
– Frequency over years
0.00 0.41 0.82 1.00 1.59 2.00

14. Shannon Vs Sterling
• Variety: how many different areas an
individual contributes
• Balance: how evenly their efforts are
distributed among these areas; and,
• Similarity, or how related those areas are

15. B. Quantifying the Ability to Compete
• Entropy has a negative correlation with measures of impact and productivity,
viz. the h-index and the g-index.
• Result (in a way) reconfirms Adamic’s result of positive correlation between
specialist and productivity

16. Geniuses, Birds, Beavers, Frogs
Geniuses: Dwell on many topics at all times (8-9)
Birds: Dwell on many topics over their research career, but a few topics at a given time
Beavers: Specialists whose focus is interdisciplinary
Frogs: High-focused

17. A Bird

18. A Frog

19. Impact of Researcher Diversity on Awards

20. Future Work
• Larger datasets
• Researchers in the long tail are specialists;
generalists are in the head of the tail;

21. Summary
• A framework to understand researcher
diversity
• Quantification of researcher diversity with
productivity and awards
• Negative correlation of diversity with
productivity and positive with awards
• Use more accurate author disambiguation
methods