DOI: 10.5061/dryad.t4b8gtj86
title: Data from: Working groups, gender and publication impact of Canada’s ecology and evolution faculty

description: Working groups are recognized as a highly effective method for
 synthesizing science. It is less clear if participating in working groups
 benefits individual researchers, or if benefits differ between men and
 women. This is a critical question, for the working group method is not
 sustainable if the benefit to science comes at a cost to academic careers
 or gender equity. Here, we analyze the publications of Canadian university
 faculty specialized in ecology and evolution (N=1244), a field that has
 embraced the working group method. Researchers were more likely to have
 participated in a working group as their academic age and prior H-index
 increased, but controlling for these factors there was no effect of
 gender. Using a longitudinal analysis, we find that researcher H-indices
 accrue 14% faster following their first working group publication,
 regardless of gender. Part of this acceleration may be the 3- to 5-fold
 higher citation rate of working group synthesis publications. In a survey
 (N=169), researchers also report indirect benefits of working groups, at
 similar rates for men and women.  Working groups are therefore,
 good not just for science but also for scientists. Formalized mechanisms
 for collaborations such as working groups may also offset gender
 inequities in science.
description: We compiled information on 1,244 faculty members at Canadian
 universities who were funded by a NSERC Discovery grant (Evolution and
 Ecology subcommittee) between 1991 and 2019. This information included
 assumed binary gender from first names and institutional website use of
 pronouns and photographs (coded men, women); we acknowledge that we may
 have mis-assigned gender or failed to notice non-binary, transitional or
 fluid gender identities. We also collected information on the researcher’s
 year of PhD and all institutions they were affiliated with during their
 research career. This information was obtained from public curriculum
 vitae, institutional websites, personally-maintained researcher websites,
 academic networking platforms (LinkedIn, Research Gate), Google Scholar,
 and other public sources such as obituaries. For each researcher, we
 reconstructed their H-index through time using (1) a compiled list of
 their peer-reviewed publications and (2) the citations for each
 publication, for each calender year from the date of publication until
 2019. We compiled their publications using a recursive procedure, which
 started by first downloading all publications for individuals with the
 researcher’s first initial and last name from Web of Science Core
 Collection (hereafter, WOS) starting from 5 years prior to their PhD until
 2019, and then filtering this list by cross-referencing with known
 variants in authorship names for the researcher (from online curriculum
 vitae or Google Scholar profile) as well as their institutional
 affiliations, fuzzy matching of publication titles from their curriculum
 vitae or Google Scholar profile where possible, and recursive
 identification of previously unidentified affiliations to fine-tune the
 cross-referencing procedure. Once we had cleaned the publication record,
 we then calculated cumulative citations over years for each publication
 from WOS yearly citation counts as a precursor to calculating the
 H-index.  We identified a potential pool of
 publications from working groups by (1) matching WOS titles with known
 working group publications funded by the 15 synthesis centers that
 comprise the International Synthesis Consortium, (2) by searching the
 funding and acknowledgment sections of publications for synthesis centre
 names or acronyms, or keywords commonly used to describe working groups
 (“working group”, “synthesis group”, “synthesis working group”, “synthesis
 committee”, “synthesis workshop”, “catalysis group”). All publications
 from steps 1 and 2 were then manually coded as primary research vs.
 synthesis research, and as working group method vs. non-working group
 method. We further categorized synthesis research publications into the
 following types: statistical synthesis (statistical analysis of previously
 published or archived data collected by multiple different researchers
 and/or studies), conceptual synthesis (qualitative review of the
 literature or proposal of new frameworks for scientific concepts or
 investigation), or mathematical synthesis (theoretical mathematical models
 or specific application of general models for the purpose of prediction).
 We scored non-working group publications using similar criteria. However,
 given the large number of publications involved, we changed methods to
 allow for programmatic approaches based on keywords indicative of the
 three types of synthesis science. This data is presented in aggregated and
 anonymized form as needed to prevent the identification of
 individuals. We conducted an online survey of current
 ecology and evolution faculty in Canada from July to September 2019,
 recruited by email and supplemented by in-person recruitment at the
 Canadian Society of Ecology and Evolution annual conference (Fredericton
 NB Canada, August 18-21 2019). The 169 valid responses represent an
 effective questionnaire response rate of 14.7%. The questionnaire asked
 for information designed to confirm or complete the researcher database
 (e.g. academic history, gender) as well as information about why
 researchers participated or not in working groups, and the perceived costs
 and benefits of participation. This data is presented in condensed and
 anonymized form only to maintain the privacy of personal
 information. We used survival analysis to test if
 gender or pace of career progression (H-index adjusted for time since PhD)
 predicts the hazard rate of participation in working groups. We included
 an interaction between gender and H-index to assess whether potential
 selection effects tied to research record captured by the H-index are the
 same for women and men. We estimated hazard ratios for attending WGs using
 Cox proportional hazard models. For the 183 researchers
 who participated in working groups, we used a fixed effects model with a
 linear spline to investigate the effects of working group participation
 and gender on researchers’ trajectory of H-indices over time. This model
 compares the trajectory of researchers’ H-indices in years before (0-5
 years before) and after (1-5 years after, and &gt;6 years after)
 participating in working groups, and then averaging those differences
 across researchers. To account for autocorrelation within individuals and
 heteroscedasticity across individuals, we clustered on individuals. We
 used a 0.67 power transformation on the “time” variable to linearize the
 H-index ~ time relationship. We code the spline specification in marginal
 form, which makes interpretation simple: coefficients of the second and
 third intervals capture changes in H-index growth rates from their prior
 intervals. The effects of research type (synthesis vs
 primary) and method (working group vs traditional) on publication citation
 rates were evaluated with a zero-inflated generalized linear model based
 on a negative binomial error distribution with a log link (R package
 glmmTMB). The survey results were evaluated with simple
 Chi-square tests of association.
description: # Data from: "Working groups, gender and publication impact of
 Canada’s ecology and evolution faculty" ## Description of the Data
 and file structure This readme file describes the (1) scripts and (2)
 datafiles included in this repository. Missing data in data files are
 indicated as NA. All data files are in .csv format meaning that “,” is
 used as the separator. # (1) Scripts ## paper\_analysis.do: This do file
 is written using Stata 18.0. This script analyses whether working group
 (WG) experience has a significant impact on researchers' Hindex
 progression and whether this benefit or WG participation is gendered.
 Input: researcher_database.csv Output: Table 1, Table 2, Figure 1(a) (b)
 (c), Figure 3(a) (b) ## SSS\_citations\_public.R: This script is written
 in the programming language R. The script analyses the effect of research
 type and research method on the citations of publications using
 generalized linear models. The script also plots this data. Input:
 syn_sc_socio_public_citations.csv Output: pubs.tif, pubs.pdf ##
 survey\_sss\_public.R: This script is written in the programming language
 R. The script compiles information from a questionnaire given to Canadian
 university faculty specialized in ecology and evolution about their
 experience of working groups. The script uses Chi squared tests to examine
 if faculty experience of working groups differs between men and women. The
 script also plots this data Input: Synthesis_science_survey_public.csv
 Output: multibar.tif, multibar.pdf # (2) Data files ## Description of
 "researcher\_database.csv" The file
 "researcher_database.csv" is a comma (",") delimited
 table with 83348 rows and 7 columns. Our sample is structured in
 individual-year format. Each row represents a researcher observed in a
 particular year. We have binned the years of PhD completion to anonymize
 this data. This data can be analysed with the
 "paper_analysis.do" script. Missing data is indicated with NA.
 The columns contain the following data: *id_1*: integer variable which
 contains the random id numbers assigned to each researcher. *year*:
 integer variable indicating the calendar years from 1953 to 2019.
 *hindex*: integer variable showing the Hindex of a researcher in a certain
 year. *gender*: factor variable taking two values: "Men (0)" and
 "Women (1)". *pub_sc_wg_raw*: numeric variable indicating the
 number of working group publications. *phd_year_bin*: character variable
 indicating the range of years in which the researcher received the PhD
 degree. *wg1_year*: numeric variable showing the years of the
 researchers' first working group publications. ## Description of
 "syn\_sc\_socio\_public\_citations.csv" The file
 "syn_sc_socio_public_citations.csv" is a comma (",")
 delimited table with 2486 rows and 8 columns. Each row represents a
 selected publication published by a Canadian university faculty member
 with specialization in in ecology and evolution. Although publication
 citation information is technically in the public domain, we have removed
 author and title information to anonymize this data. This data can be
 analysed with the "SSS_citations_public.R" script. Missing data
 is indicated with NA. The columns contain the following data: *type*:
 character variable indicating the type research in the publication, taking
 one of four values - "Meta-analysis", "Review",
 "Model", "Primary": "Meta-analysis" is
 defined as a quantitative meta-analysis of previously published data
 "Review" is defined as a qualitative synthesis or summary of
 previously published results "Model" is defined as mathematical
 or conceptual framework for predicting future results or understanding
 previous results, excluding purely statistical models "Primary"
 is defined as the original collection of new data *method*: character
 variable indicating the method used to conduct the research in the
 publication, either "Traditional" or "Working group".
 "Working group" is defined as collaborative research conducted
 largely in a small group meeting assembled for that purpose, often at
 synthesis centres "Traditional" is defined as research conducted
 by means other than a working group *level*: character variable
 summarizing the level of research, either "Primary" (when type =
 "Primary) or "Synthesis" (when type =
 "Meta-analysis" or "Review" or"Model")
 *citations*: numerical variable indicating the mean annual number of
 citations of the publication from the year of publication until 2019
 *synthesis_science_dummy*: numerical variable taking the value
 "0" (level = "Primary") and "1" (level =
 "Synthesis") *wg_dummy*: numerical variable taking the value
 "0" (method = "Traditional") and "1" (method
 = "Working group") *years_since*: integer variable indicating
 the number of years that have elapsed between publication and the year
 2019 (e.g. an article published in 2018 has years_since = 1)
 *citations_decade*: integer variable which estimates the number of
 citations in a decade, calculated as "citations" x 10 rounded to
 the nearest integer. ## Description of
 "Synthesis\_science\_survey\_public.csv" The file
 "Synthesis_science_survey_public.csv" is a comma (",")
 delimited table with 169 rows and 7 columns. Each row represents one
 respondent to an online and in-person questionnaire. Respondents are
 faculty at Canadian universities with speciality in ecology and evolution.
 To preserve anonymity of respondents, we report here only the 7 responses
 analyzed in this study an provide no additional identifying information.
 This data can be analysed with the "survey_sss_public.R" script.
 Missing data is indicated with NA and often means that the question did
 not apply to the respondent. The columns contain the following data:
 *gender*: character variable which contains identity as male
 ("M") or female ("F"); other gender identities not
 given. *WG(yes or no)*: character variable which contains answer yes
 ("Y") or no ("N") to question "Are you currently
 or have you ever been part of a Working Group?" *decline_WG*:
 character variable which contains answer yes ("Y") or no
 ("N") to question "Have you ever declined an invitation to
 participate in a working group?" *decline_reason*: character variable
 which contains answer to question "If yes, why" when decline_WG
 = Y. Respondents chose one of "I was too busy or could not travel due
 to work-related duties", "I was too busy or could not travel due
 to family-related duties", "I was not interested in the
 topic", "I do not like the working group method", "If
 other, please specify" *subsequent_colla*: character variable which
 contains answer to "How many participants from this working group
 have you subsequently collaborated with in other contexts?" with the
 answers generally being a number but also including text answers such as
 "Aucun"(translation of “Aucun” [French] is "none").
 This question referred just to the most recent working group of the
 respondent. We altered the entry “2-3” to “2 to 3” to prevent this entry
 being misinterpreted as a date. *reuse*: character variable. If the
 respondent had constructed a dataset in their most recent working group,
 they were then asked "Has this dataset been used for other projects,
 besides the original project of the working group?". This variable
 contains the reply, either "Yes" or "No"
 *future_fund*: character variable which contains answer to "Has your
 participation in this working group led to funding opportunities?",
 either "Yes" or "No". This question referred just to
 the most recent working group of the respondent. ## Sharing/access
 Information Links to other publicly accessible locations of the data: No
 other publicly accessible location Was data derived from another source?
 Yes (variable "citations" only, all other variables original) If
 yes, list source(s): Clarivate Web of Science