Cassidy Sugimoto is Associate Professor in the School of Informatics and Computing, Indiana University Bloomington, who researches within the domain of scholarly communication and scientometrics, examining the formal and informal ways in which knowledge producers consume and disseminate scholarship. She presented this talk, entitled Labor And Reward In Science: Do Women Have An Equal Voice In Scholarly Communication? A Brown Bag With Cassidy Sugimoto, as part of the Program on Information Science Brown Bag Series. Despite progress, gender disparities in science persist. Women remain underrepresented in the scientific workforce and under rewarded for their contributions. This talk will examine multiple layers of gender disparities in science, triangulating data from scientometrics, surveys, and social media to provide a broader perspective on the gendered nature of scientific communication. The extent of gender disparities and the ways in which new media are changing these patterns will be discussed. The talk will end with a discussion of interventions, with a particular focus on the roles of libraries, publishers, and other actors in the scholarly ecosystem..

1. Labor and Reward in Science: Do
Women Have an Equal Voice in
Scholarly Communication
Cassidy R. Sugimoto
School of Informatics and Computing
Indiana University Bloomington
@csugimoto
Vincent Lariviere
EBSI
Université de Montréal
@lariviev

2. WHO PARTICIPATES IN SCIENCE?
HOW DO THEY PARTICIPATE?
HOW ARE THEY REWARDED?

3. “WHAT DOES IT MATTER
WHO IS SPEAKING?”
. . . . . . . .
What is an author?
Michel Foucault (1969)

4. . . . . . . . .
Functions of authorship
Birnholtz (2006)

5. . . . . . . . .
Hyperauthorship
Cronin (2001)

6. . . . . . . . .
Demise of the single author
Lariviere, Sugimoto, Tsou, & Gingras (2015)

7. . . . . . . . .
What do we know about authorship?
There are differences by discipline.
--(Pontille, 2004; Biagioli, 2006; Biagioli, 2003; Birnholtz, 2006)
Authors do bad things.
--(Gøtzsche et al., 2007; Flanagin et al., 1998)

8. . . . . . . . .
Criteria for authorship
ICMJE
Authorship credit should be based on
1) substantial contribution to conception and design, or acquisition of
data, or analysis and interpretation of data; AND
2) drafting the article or revising it critically for important intellectual
content; and AND
3) final approval of the version to be published. Authors should meet
conditions 1, 2, and 3. AND
4) Agreement to be accountable for all aspects of the work and identify
which co-authors are responsible for specific parts of the work. Should
have confidence in the integrity of the conclusions of their co-authors

9. AUTHORSHIP FAILS
TO CAPTURE LABOR

10. . . . . . . . .
New forms of attribution
PLOS
Authorship
Contributorship
Acknowledgements

11. . . . . . . . .
Description of data
PLOS journal articles
Articles Author-article combinations
N % N %
Analyzed the data 85,900 98.7% 320,080 50.6%
Conceived and designed the experiments 85,406 98.2% 288,765 45.6%
Contributed reagents/materials/analysis tools 64,444 74.1% 220,331 34.8%
Performed the experiments 82,811 95.2% 311,679 49.3%
Wrote the paper 86,517 99.4% 287,796 45.5%
Other (20 243) 15,900 18.3% 79,978 12.6%
N distinct papers 87,002 100.0% 632,799 100.0%
Contribution

12. . . . . . . . .
How distributed is the labor?
Distribution of contributions, by field
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
All Fields
Clinical Medicine
Health
Biomedical Research
Biology
Chemistry
Social Sciences
Engineering and Technology
Psychology
Earth and Space
Mathematics
Professional Fields
Physics
Percentage of authors
5 Contributions 4 Contributions 3 Contributions 2 Contributions 1 Contribution

13. . . . . . . . .
Which contributions are isolated?
Contribution by number of contributions
Nb. of Contribution
1 2 3 4 5
Analyzed the data
Conceived and designed the experiments
Contributed reagents/materials/analysis tools
Performed the experiments
Wrote the paper
Contribution

14. DR. RUTH
HUBBARD
“Women and nonwhite, working-class and
poor men have largely been outside the
process of science-making. Though we
have been described by scientists, by and
large we have not been the describers and
definers of scientific reality. We have not
formulated the questions scientists ask,
nor have we answered them. This
undoubtedly has affected the content of
science, but it has also affected the social
context and the ambience in which science
is done.” (New York Times, 1981)

15. . . . . . . . .
Gender differences in production?
Female/male productivity by country (2008-2012, Nature)

16. . . . . . . . .
Gender differences by discipline?
Female/male productivity by discipline

17. . . . . . . . .
Gender differences in collaboration?
National vs. international collaboration by gender

18. . . . . . . . .
Implications for reward system?
Citation impact by type of collaboration and country

19. . . . . . . . .
Citations v. Impact Factor
Disparity in citations and impact factor by gender

20. . . . . . . . .
The impact factor gap
Disparity in impact factor by gender
0
0.5
1
1.5
2
2.5
3
3.5
Meanfield-normalizedciationrate
Field-Normalized Impact Factor Class
Last author
0
0.5
1
1.5
2
2.5
3
3.5
ARC
Field-Normalized Impact Factor Class
First author
M
F

21. LET US RETURN TO LABOR…

22. . . . . . . . .
Are labor roles gendered?
Odds of female contribution by type

23. . . . . . . . .
Does the gender of the leader matter?
Proportion of authors contributing by author position

24. . . . . . . . .
Many hands makes light work…
Contribution distribution by number of authors

25. WHAT DO THE
AUTHORS HAVE TO SAY?

26. . . . . . . . .
Authorship survey
Asking the authors
• Data: 5309 cases with all relevant variables
(of more than 11k responses)
– Gender, rank, discipline, # of collaboratively authored
publications
– Question: “Have you ever encountered disagreement
regarding authorship naming?” (yes/no)
• Method: Logistic regression
• Results: Controlling for all other variables,
women were significantly (p<.000) more likely
to report author disputes than men.

27. . . . . . . . .
Disagreement factors by gender
Percentage of “very important” or “extremely important”
Figure 1. Proportion of respondents who have A) selected a specific fa
0% 20% 40% 60% 80%
Difference between team authorship
practices and those of journal
Differing disciplinary practices
Differing values
Differing ethics
Lack of agreement within the team
Lack of clarity of authorship definition
Different ways of valuing importance
of contribution
Factors contributing to disagreement
0%
Management
Technical
work
Literature
review
Data
collection
Study design
Data analysis
Writing
manuscript
C

28. . . . . . . . .
Valued contributions by gender
Percentage of “very important” or “extremely important”
who have A) selected a specific factor as contributing to
40% 60% 80%
agreement
0% 20% 40% 60% 80% 100%
Management
Technical
work
Literature
review
Data
collection
Study design
Data analysis
Writing
manuscript
Contributions valued
Women
Men

29. . . . . . . . .
Open-ended questions
Directed and non-directed responses on survey
“I think seniority is important, but perhaps not
in the way other respondents do - I really try to
encourage students and junior faculty to take
the lead on articles, and all other things being
equal, will favor female authors in ordering
decisions. As a white cis het male full professor, I
really don't need the modest advantage of first
authorship.”

30. . . . . . . . .
Open-ended questions
Directed and non-directed responses on survey
“I believe females are often discriminated
against in authorship attribution. Males are
included who had very little to do with the
research but who are considered crucial to the
PIs employment and promotion prospects.
Females who made significant contributions
are left off.”

31. . . . . . . . .
Open-ended questions
Directed and non-directed responses on survey
“When working as the main person on a project
and becoming third author on the main paper, I
got a bit disappointed. But the senior person
had the right to set the order. In conversations
at conferences people also sometimes will refer
to a male second author as the main
contributor when I was the first author and did
the majority of the work.”

32. BUT DOES IT CHANGE WHAT
QUESTIONS ARE ASKED?

33. . . . . . . . .
Gender as an object of study
Percentage of studies which examine male/female populations

34. . . . . . . . .
Gender as an object of study
Percentage of studies with gender by subdiscipline

35. . . . . . . . .
Gender as an object of study
Percentage of male/female authors incorporating gender
0% 10% 20% 30% 40% 50% 60% 70%
F
M
F
M
F
M
Health(SS)ClinicalMedicine
Biomedical
Research
Last author
Female only
Male only
Both genders
0% 10% 20% 30% 40% 50% 60% 70%
Female
Male
Female
Male
Female
Male
Health(SS)ClinicalMedicine
Biomedical
Research
First author

36. THE PIPELINE PROBLEM

37. The pipeline metaphor
Women have earned half of all STEM degrees
in the US since the 1990s…

38. The pipeline metaphor
…yet comprise only a third of the scientific
workforce.

39. . . . . . . . .
Is the situation improving?
Percentage of female authors, by domain
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
2008 2009 2010 2011 2012 2013 2014 2015
Percentageoffemaleauthors
Social Sciences
Arts and Humanities
Medical Sciences
Natural Sciences

40. . . . . . . . .
Set destination: 2150!
Percentage of female authors, by domain -- predicted
0%
10%
20%
30%
40%
50%
60%
2008 2018 2028 2038 2048 2058 2068 2078 2088 2098 2108 2118 2128 2138 2148
Percentageoffemaleauthors
Social Sciences
Arts and Humanities
Medical Sciences
Natural Sciences
Social Sciences
Arts and Humanities
Medical Sciences
Natural Sciences
Social Sciences
Arts and Humanities
Medical Sciences
Natural Sciences

41. CHANGING PERCEPTIONS

42. Perpetuating disparities online
Self-presentation in scholarly profiles (Tsou et al., 2016)

43. Perpetuating disparities online
Self-presentation in scholarly profiles (Tsou et al., 2016)

44. Perceptions of the “man of science”
Perceptions of performance in bio classes (Grunspan, et al., 2016)
Grunspan DZ, Eddy SL, Brownell SE, Wiggins BL, Crowe AJ, et al. (2016) Males Under-Estimate Academic Performance of Their Female Peers in
Undergraduate Biology Classrooms. PLOS ONE 11(2): e0148405. https://doi.org/10.1371/journal.pone.0148405
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148405

45. That certain something…
Innate abilities and representation of women (Leslie et al., 2015)

46. Bias, not disparity
Double-blind study of lab manager applications (Moss-Racusin, et al., 2012)
Corinne A. Moss-Racusin et al. PNAS 2012;109:16474-16479

47. ARE THINGS CHANGING?

48. . . . . . . . .
Open <fill in the blank>

49. . . . . . . . .
Defense of a core value
Daniel Colt Gilman (1878)
“It is one of the noblest
duties of a university to
advance knowledge, and
to diffuse it not merely
among those who can
attend the daily
lectures—but far and
wide”

51. . . . . . . . .
OA mandates
Roarmap.eprints.org (2017)

54. . . . . . . . .
Altmetric aggregators
Altmetric and PlumAnalytics

55. Gender differences in altmetric indicators
Discipline
F M F M F M F M F M F M
Arts 0.35 0.37 4.53 4.09 18% 15% 0.03 0.04 0.01 0.01 0.01 0.01
Biology 2.39 2.49 12.62 13.39 25% 27% 0.12 0.14 0.04 0.04 0.01 0.02
Biomedical Research 4.03 4.66 15.41 18.27 40% 41% 0.36 0.39 0.09 0.13 0.02 0.03
Chemistry 3.79 4.41 6.42 7.09 19% 20% 0.04 0.04 0.01 0.02 0.00 0.00
Clinical Medicine 3.26 3.42 10.02 9.60 42% 39% 0.37 0.38 0.05 0.04 0.01 0.01
Earth & Space 3.05 3.31 10.70 9.69 23% 21% 0.16 0.15 0.06 0.07 0.02 0.03
Engineering & Technology 2.80 2.68 7.54 7.60 6% 6% 0.03 0.02 0.01 0.01 0.00 0.00
Health 1.62 2.00 10.87 11.29 54% 55% 0.27 0.30 0.05 0.09 0.00 0.01
Humanities 0.49 0.42 4.90 4.31 22% 24% 0.05 0.09 0.02 0.02 0.00 0.01
Mathematics 1.06 1.15 2.75 2.86 6% 6% 0.02 0.02 0.01 0.01 0.00 0.00
Physics 2.45 2.76 5.45 6.00 9% 10% 0.02 0.04 0.01 0.02 0.00 0.00
Professional Fields 1.24 1.42 18.63 19.77 37% 31% 0.09 0.07 0.03 0.02 0.00 0.01
Psychology 2.15 2.45 17.56 18.53 49% 48% 0.22 0.23 0.10 0.12 0.01 0.02
Social Sciences 1.34 1.40 12.81 12.70 36% 34% 0.11 0.11 0.04 0.06 0.01 0.01
Mendeley WikipediaTwitter Facebook BlogsCitations

57. . . . . . . . .
Initiative for Open Citations
I4OC
0 5 10 15 20 25 30 35 40 45
Now
March

58. . . . . . . . .
Model of science communication
UNISIST (1971)
PRODUCERS
ABSTRACTING &
INDEXING SERVICES
PUBLISHERS,
EDITORS
LIBRARIES
INFORMATION
CENTERS
CLEARING
HOUSES
DATA
CENTERS
USERS
PRIMARY SOURCES
SECONDARY SOURCES
TERTIARY SERVICES
Selection
Production
Distribution
Analysis & storage
Dissemination
Evolution
Compression
Consolidation
Qualified
surveys
(tabular)(formal)
(unpublished)(published)
(informal)
Talks, lectures,
conferences, etc.
Letters to
editors, preprints,
etc. Books, Journals Thesis, reports
Abstracts &
Index
Journals
Catalogs, Guides
Reference Services,
etc.
Reviews,
Syntheses, etc.
Special
Bibliographies,
Translations, etc.

59. . . . . . . . .
Acknowledge new forms of search
GoogleTrends (2017)
Figure 2. Google searches for the three main citation indexes, 2004-2016. Source: Google
Trends.
0
10
20
30
40
50
60
70
80
90
100SearchesonGoogle(Max=100)
Google Scholar
Scopus
Web of Science /
Web of Knowledge

60. . . . . . . . .
Blurring of boundaries
Losing the distinctions between creators and consumers
Draft Tweet
Creator
Consumer
Prosumer

61. . . . . . . . .
Open science, not feral science

62. . . . . . . . .
Standardization and interoperability

63. . . . . . . . .
Authorship badges
BioMed Central

64. . . . . . . . .
CRediT taxonomy
PLOS

65. . . . . . . . .
Transparency to end disparity?
Interoperability
Mentoring
Grant
Metrics
Publication
As Protégé
• Dissertation
• Advisor
• Discipline
• Institution
• More…
As Mentor
• Advisees
• Affiliation
• Discipline
• More….
NSF
•Award
•Amount
•Time
•More…
NIH
•Award
•Amount
•Time
•More…
NEH
•Award
•Amount
•Time
•More…
Publication
• Papers
• Venue
• Topics
• More….
Citation
•Cites
•References
•More…
Collaboration
• Co-author
• More….
Demo.
Demographic
•Gender
•Career Age
•More…
SNS
•Twitter
•Facebook
•More…
Ref. Man.
•Mendeley
•Zotero
Press
•Blogs
•News
•More…

66. . . . . . . . .
Avoiding goal displacement
Kardashian index (Hall, 2014)

67. WHAT CAN LIBRARIANS DO?

68. . . . . . . . .
Defending openness & disrupting barriers
Role for librarians (2017)
• Use and promote open access in training sessions
• Provide programming that lessens barriers to participation
for women and minorities
• Advocate for contributorship models which recognize the
diversity of knowledge production
• Approach new metrics with productive skepticism
• Encourage engagement between students and scholars
• Evaluate and contribute to the development of new tools

69. Thank you!
Questions?
Cassidy R. Sugimoto
Associate Professor, School of Informatics and Computing
Indiana University Bloomington
sugimoto@indiana.edu
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