Labor and Reward in Science: Do Women Have an Equal Voice in

Scholarly Communication

Cassidy R. SugimotoSchool of Informatics and Computing

Indiana University Bloomington

@csugimoto

Vincent LariviereEBSI

Université de Montréal

@lariviev

WHO PARTICIPATES IN SCIENCE?

HOW DO THEY PARTICIPATE?

HOW ARE THEY REWARDED?

“WHAT DOES IT MATTER WHO IS SPEAKING?”

. . . . . . . .

What is an author?Michel Foucault (1969)

. . . . . . . .

Functions of authorshipBirnholtz (2006)

. . . . . . . .

HyperauthorshipCronin (2001)

. . . . . . . .

Demise of the single authorLariviere, Sugimoto, Tsou, & Gingras (2015)

. . . . . . . .

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)

. . . . . . . .

Criteria for authorshipICMJE

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

AUTHORSHIP FAILS TO CAPTURE LABOR

. . . . . . . .

New forms of attributionPLOS

Authorship

Contributorship

Acknowledgements

. . . . . . . .

Description of dataPLOS 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

. . . . . . . .

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

. . . . . . . .

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

DR. RUTHHUBBARD

“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)

. . . . . . . .

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

. . . . . . . .

Gender differences by discipline?Female/male productivity by discipline

. . . . . . . .

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

. . . . . . . .

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

. . . . . . . .

Citations v. Impact FactorDisparity in citations and impact factor by gender

. . . . . . . .

The impact factor gapDisparity in impact factor by gender

0

0.5

1

1.5

2

2.5

3

3.5

Mean f

ield

-norm

aliz

ed c

iatio

n r

ate

Field-Normalized Impact Factor Class

Last author

0

0.5

1

1.5

2

2.5

3

3.5

AR

C

Field-Normalized Impact Factor Class

First author

M

F

LET US RETURN TO LABOR…

. . . . . . . .

Are labor roles gendered?Odds of female contribution by type

. . . . . . . .

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

. . . . . . . .

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

WHAT DO THE AUTHORS HAVE TO SAY?

. . . . . . . .

Authorship surveyAsking 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.

. . . . . . . .

Disagreement factors by genderPercentage of “very important” or “extremely important”

Figure 1. Proportion of respondents who have A) selected a specific factor as contributing to

authorship disagreements and B) valued a contribution as “very important” or “extremely important”,

by gender.

0% 20% 40% 60% 80%

Difference between team authorshippractices 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 importanceof contribution

Factors contributing to disagreement

0% 20% 40% 60% 80% 100%

Management

Technicalwork

Literaturereview

Datacollection

Study design

Data analysis

Writingmanuscript

Contributions valued

Women

Men

. . . . . . . .

Valued contributions by genderPercentage of “very important” or “extremely important”

Figure 1. Proportion of respondents who have A) selected a specific factor as contributing to

authorship disagreements and B) valued a contribution as “very important” or “extremely important”,

by gender.

0% 20% 40% 60% 80%

Difference between team authorshippractices 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 importanceof contribution

Factors contributing to disagreement

0% 20% 40% 60% 80% 100%

Management

Technicalwork

Literaturereview

Datacollection

Study design

Data analysis

Writingmanuscript

Contributions valued

Women

Men

. . . . . . . .

Open-ended questionsDirected 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.”

. . . . . . . .

Open-ended questionsDirected 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.”

. . . . . . . .

Open-ended questionsDirected 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.”

BUT DOES IT CHANGE WHAT QUESTIONS ARE ASKED?

. . . . . . . .

Gender as an object of studyPercentage of studies which examine male/female populations

. . . . . . . .

Gender as an object of studyPercentage of studies with gender by subdiscipline

. . . . . . . .

Gender as an object of studyPercentage of male/female authors incorporating gender

0% 10% 20% 30% 40% 50% 60% 70%

F

M

F

M

F

M

Hea

lth (

SS

)C

linic

al M

edic

ine

Bio

med

ical

Res

earc

h

Last author

Female only

Male only

Both genders

0% 10% 20% 30% 40% 50% 60% 70%

Female

Male

Female

Male

Female

Male

Hea

lth (

SS

)C

linic

al M

edic

ine

Bio

med

ical

Res

earc

h

First author

THE PIPELINE PROBLEM

The pipeline metaphor

Women have earned half of all STEM degrees

in the US since the 1990s…

The pipeline metaphor

…yet comprise only a third of the scientific

workforce.

. . . . . . . .

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

Pe

rce

nta

ge

of f

em

ale

au

tho

rs

Social Sciences

Arts and Humanities

Medical Sciences

Natural Sciences

. . . . . . . .

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

Pe

rce

nta

ge

of f

em

ale

au

tho

rs

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

CHANGING PERCEPTIONS

Perpetuating disparities onlineSelf-presentation in scholarly profiles (Tsou et al., 2016)

Perpetuating disparities onlineSelf-presentation in scholarly profiles (Tsou et al., 2016)

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.0148405http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148405

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

Bias, not disparityDouble-blind study of lab manager applications (Moss-Racusin, et al., 2012)

Corinne A. Moss-Racusin et al. PNAS 2012;109:16474-16479

ARE THINGS CHANGING?

. . . . . . . .

Open <fill in the blank>

. . . . . . . .

Defense of a core valueDaniel 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”

. . . . . . . .

OA mandatesRoarmap.eprints.org (2017)

. . . . . . . .

Altmetric aggregatorsAltmetric and PlumAnalytics

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

. . . . . . . .

Initiative for Open CitationsI4OC

0 5 10 15 20 25 30 35 40 45

Now

March

. . . . . . . .

Model of science communicationUNISIST (1971)

PRODUCERS

ABSTRACTING &

INDEXING SERVICES

PUBLISHERS,

EDITORS

LIBRARIES

INFORMATION

CENTERS

CLEARING

HOUSES

DATA

CENTERS

USERS

PRIMARY SOURCES

SECONDARY SOURCES

TERTIARY SERVICES

SelectionProductionDistribution

Analysis & storageDissemination

EvolutionCompressionConsolidation

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.

. . . . . . . .

Acknowledge new forms of searchGoogleTrends (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

100S

earc

hes

on G

oogl

e (M

ax =

100

)

Google Scholar

Scopus

Web of Science /Web of Knowledge

. . . . . . . .

Blurring of boundariesLosing the distinctions between creators and consumers

Draft TweetCreator

Consumer

Prosumer

. . . . . . . .

Open science, not feral science

. . . . . . . .

Standardization and interoperability

. . . . . . . .

Authorship badgesBioMed Central

. . . . . . . .

CRediT taxonomyPLOS

. . . . . . . .

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…

. . . . . . . .

Avoiding goal displacementKardashian index (Hall, 2014)

WHAT CAN LIBRARIANS DO?

. . . . . . . .

Defending openness & disrupting barriersRole 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

Thank you!

Questions?

Cassidy R. SugimotoAssociate Professor, School of Informatics and Computing

Indiana University Bloomington

sugimoto@indiana.edu

Template by Dongoh Park