RESEARCH ARTICLE
Who’s writing open access (OA) articles?
Characteristics of OA authors at
Ph.D.-granting institutions in
the United States
a n o p e n a c c e s s
j o u r n a l
Anthony J. Olejniczak
and Molly J. Wilson
Academic Analytics Research Center (AARC), 1985 W Henderson Road #2159, Columbus, OH 43220
Citation: Olejniczak, UN. J., & Wilson,
M. J. (2020). Who’s writing open access
(OA) articles? Characteristics of OA
authors at Ph.D.-granting institutions in
the United States. Quantitative Science
Studi, 1(4), 1429–1450. https://doi
.org/10.1162/qss_a_00091
DOI:
https://doi.org/10.1162/qss_a_00091
Received: 20 Marzo 2020
Accepted: 8 settembre 2020
Corresponding Author:
Anthony J. Olejniczak
aolejniczak@academicanalytics.com
Handling Editor:
Ludo Waltman
Copyright: © 2020 Anthony J.
Olejniczak and Molly J. Wilson.
Pubblicato sotto Creative Commons
Attribuzione 4.0 Internazionale (CC BY 4.0)
licenza.
The MIT Press
Keywords: article processing charge, bibliometrics, open access, open access publishing, open
science, scholarly publishing
ABSTRACT
The open access (OA) publication movement aims to present research literature to the public at
no cost and with no restrictions. While the democratization of access to scholarly literature is a
primary focus of the movement, it remains unclear whether OA has uniformly democratized the
corpus of freely available research, or whether authors who choose to publish in OA venues
represent a particular subset of scholars—those with access to resources enabling them to afford
article processing charges (APCs). We investigated the number of OA articles with article
processing charges (APC OA) authored by 182,320 scholars with known demographic and
institutional characteristics at American research universities across 11 broad fields of study.
The results show, in general, that the likelihood for a scholar to author an APC OA article
increases with male gender, employment at a prestigious institution (AAU member universities),
association with a STEM discipline, greater federal research funding, and more advanced career
stage (cioè., higher professorial rank). Participation in APC OA publishing appears to be skewed
toward scholars with greater access to resources and job security.
1.
INTRODUCTION
1.1. Research Objective
Open access (OA) publications present research literature to the public at no cost and with no
restrictions. The themes of the open access movement center on research integrity, transparency,
and accessibility. Infatti, research funding agencies are more frequently promoting or mandating
publication in OA venues and dissemination of code, dati, and methods in open repositories
(Vedere, per esempio., http://roarmap.eprints.org). A fundamental goal of OA is that any person can read
published scholarly research, regardless of their ability to pay for access either personally or
through an institutional credential. While the democratization of access is a primary driver
behind the OA movement (Swan & Brown, 2004; Tennant, Waldner, et al., 2016) it remains
unclear whether OA has uniformly democratized the research corpus, or whether a particular
subset of authors is more likely to publish their work as OA (specifically, those with access to
resources to pay for article processing charges [APCs]).
OA can take many forms, with the most common referred to as a series of colors: Bronze (IL
article is free to read on the publisher’s website but no explicit license is presented); Verde (IL
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Who’s writing open access (OA) articles?
article is available in a repository, self-archived by the author); Gold (all articles in the journal are
OA); and Hybrid (individual articles are OA if the authors have paid a publication fee, but other
articles in the journal are closed). While Bronze and Green represent the majority of all OA
publications (Piwowar, Priem, et al., 2018), Gold and Hybrid are unique in that they reflect an
author’s deliberate decision to make their article immediately publicly available at the time of
pubblicazione, often paying an APC to do so. In light of these different OA types, we ask two specific
questions: (UN) What are the characteristics of authors who intend to publish openly immediately
(cioè., who choose to publish OA articles), E (B) Which authors are ultimately represented in the
OA literature, regardless of the means or type of OA?
1.2. Literature Review
There have been substantial efforts to understand the extent of OA adoption, but none have
allowed for granular analysis at the individual author level. Usually, studies focus on the overall
number of OA articles published as a percent of the total scholarly literature (E. Archambault,
Amyot, et al., 2014; Björk, Welling, et al., 2010; Laakso, Welling, et al., 2011; Piwowar et al.,
2018) or the number of journals indexed by OA directories such as ISSN’s ROAD (https://road
.issn.org/) or the Directory of Open Access Journals (DOAJ) (per esempio., Björk, 2019). Others have
examined OA by discipline, trovare, Per esempio, greater adoption in biomedical research areas
(Piwowar et al., 2018). Tuttavia, discipline-specific OA adoption is often done by a priori
classification of journal titles into fields. A disadvantage of this approach is that multidisciplinary
journals (per esempio., Nature, Scienza, PLOS ONE) necessitate a time-consuming procedure to subclas-
sify each individual article within those journals, as Piwowar et al. (2018) performed.
Additionally, a priori journal classifications fail to account for author-specific discipline affilia-
zioni. Per esempio, a scholar whose research program focuses on geochemistry may publish
in geology journals, while their academic appointment is in a chemistry department; tagging this
scholar’s work as only “geology” fails to capture their chemistry discipline affiliation and loses an
important characteristic of the individual author.
One frequently cited concern about OA publication is that the method places the burden of
publication cost on the scholar, rather than the traditional subscription model, where costs are
typically paid by libraries or other resources within a researcher’s employing institution. Solomon
and Björk (2012) reviewed APCs in OA journals, finding the average APC among OA journals
was just over US$900 at the time of their study; allo stesso modo, the mean APC was found to be US$899
by Siler and Frenken (2020). In a particularly sharp early criticism of the OA model, Stevenson
(2004) wrote in Times Higher Education: “The Public Library of Science and the other open-
access publishers were created to serve the interests of an elite well-funded and narrow research
community.” We sought to explore whether authors at more prestigious or wealthy universities
publish more often in OA, using the public/private distinction and AAU membership status1 as
the descriptors of institution type.
Another common reservation is the perception that OA journals are less prestigious or have a
less scrutinous peer review process (Agrawal, 2014; Beaubien & Eckard, 2014). Although there is
evidence that OA research is actually cited more frequently than research behind a paywall
(Piwowar et al., 2018), OA publishing is a relatively new phenomenon compared to the approx-
imately 350-year history of traditional scholarly journals (Mabe, 2003). We hypothesize that
1 The American Association of Universities (http://www.aau.edu) is an invitation-only group of 63 North
American research universities (at the time of our study) and membership is widely regarded as evidence
of institutional prestige and also access to research support resources. The AAU has been described as
“…perhaps the most elite organization in higher education” (Hine, 2010).
Quantitative Science Studies
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Who’s writing open access (OA) articles?
young scholars seeking tenure-track positions or promotions may be particularly influenced by
the perception of reduced prestige, opting to publish fewer OA articles until their careers are
established (cioè., they achieve a tenured position).
There is also evidence that gender affects publication patterns. Per esempio, differences in
publishing patterns between men and women are observed in terms of both overall article output
(per esempio., Cameron, White, & Gray, 2016; Ceci, Ginther, et al., 2014; Duch, Zeng, et al., 2012; Fox,
Burns, et al., 2016) and citation patterns, such as a greater proclivity to self-cite among men (King,
Bergstrom, et al., 2017). Mishra, Fegley, et al. (2018) found that self-citation differences were
largely due to career attrition disproportionately affecting women rather than gender itself as a
factor, which underscores that gendered differences in career trajectory play an important role in
observed publication and citation patterns. We therefore propose that proclivity to publish in OA
journals may also differ between men and women.
In sum, we hypothesize that individual author characteristics (discipline, career stage, overall
publication rate, federal research funding support, institution type, and gender) predict an
author’s likelihood of authoring OA articles in Gold and Hybrid venues, where the deliberate
intent to produce an OA article can be inferred. We further hypothesize that the same set of
factors predict an author’s overall representation in the OA literature (whether Gold, Hybrid,
Verde, or Bronze). Specifically, we predict that increased institutional prestige, male gender, more
advanced career stage, greater overall publishing activity, affiliation with STEM disciplines, E
increased federal research grant support will predict increased levels of all types of OA publishing.
2. DATA SOURCES
We culled the names of faculty members at research universities in the United States from the
Academic Analytics commercial database (v. AAD2018-1391; http://www.academicanalytics
.com), representing faculty rosters for the Fall 2018–Spring 2019 academic year. The Academic
Analytics database contains a comprehensive list of faculty members affiliated with one or more
academic departments at 390 Ph.D.-granting American research institutions (Supplementary Table 1;
https://osf.io/sb8fq/); each department is manually classified by Academic Analytics into one or
more of 11 fields of study (Tavolo 1). Academic Analytics uses manual disambiguation and matching
to associate each faculty member with their (co)authored CrossRef-DOI journal articles and each of
the federal research grants on which they served as a principal investigator (PI). The Academic
Analytics database also contains the year of terminal degree for each faculty member, obtained
by manual searching. Gender for each faculty member was inferred using genderize.io with a
95% threshold (https://genderize.io). Genderize.io uses a large, global sample of given names
associated with known gender gleaned from public social profiles to assign gender probabilities.
We used genderize.io to infer gender for the first and middle name of each scholar in the Academic
Analytics database; in cases where the first name resulted in a lower than 95% probability of infer-
ring the gender, we deferred to the result for the middle name. We kept in our sample only faculty
members with an inferred gender of “male” or “female” based on first name (or middle name when
the first name resulted in “unknown”). We assembled the following attributes for each faculty
member:
1. A binary indicator whether the faculty member has won federal research grant funding
over a 5-year period (2014–2018).
2. The total number of journal articles authored or coauthored over five years (2014–2018),
including the DOI, journal name, ISSN, and EISSN for each article for which the scholar is
listed as an author.
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Who’s writing open access (OA) articles?
Field
Agricultural Sciences
Biological and Biomedical Sciences
Business
Education
Engineering
Family, Consumer and Human Sciences
Health Professions Sciences
Humanities
Natural Resources and Conservation
Physical and Mathematical Sciences
Social and Behavioral Sciences
Tavolo 1.
Scholar and authorship counts by field
Number of
unique scholars
4,860
Scholars with at least
one authorship of any kind
4,510 (92.8%)
Scholars with at least
one APC OA authorship
3,448 (70.9%)
30,725
11,764
8,317
22,658
13,609
13,098
34,159
3,913
30,415
28,228
29,207 (95.1%)
25,930 (84.4%)
9,911 (84.2%)
6,466 (77.7%)
20,763 (91.6%)
10,072 (74.0%)
11,448 (87.4%)
19,852 (58.1%)
3,664 (93.6%)
27,843 (91.5%)
24,848 (88.0%)
1,594 (13.5%)
1,936 (23.3%)
14,753 (65.1%)
4,808 (35.3%)
7,738 (59.1%)
3,541 (10.4%)
2,977 (76.1%)
19,954 (65.6%)
10,076 (35.7%)
3. The professorial rank of each scholar (assistant professor, associate professor, full profes-
sor; while not always true, an associate or full professor title typically indicates a tenured
position, whereas assistant professors are usually not tenured).
4. The year each scholar completed their terminal degree (typically Ph.D., sometimes M.F.A.,
M.B.A., eccetera.).
5. An indicator of the scholar’s employing institution’s status as a public or private university.
6. An indicator of the scholar’s employing institution’s status as a member of the Association of
American Universities (AAU; http://www.aau.edu).
7. The inferred gender of each scholar.
We downloaded the contents of the Unpaywall database in December, 2019 (http://unpaywall
.org/; Piwowar et al., 2018). Unpaywall harvests article information from OA repositories and other
fonti, including CrossRef, PubMed Central, and DOAJ. We matched the DOI of articles matched
to scholars in the Academic Analytics database with the DOI from the Unpaywall database to clas-
sify each journal article (co-)authored by a researcher in our study sample as either “Closed” (non
OA), Bronze, Verde, Gold, or Hybrid. Over the 5-year study period, 1,585,176 (98%) of the journal
articles matched to scholars in our extract from Academic Analytics were also in Unpaywall with
their OA status indicated.
The Gold and Hybrid OA models both imply that the authors made an explicit decision to place
their article in an OA journal, agreeing to pay APCs and making their research available immedi-
ately upon publishing. We recognize that not all Gold OA journals charge APCs, but the Unpaywall
data do not distinguish non-APC from APC Gold journals. Inoltre, a majority of Gold OA articles
are published in venues that do charge APCs (see discussion by Crotty, 2015). Our research ques-
tions focus on (UN) an individual author’s decision to publish an article immediately upon publication,
including their willingness to absorb APCs, which is captured by their combined Gold and Hybrid
article count, E (B) an individual author’s representation in the OA literature as a whole, through
any mechanism or OA color. Inoltre, Unpaywall’s definitions of OA types distinguish Green
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from Hybrid OA explicitly: An article is Green if the publisher’s website charges a fee for the article
but the article is also freely available in a repository; an article is Hybrid if there is no such fee on the
publisher’s website to read the article (whether or not the article is also placed in a repository).
Così, we summarized each author’s article production as follows: The sum of Gold and Hybrid
articles is the author’s count of “APC OA articles” and the sum of all Gold, Hybrid, Bronze, E
Green articles is an author’s count of “Total OA articles.”
3. REGRESSION MODEL
Our model is designed to analyze how information describing a scholar (genere, professorial rank,
years since terminal degree, federal research funding) and characteristics describing their institu-
tional employer (public or private university, AAU member institution) are associated with the num-
ber of OA journal articles those scholars author (both APC OA and Total OA). As OA articles
published is a discrete variable and the number of scholars who published zero OA articles in
the 5-year study period shows a high level of zero-inflation in each field (Tavolo 1), an ordinary least
squares regression is inappropriate. General linear models (GLMs) suitable for discrete dependent
variables include the Poisson model and the negative binomial model, but neither is appropriate for
data with substantial zero-inflation. A hurdle model (Mullahy, 1986; Zeileis, Kleiber, & Jackman,
2008), Tuttavia, can account for zero-inflation by framing the model as two components: One
component assumes a binomial probability model governs the binary outcome of whether a count
measurement (in our case, the count of APC OA or Total OA articles) is either zero or greater than
zero, depending on whether a “hurdle” has been overcome; the second component fits a truncated-
at-zero count model for the positive OA article count observations (cioè., those cases for which the
hurdle to publishing at least one OA article has been overcome).
We propose that zero-inflation in the APC OA or total OA article count data reflects a hurdle not
overcome by scholars, related to (UN) a lack of publishing activity overall (scholars with zero total
articles published over our sample’s 5-year period may represent cases where publishing research
articles is not incentivized or is not part of their research dissemination strategy) O (B) a lack of
federal funding supporting one’s research; public research funders increasingly mandate that
grant recipients publish in OA venues so federal support may be a strong predictor of nonzero
OA article counts. We conducted two hurdle models for each of the 11 fields of study, using the
pscl package (Jackman, 2017; Zeileis et al., 2008) in R version 3.6.1 (R Development Core
Team, 2011). The first model predicts APC OA articles authored; the second model predicts total
OA articles authored.
In the zero count component of each model, we used “APC OA articles” or “Total OA articles”
as the dependent variable (interpreted as a binary variable with value “0” for zero APC OA or Total
OA articles and value “1” for greater than zero APC OA or Total OA articles), and the following
independent variables:
1. Gender (female = 0, male = 1)
2. Professorial rank (as of the Fall 2018–Spring 2019 academic year (assistant professor = 1,
associate professor = 2; full professor = 3)
3. Public or private institution (private = 0, public = 1)
4. AAU member institution (not AAU member = 0, AAU member = 1)
5. The total number of articles (combining OA and non-OA) published in the 5-year study
period
6. Years since terminal degree (per esempio., if a scholar earned their Ph.D. In 2008, years since terminal
degree = 2018 − 2008 = 10 years)
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7. A binary “Supported by Federal Funding” indicator (has won a federal research grant in the
5-year period = 1; has not won a federal research grant in the 5-year period = 0); only prin-
ciple investigators on research grants are indicated, other roles (per esempio., key personnel) were not
available from our data source
For the positive count component, we again used “APC OA articles” or “Total OA articles” as the
dependent variable, and the same set of seven independent variables as the zero count component.
To explore dispersion in the regression model, we compared Poisson and negative binomial distri-
butions to the actual OA count frequencies. Following Kleiber and Zeileis (2016), we visualized
both observed and expected frequencies of OA article counts as hanging rootograms
(Supplementary Figure 1; https://osf.io/sb8fq/). In all fields, a negative binomial distribution was a
better fit than a Poisson distribution, and results reported hereafter are from the negative binomial
models.
4. RESULTS
4.1. Descriptive Statistics
We dropped 18,164 (9.3%) cases from the original sample of 200,484 scholars for whom gender
was inferred as “Unknown.” Of the 182,320 unique faculty members in the database with an in-
ferred gender of “female” or “male," 65,294 (35.8%) are inferred to be “female” and 117,026
(64.2%) are inferred to be “male.” The data set contains 84,401 full professors (46.3%), 55,499
associate professors (30.4%), E 42,523 assistant professors (23.3%). The sample included
77,905 scholars at AAU member institutions (42.7%) E 104,611 scholars at non-AAU member
istituzioni (57.3%). Private institutions employ 48,214 of the scholars in our sample (26.4%), while
134,237 scholars are at public institutions (73.6%). Tavolo 2 gives summary information for each of
IL 11 fields. Scholars were each affiliated with one or more of 11,436 university departments or
other academic units, and each academic unit was classified into one or more of the 11 fields of
study. The complete list of academic units and classifications is given as Supplementary Table 1
(https://osf.io/sb8fq/).
Individuals in the study sample authored 1,618,502 journal articles in 25,894 academic jour-
nals between 2014 E 2018 (Supplementary Table 2; https://osf.io/sb8fq). The number of scholars
who authored articles in the 5-year period is given for each field in Table 1. Of the articles authored
by scholars in our study sample, 868,817 are “Closed” (53.7%), 197,791 are Gold OA (12.2%; Tutto
articles in this journal are OA), 253,024 are Green OA (15.6%; the article is available in a repos-
itory, self-archived by the author), 175,248 are Bronze OA (10.8%; the article is free to read on the
publisher’s website but no explicit license is presented), E 123,622 are Hybrid OA (7.6%; indi-
vidual articles within the journal are OA if the authors have paid an APC). The percentages of
authorships by OA classification and by demographic and institutional characteristics of the au-
thor are shown in Figure 1. The percentage of each group’s authorships that are APC OA ranges
from 22% of authorships by women to 29 by scholars at non-AAU member institutions. Scholars at
private institutions author 2% more of their articles in an APC OA venue than those at public in-
stitutions. Scholars at AAU member institutions author 5% more of their articles in APC OA venues
than those at non-AAU member institutions. Men author 6% more of their articles in APC OA
venues than women. Full professors author 3% more of their articles in APC OA venues than either
associate or assistant professors.
IL 11 fields we examined reveal a wide range of adoption of APC OA publishing (Tavolo 1;
Figura 2). Among Humanities and Business scholars, only 10.4% E 13.5% have authored an
APC OA article in the 5-year study period, rispettivamente. The greatest rate of participation in
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Tavolo 2.
Scholar counts by gender, professorial rank, and institution type in each field
Female
scholars
1,394
Male
scholars
3,466
Scholars
at AAU
istituzioni
2,083
Scholars at
non-AAU
istituzioni
2,777
Scholars at
private
istituzioni
146
Scholars at
public
istituzioni
4,714
Assistant
Professors
1,158
Associate
Professors
1,173
Full
Professors
2,529
Agricultural Sciences
Biological and Biomedical
9,937
20,788
14,217
16,508
10,518
20,207
7,166
8,042
15,517
Scienze
Business
Education
Engineering
Family, Consumer and
Human Sciences
3,268
8,496
4,984
3,333
4,755
2,482
7,009
5,835
4,008
18,650
10,977
11,681
6,467
7,142
5,410
8,199
Health Professions Sciences
7,862
5,236
5,366
7,732
Humanities
14,812
19,347
14,896
19,263
Natural Resources and Conservation
1,072
2,841
1,457
2,456
Physical and Mathematical Sciences
6,339
24,076
13,758
16,657
Social and Behavioral Sciences
11,540
16,688
11,569
16,659
3,662
1,449
5,512
2,567
3,340
9,906
472
7,898
7,922
8,102
6,868
17,146
11,042
9,758
24,253
3,441
22,517
20,306
3,115
2,222
5,240
3,722
4,374
6,223
901
6,287
6,413
3,566
3,055
5,719
4,896
5,083
3,040
11,699
4,991
4,046
4,678
13,077
14,859
1,066
7,360
8,770
1,946
16,768
13,045
1
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Who’s writing open access (OA) articles?
Figura 1. Percentage of articles by OA type by institutional characteristics, genere, and professo-
rial rank.
APC OA publishing is found among scholars in Biological and Biomedical Sciences and
Natural Resources and Conservation, among whom 84.4% E 76.1% have authored at least
one APC OA article. In five of the 11 fields, fewer than 50% of scholars have authored an APC
OA article in the previous 5 years. Figura 2 shows the percentage of authorships in each field
by OA type, revealing that even in fields where the rate of participation in APC OA publishing
is high, the proportion of articles published that are APC OA (Gold and Hybrid) never reaches
50%. In Physical and Mathematical Sciences, Per esempio, 65.6% of authors have published
at least one APC OA article in the previous 5 years, but only 43% of articles authored are APC
OA. Likewise, among Agricultural Sciences researchers, 70.0% of scholars have authored an
APC OA article, but only 24.7% of their articles are APC OA.
Figura 2. Percentage of articles by OA type published by scholars in each field.
Quantitative Science Studies
1436
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Who’s writing open access (OA) articles?
4.2. Regression Results—Predicting APC OA Articles
The results of the APC OA hurdle models by field are given in Tables 3, 4, E 5 for both the
truncated positive counts component (predicting the number of APC OA articles authored among
scholars who have authored at least one APC OA article) and the zero count component
(predicting the binary variable “scholar has/has not authored at least one APC OA article.” The
exponentiated coefficients for the truncated positive counts component are displayed in Figure 3.
4.2.1. Zero count component of hurdle model: APC OA articles
In all fields, the total number of articles authored was a positive and significant predictor of having
authored at least one APC OA article, suggesting that increased overall publication activity in-
creases the likelihood of authoring at least some of those articles in Gold and Hybrid OA venues.
For each additional article authored, the likelihood of having authored at least one APC OA article
increases by a factor between 1.12 (Business) E 1.29 (Natural Resources and Conservation).
Securing federal research grants over the 5-year study period was also a positive and significant
predictor of authoring at least one APC OA article in all 11 fields. Most fields show a pronounced
increase in the likelihood of authoring APC OA articles if federal research grants were won, including
two fields in which the likelihood of publishing at least one APC OA article increases by a factor
more than 2.0 if a scholar has won a federal grant (Tables 3–5). AAU membership was a consis-
tently strong predictor of having authored at least one APC OA article; researchers at AAU mem-
ber institutions are significantly more likely to have published at least one APC OA article than
their non-AAU counterparts in five fields. In one field (Engineering), Tuttavia, AAU membership
had a significant negative relationship with having authored at least one APC OA article.
Men are significantly more likely than women to have authored at least one APC OA article in
three fields (Biological and Biomedical Sciences, Education, and Health Professions Sciences), E
women are significantly more likely than men to have authored at least one APC OA article in three
fields (Engineering; Family, Consumer, and Human Sciences; and Natural Resources and
Conservation). Scholars at public institutions are significantly less likely to have authored at least
one APC OA article than their peers at private institutions in three fields (Agricultural Sciences,
Business, and Engineering), but public institution scholars are more likely to have authored at least
one APC OA article than private institution scholars in two fields (Health Professions Sciences and
Social and Behavioral Sciences). Years since degree has a significant negative relationship with
having authored at least one APC OA article in four fields (Biological and Biomedical Sciences,
Business, Engineering, Humanities, and Physical and Mathematical Sciences), and a positive rela-
tionship with having authored at least one APC OA article in one field (Social and Behavioral
Scienze). Increased professorial rank (from assistant professor, to associate professor, to full
professor) has a positive significant relationship with publishing at least one APC OA article
in one field (Humanities) and a significant negative relationship in three fields (Agricultural
Scienze, Engineering, and Social and Behavioral Sciences).
4.2.2. Truncated positive count component of hurdle model: APC OA articles
In every field, federal research grant support and the total count of articles authored were positive
significant predictors of the number of APC OA articles authored (Tables 3–5; Figura 3). Having
won at least one federal research grant results in an expected increase in the number of APC OA
articles authored by a factor of between 1.19 (Health Professions Sciences and Natural Resources
and Conservation) A 1.79 (Business). Each additional article authored increases the likelihood of
authoring an additional APC OA article by a factor of between 1.02 (Biological and Biomedical
Sciences and Physical and Mathematical Sciences) E 1.16 (Humanities). Affiliation with an
AAU institution has a positive significant relationship with the number of APC OA articles authored
Quantitative Science Studies
1437
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Tavolo 3.
(APC OA articles > 0) and the zero count component (APC OA articles = 0)
Regression results from the APC OA hurdle models for Agricultural Sciences, Biological and Biomedical Sciences, Business, and Education, showing the count data component
Agricultural Sciences
Biological &
Biomedical Sci.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Business
e^(cid:1)
Sig.
Std. Err.
(cid:1)
Education
e^(cid:1)
Sig.
Std. Err.
Positive Count Component
Positive Count Component
Positive Count Component
Positive Count Component
1.099
0.040
0.102
***
1.107
0.011
0.058
1.059
0.654
0.285
***
1.329
0.085
0.829
0.091
−0.029
0.971
0.010
0.994
0.036
0.095
***
1.100
0.010
−0.090
−0.022
0.914
0.459
0.978
0.855
−0.035
−0.003
0.965
0.109
0.997
0.089
*
*
Gender is Male
0.094
Institution is Public
Institution is AAU
Member
Years Since Degree
Professorial Rank
−0.187
−0.006
−0.003
−0.005
0.997
0.002
−0.009
0.995
0.032
0.147
Has Won Research
0.314
***
1.368
0.038
0.223
Grants
Total Article Count
0.040
Log((cid:3))
Constant
0.409
0.547
***
***
***
1.041
0.001
1.506
0.054
0.024
1.000
1.728
0.110
0.788
***
***
***
***
***
***
0.991
0.001
0.022
***
1.022
0.001
0.003
1.003
0.006
1.158
0.009
−0.327
1.249
0.010
0.581
**
**
0.721
0.001
−0.040
0.961
0.076
1.788
0.002
0.278
*
1.321
0.109
1.024
0.000
0.087
***
1.091
0.000
0.070
2.718
0.016
2.198
0.019
−4.122
−4.554
0.016
0.387
0.011
4.730
−1.038
−1.745
***
***
***
1.073
0.007
0.354
0.309
0.175
0.306
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Gender is Male
0.039
1.040
0.086
0.116
**
1.123
0.041
Institution is Public
−0.521
*
0.594
0.264
0.023
1.023
0.043
Institution is AAU
0.010
1.010
0.081
0.133
**
1.143
0.041
Member
−0.045
−0.241
−0.004
0.956
0.067
0.168
**
1.183
0.058
***
0.786
0.064
0.095
1.100
0.077
0.996
0.063
0.089
1.093
0.062
Years Since Degree
0.004
1.004
0.005
Professorial Rank
−0.143
*
0.866
0.073
−0.013
−0.005
***
0.987
0.002
0.004
1.004
0.003
0.995
0.034
0.024
1.024
0.054
−0.006
−0.016
0.994
0.004
0.984
0.051
Has Won Research
0.381
***
1.463
0.111
0.723
***
2.060
0.047
1.397
***
4.045
0.134
0.263
**
1.300
0.088
Grants
Total Article Count
0.206
***
1.229
0.008
0.250
Constant
Observations
Log-likelihood
−0.345
4,860
−9,954
0.708
0.292
−0.482
30,725
−75,120
***
***
1.284
0.005
0.113
0.618
0.069
−2.680
11,764
−5,786
***
***
1.119
0.004
0.129
0.069
0.112
−2.062
8,317
−6,228
***
***
1.138
0.005
0.127
0.110
* P < 0.05; ** p < 0.01; *** p < 0.001. 1 4 3 8 W h o s w ’ r i t i n g o p e n a c c e s s ( O A ) a r t i c l e s ? l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u q s s / a r t i c e - p d l f / / / / 1 4 1 4 2 9 1 8 7 1 0 3 2 q s s _ a _ 0 0 0 9 1 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Q u a n t i t a i t i v e S c e n c e S u d e s t i Table 4. data component (APC OA articles > 0) and the zero count component (APC OA articles = 0)
Regression results from the APC OA hurdle models for Engineering, Family, Consumer, and Human Sciences, Health Professions Sciences, and Humanities, showing the count
(cid:1)
Engineering
e^(cid:1)
Sig.
Fam., Cons., & Hum. Sci.
Health Professions Sci.
Std. Err.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Humanities
e^(cid:1)
Sig.
Std. Err.
Positive Count Component
Positive Count Component
Positive Count Component
Positive Count Component
Gender is Male
Institution is Public
−0.005
−0.091
Institution is AAU
0.086
Member
0.995
0.021
0.073
0.913
0.019
−0.081
1.090
0.017
0.085
***
***
Years Since Degree
−0.004
***
0.996
0.001
0.003
Professorial Rank
0.023
1.023
0.015
−0.073
*
*
*
1.076
0.035
0.277
***
1.320
0.023
0.085
1.088
0.078
0.922
0.046
−0.077
**
0.925
0.026
1.088
0.036
0.212
***
1.236
0.024
−0.086
−0.088
0.918
0.083
0.916
0.081
1.003
0.002
−0.004
**
0.996
0.001
0.011
*
1.012
0.005
0.929
0.032
0.019
1.019
0.020
−0.133
0.875
0.071
Has Won Research
0.237
***
1.267
0.017
0.367
***
1.443
0.040
0.173
***
1.189
0.024
0.372
**
1.451
0.121
Grants
Total Article Count
0.029
Log((cid:3))
Constant
0.546
0.396
***
***
***
1.030
0.000
0.033
***
1.034
0.001
1.727
0.027
1.486
0.036
0.102
0.060
1.108
0.061
1.061
0.074
0.030
0.404
0.364
***
***
***
1.031
0.001
0.148
***
1.160
0.011
1.497
0.035
1.439
0.044
−2.951
−3.872
**
0.052
1.010
***
0.021
1.006
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Gender is Male
Institution is Public
Institution is AAU
Member
Years Since Degree
Professorial Rank
−0.149
−0.079
−0.086
−0.008
−0.090
**
0.862
0.046
−0.089
0.915
0.047
0.603
0.924
0.042
0.061
1.063
0.062
0.206
*
0.917
0.036
0.220
***
1.246
0.048
0.336
***
***
***
1.827
0.050
−0.018
0.982
0.040
1.228
0.057
0.002
1.002
0.043
1.399
0.051
0.228
***
1.256
0.040
***
0.992
0.002
**
0.914
0.032
−0.005
−0.049
0.995
0.003
0.000
1.000
0.003
−0.017
***
0.983
0.002
0.952
0.041
−0.034
0.967
0.040
0.099
**
1.104
0.037
Has Won Research
0.469
***
1.598
0.039
0.500
***
1.649
0.081
0.395
***
1.484
0.067
0.464
***
1.591
0.077
Grants
Total Article Count
0.164
Constant
Observations
Log-likelihood
−0.715
22,658
−42,670
***
***
* P < 0.05; ** p < 0.01; *** p < 0.001. 1 4 3 9 1.178 0.003 0.176 0.489 0.071 −2.007 13,609 −15,330 *** *** 1.193 0.004 0.179 0.134 0.088 −1.880 13,098 −24,050 *** *** 1.195 0.004 0.243 0.153 0.079 −2.957 34,159 −12,790 *** *** 1.276 0.005 0.052 0.076 W h o s w ’ r i t i n g o p e n a c c e s s ( O A ) a r t i c l e s ? l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u q s s / a r t i c e - p d l f / / / / 1 4 1 4 2 9 1 8 7 1 0 3 2 q s s _ a _ 0 0 0 9 1 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Q u a n t i t a i t i v e S c e n c e S u d e s t i 1 4 4 0 Table 5. the count data component (APC OA articles > 0) and the zero count component (APC OA articles = 0)
Regression results from the APC OA hurdle models for Natural Resources and Conservation, Physical and Mathematical Sciences, and Social and Behavioral Sciences, showing
Nat. Res. & Conservation
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Phys. & Math. Sci.
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Soc. & Behav. Sci.
Sig.
e^(cid:1)
Std. Err.
Positive Count Component
Positive Count Component
Positive Count Component
Gender is Male
Institution is Public
0.031
−0.035
Institution is AAU
0.038
Member
Years Since Degree
−0.005
**
Professorial Rank
Has Won Research
Grants
Total Article Count
Log((cid:3))
Constant
0.021
0.177
0.036
0.967
0.653
***
***
***
***
1.031
0.966
1.039
0.995
1.021
1.193
1.036
2.631
1.921
Zero Hurdle Component
Gender is Male
−0.208
Institution is Public
0.167
Institution is AAU
Member
Years Since Degree
Professorial Rank
−0.079
−0.002
−0.129
Has Won Research
0.280
*
Grants
Total Article Count
Constant
Observations
Log-likelihood
***
***
0.254
−0.919
3,913
−8,287
* P < 0.05; ** p < 0.01; *** p < 0.001. 0.812 1.182 0.924 0.998 0.879 1.323 1.289 0.399 0.036 0.045 0.032 0.002 0.028 0.032 0.001 0.054 0.070 0.109 0.165 0.106 0.006 0.088 0.123 0.011 0.224 ** *** *** * *** *** *** *** *** 1.072 0.924 1.190 0.997 1.134 1.253 1.018 0.706 1.446 Zero Hurdle Component 0.989 1.052 1.016 *** 0.990 0.992 1.306 1.194 0.385 *** *** *** 0.022 0.021 0.019 0.001 0.016 0.018 0.000 0.027 0.040 0.037 0.035 0.032 0.002 0.027 0.033 0.003 0.060 0.069 −0.079 0.174 −0.003 0.126 0.225 0.018 −0.348 0.368 −0.011 0.050 0.016 −0.010 −0.008 0.267 0.177 −0.953 30,415 −65,540 0.138 *** 1.147 1.044 1.156 1.007 0.855 1.453 1.063 0.521 0.399 *** *** *** *** *** *** *** Zero Hurdle Component 1.045 1.104 1.203 1.003 0.890 1.985 1.152 0.146 ** *** *** *** *** *** 0.043 0.145 0.007 −0.157 0.374 0.061 −0.653 −0.919 0.044 0.099 0.185 0.003 −0.117 0.686 0.141 −1.927 28,228 −32,000 0.032 0.034 0.032 0.002 0.028 0.034 0.002 0.063 0.075 0.030 0.034 0.031 0.002 0.028 0.041 0.002 0.056 W h o s w ’ r i t i n g o p e n a c c e s s ( O A ) a r t i c l e s ? l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u q s s / a r t i c e - p d l f / / / / 1 4 1 4 2 9 1 8 7 1 0 3 2 q s s _ a _ 0 0 0 9 1 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Who’s writing open access (OA) articles? Figure 3. Range of exponentiated coefficients from the positive count component of the APC OA articles hurdle model for each independent variable. Values greater than the vertical reference line at 1.0 represent a greater likelihood of publishing APC OA articles; values less than 1.0 represent a lower likelihood of publishing APC OA articles. Individual dots represent the actual value for each of the 11 fields that constitute the box and whisker summary. The line in the center of each box is the median, the ends of the boxes are the 25th and 75th percentiles, and the whiskers represent the full data range. in six fields, by a factor ranging between 1.09 (Engineering and Family, Consumer, and Human Sciences) and 1.24 (Health Professions Sciences). Scholars affiliated with public universities are expected to author fewer APC OA articles than their peers at private universities in 10 of the 11 fields (Tables 3–5), and this relationship is signif- icant in five of those fields. Agricultural Sciences shows the lowest exponentiated coefficient, with public institution scholars authoring APC OA articles at a factor of 0.83 that of their private institution colleagues. In one field (Social and Behavioral Sciences) scholars at public institutions are expected to author slightly more APC OA articles than their peers at private institutions, although this effect is not significant (Table 5). In 10 of the 11 fields, men author more APC OA articles than women, and this result is significant in seven fields (Tables 3–5). The strongest effect is in Education, where men are expected to author more APC OA articles than women by a factor of 1.33 (Table 3). In one field (Engineering), women are expected to author more APC OA articles then men, although this effect is not significant (Table 4). Years since terminal degree is a positive significant predictor of APC OA articles authored in three fields (Business, Humanities, and Social and Behavioral Sciences), and a negative significant predictor in five fields (Tables 3–5). In four fields, increased professorial rank has a significant negative relationship with APC OA articles authored (Business; Family, Consumer, and Human Sciences; Humanities; and Social and Behavioral Sciences), and in two fields increased rank has a positive relationship with APC OA articles authored (Biological and Biomedical Sciences and Physical and Mathematical Sciences). 4.3. Regression Results—Predicting Total OA Articles The results of the Total OA articles hurdle models by field are given in Tables 6, 7, and 8 for both the truncated positive counts component (predicting the total number of OA articles published among Quantitative Science Studies 1441 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u q s s / a r t i c e - p d l f / / / / 1 4 1 4 2 9 1 8 7 1 0 3 2 q s s _ a _ 0 0 0 9 1 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Q u a n t i t a i t i v e S c e n c e S u d e s t i Table 6. component (Total OA articles > 0) and the zero count component (Total OA articles = 0)
Regression results from the Total OA Articles hurdle models for Agricultural Sciences, Biological and Biomedical Sciences, Business, and Education, showing the count data
Agricultural Sciences
Biological &
Biomedical Sci.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Business
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Education
e^(cid:1)
Sig.
Std. Err.
Positive Count Component
Positive Count Component
Positive Count Component
Positive Count Component
Gender is Male
Institution is Public
0.027
−0.127
1.027
0.028
0.052
0.881
0.068
−0.058
Institution is AAU
0.077
**
1.081
0.026
0.125
Member
Years Since Degree
Professorial Rank
−0.002
−0.003
0.998
0.002
−0.006
0.997
0.023
0.115
Has Won Research
0.323
***
1.381
0.028
0.291
Grants
Total Article Count
0.041
Log((cid:3))
Constant
0.876
1.036
***
***
***
1.042
0.001
2.400
0.039
0.028
1.483
2.818
0.081
1.456
***
***
***
***
***
***
***
***
***
1.054
0.007
0.056
1.058
0.041
0.129
**
1.138
0.046
0.943
0.007
−0.256
1.133
0.007
0.428
0.994
0.000
−0.007
1.121
0.006
0.092
***
***
**
**
0.774
0.038
−0.102
0.903
0.058
1.534
0.039
0.065
1.067
0.048
0.993
0.002
0.003
1.003
0.003
1.096
0.033
−0.052
0.949
0.041
1.337
0.007
0.517
***
1.677
0.071
0.209
***
1.233
0.061
1.028
0.000
4.408
0.012
0.080
0.265
4.290
0.013
−0.616
***
***
***
1.083
0.003
0.089
***
1.093
0.004
1.304
0.071
0.540
0.080
−0.017
−0.526
0.983
0.093
***
0.591
0.104
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Gender is Male
Institution is Public
−0.121
−0.615
0.886
0.115
0.541
0.392
−0.073
−0.019
0.930
0.068
0.981
0.068
−0.020
−0.346
Institution is AAU
0.031
1.031
0.109
0.344
***
1.411
0.068
0.470
Member
Years Since Degree
0.005
1.005
0.007
Professorial Rank
−0.113
0.893
0.095
−0.006
−0.059
0.994
0.003
−0.008
0.942
0.054
0.127
0.980
0.049
0.204
***
1.226
0.055
0.708
0.049
0.031
1.032
0.073
1.600
0.046
0.050
1.052
0.061
0.992
0.003
0.005
1.005
0.003
1.135
0.041
−0.055
0.946
0.048
***
***
**
**
Has Won Research
0.270
1.310
0.171
0.835
***
2.306
0.100
0.985
***
2.678
0.179
0.154
1.167
0.096
Grants
Total Article Count
0.464
***
1.590
0.019
0.858
Constant
Observations
Log-likelihood
−0.339
4,860
−11,950
* P < 0.05; ** p < 0.01; *** p < 0.001. 0.713 0.426 −0.964 30,725 −92,020 1 4 4 2 *** *** 2.360 0.019 0.249 0.382 0.112 −1.652 11,764 −14,420 *** *** 1.282 0.006 0.299 0.192 0.083 −1.784 8,317 −9,984 *** *** 1.349 0.008 0.168 0.104 W h o s w ’ r i t i n g o p e n a c c e s s ( O A ) a r t i c l e s ? l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u q s s / a r t i c e - p d l f / / / / 1 4 1 4 2 9 1 8 7 1 0 3 2 q s s _ a _ 0 0 0 9 1 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Q u a n t i t a i t i v e S c e n c e S u d e s t i Table 7. count data component (Total OA articles > 0) and the zero count component (Total OA articles = 0)
Regression results from the Total OA Articles hurdle models for Engineering, Family, Consumer, and Human Sciences, Health Professions Sciences, and Humanities, showing the
(cid:1)
Engineering
e^(cid:1)
Sig.
Fam., Cons., & Hum. Sci.
Health Professions Sci.
Std. Err.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Humanities
e^(cid:1)
Sig.
Std. Err.
Positive Count Component
Positive Count Component
Positive Count Component
Positive Count Component
Gender is Male
Institution is Public
−0.032
−0.180
Institution is AAU
0.237
Member
Years Since Degree
Professorial Rank
−0.004
−0.015
0.969
0.017
−0.047
0.954
0.025
0.132
0.835
0.015
0.040
1.041
0.033
−0.087
1.267
0.014
0.208
***
1.231
0.025
0.257
***
***
***
***
***
1.141
0.015
0.082
1.085
0.054
0.916
0.016
0.003
1.003
0.058
1.293
0.015
0.098
1.103
0.056
***
0.996
0.001
0.005
**
1.005
0.002
−0.003
***
0.997
0.001
−0.001
0.999
0.003
0.985
0.012
−0.125
Has Won Research
0.333
***
1.395
0.014
0.496
Grants
Total Article Count
0.034
Log((cid:3))
Constant
0.672
1.010
***
***
***
1.034
0.000
1.959
0.019
2.746
0.028
0.048
0.349
0.547
***
***
***
***
***
0.883
0.022
0.040
**
1.041
0.013
0.002
1.002
0.049
1.642
0.030
0.343
***
1.409
0.016
0.390
***
1.476
0.091
1.049
0.001
1.417
0.037
1.728
0.050
0.035
1.071
1.068
***
***
***
1.035
0.000
0.238
2.919
0.023
2.910
0.026
−2.796
−3.974
***
***
***
1.268
0.011
0.061
0.485
0.019
0.507
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Zero Hurdle Component
Gender is Male
Institution is Public
−0.097
−0.183
Institution is AAU
0.232
Member
Years Since Degree
Professorial Rank
−0.014
−0.003
0.908
0.055
0.833
0.050
−0.100
−0.026
1.261
0.043
0.125
*
*
***
***
***
0.987
0.002
0.997
0.038
−0.002
−0.022
0.904
0.050
0.390
***
1.476
0.064
−0.047
0.954
0.033
0.974
0.064
0.059
1.061
0.072
0.008
1.008
0.036
1.133
0.052
0.384
***
1.468
0.068
0.300
***
1.350
0.033
0.998
0.003
0.001
1.001
0.003
−0.012
***
0.988
0.002
0.978
0.044
0.029
1.029
0.048
0.041
1.042
0.031
Has Won Research
0.545
***
1.725
0.050
0.561
***
1.752
0.110
0.674
***
1.962
0.110
0.389
***
1.475
0.072
Grants
Total Article Count
0.263
Constant
Observations
Log-likelihood
−0.540
22,658
−54,880
***
***
* P < 0.05; ** p < 0.01; *** p < 0.001. 1 4 4 3 1.300 0.005 0.359 0.583 0.085 −1.847 13,609 −21,960 *** *** 1.432 0.007 0.438 0.158 0.093 −1.827 13,098 −31,990 *** *** 1.550 0.010 0.428 0.161 0.097 −2.596 34,159 −20,370 *** *** 1.534 0.006 0.075 0.064 W h o s w ’ r i t i n g o p e n a c c e s s ( O A ) a r t i c l e s ? l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u q s s / a r t i c e - p d l f / / / / 1 4 1 4 2 9 1 8 7 1 0 3 2 q s s _ a _ 0 0 0 9 1 p d . / f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Q u a n t i t a i t i v e S c e n c e S u d e s t i Table 8. Regression results from the Total OA Articles hurdle models for Natural Resources and Conservation, Physical and Mathematical Sciences, and Social and Behavioral Sciences, showing the count data component (Total OA articles > 0) and the zero count component (Total OA articles = 0)
Nat. Res. & Conservation
(cid:1)
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Phys. & Math. Sci.
Sig.
e^(cid:1)
Std. Err.
(cid:1)
Soc. & Behav. Sci.
Sig.
e^(cid:1)
Std. Err.
Positive Count Component
Positive Count Component
Positive Count Component
Gender is Male
Institution is Public
Institution is AAU
Member
Years Since Degree
Professorial Rank
Has Won Research
Grants
Total Article Count
Log((cid:3))
Constant
Gender is Male
Institution is Public
Institution is AAU
Member
Years Since Degree
Professorial Rank
0.011
−0.071
0.106
−0.004
0.023
0.235
0.038
1.369
1.141
0.040
0.140
−0.060
−0.009
−0.128
1.011
0.932
1.112
0.996
1.024
1.265
1.039
3.932
3.131
*
***
**
***
***
***
***
Zero Hurdle Component
1.041
1.150
0.942
0.991
0.880
1.504
1.555
0.419
0.026
0.033
0.024
0.001
0.021
0.024
0.001
0.042
0.051
0.139
0.224
0.139
0.007
0.110
0.181
0.021
0.296
**
***
***
***
***
***
***
***
***
1.043
0.906
1.332
0.995
1.103
1.419
1.021
1.232
3.393
Zero Hurdle Component
1.072
0.925
1.474
0.984
1.094
1.533
1.680
0.331
***
***
*
***
***
***
0.015
0.014
0.013
0.001
0.011
0.013
0.000
0.015
0.026
0.052
0.050
0.046
0.002
0.039
0.053
0.009
0.087
0.042
−0.099
0.287
−0.005
0.098
0.350
0.021
0.209
1.222
0.070
−0.078
0.388
−0.016
0.090
0.427
0.519
−1.105
30,415
−87,620
1.017
0.942
1.245
1.003
0.924
1.407
1.066
1.788
1.478
***
***
**
***
***
***
***
***
Zero Hurdle Component
***
***
***
***
***
***
***
1.118
0.870
1.534
0.991
1.000
1.610
1.408
0.230
0.015
0.016
0.015
0.001
0.013
0.017
0.001
0.024
0.029
0.033
0.036
0.033
0.002
0.030
0.055
0.005
0.060
0.016
−0.060
0.219
0.003
−0.079
0.341
0.064
0.581
0.391
0.111
−0.139
0.428
−0.009
0.000
0.476
0.342
−1.469
28,228
−51,720
Has Won Research
0.408
*
Grants
Total Article Count
Constant
Observations
Log-likelihood
***
**
0.442
−0.870
3,913
−9,894
* P < 0.05; ** p < 0.01; *** p < 0.001.
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Who’s writing open access (OA) articles?
scholars who have published at least one OA article) and the zero count component (predicting
the binary variable “scholar has/has not published at least one OA article.” The exponentiated
coefficients for the truncated positive counts component are displayed in Figure 4.
4.3.1. Zero count component of hurdle model: Total OA articles
In all fields, the total number of articles authored was a positive and significant predictor of having
authored at least one OA article, suggesting that increased overall publication activity increases
the likelihood of at least some articles ultimately appearing in OA venues. For each additional
article authored, the likelihood of having authored at least one OA article increases by a factor
between 1.28 (Business) and 2.36 (Biological and Biomedical Sciences) (Tables 3–5). Securing
federal research grants over the 5-year study period was a positive and significant predictor of
authoring at least one article OA article in nine of 11 fields (all except Agricultural Sciences
and Education). Many fields show a marked increase in the likelihood of authoring OA articles
if federal research grants were won, including eight fields in which the likelihood of publishing at
least one OA article increases by a factor more than 1.5 if a scholar has won a federal grant
(Tables 3–5). Likewise, AAU membership was a consistently strong predictor of having published
at least one OA article; researchers at AAU member institutions are more likely to have published
at least one OA article than their non-AAU counterparts in nine fields (Biological and Biomedical
Sciences; Business; Engineering; Family, Consumer and Human Sciences; Health Professions
Sciences; Humanities; Physical and Mathematical Sciences; and Social and Behavioral Sciences).
Men are significantly more likely than women to have authored at least one OA article in three
fields (Education, Health Professions Sciences, and Social and Behavioral Sciences), and women
are significantly more likely than men to have authored at least one OA article in one field (Family,
Consumer, and Human Sciences). Scholars at public institutions are significantly less likely to have
authored at least one OA articles than their peers at private institutions in three fields (Business,
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Figure 4. Range of exponentiated coefficients from the positive count component of the Total OA
articles hurdle model for each independent variable. Values greater than the vertical reference line
at 1.0 represent greater likelihood of publishing OA articles; values less than 1.0 represent lower
likelihood of publishing OA articles. Individual dots represent the actual value for each of the 11
fields that constitute the box and whisker summary. The line in the center of each box is the median,
the ends of boxes are the 25th and 75th percentiles, and the whiskers represent the full data range.
Quantitative Science Studies
1445
Who’s writing open access (OA) articles?
Engineering, and Social and Behavioral Sciences). Years since degree has a significant negative
relationship with having authored at least one OA article in five fields (Business, Engineering,
Humanities, Physical and Mathematical Sciences, and Social and Behavioral Sciences).
Increased professorial rank (from assistant professor, to associate professor, to full professor) has
a positive significant relationship with having authored at least one OA article in two fields
(Business and Physical and Mathematical Sciences).
4.3.2. Truncated positive count component of hurdle model: Total OA articles
In every field, federal research grant support and the total count of articles authored were positive
significant predictors of the number of OA articles published (Tables 6–8 and Figure 4). Having won
at least one federal research grant results in an expected increase in the number of OA articles
authored by a factor of between 1.23 (Education) to 1.68 (Business). Each additional article
authored increases the likelihood of authoring an additional OA article by a factor of between
1.02 (Physical and Mathematical Sciences) and 1.27 (Humanities). A researcher’s affiliation with
an AAU institution also positively predicts the number of OA articles authored in all 11 fields (this
is significant in nine fields) by a factor ranging between 1.08 (Agricultural Sciences) and 1.53
(Business).
Our model shows that scholars affiliated with public universities are expected to author fewer
OA articles than their peers at private universities in seven of the 11 fields (Tables 6–8). Business and
Engineering show the lowest exponentiated coefficient, with public institution scholars authoring
OA articles at a factor of 0.77 and 0.84 that of their private institution colleagues, respectively. In
two disciplines (Family, Consumer, and Human Sciences and Humanities) scholars at public
institutions are expected to author slightly more OA articles than their peers at private institutions,
although this effect is not significant in either case.
In eight of the 11 fields, men author more OA articles than women, and this result is sig-
nificant in four fields (Biological and Biomedical Sciences, Education, Health Professions
Sciences, and Physical and Mathematical Sciences). The strongest effect is in Health
Professions Sciences, where men are expected to author more OA articles than women by
a factor of 1.14 (Table 7). In two fields (Engineering; Family, Consumer, and Human
Sciences), women are expected to publish more OA articles then men, although this effect
is not significant in either field.
Years since terminal degree is a positive significant predictor of OA articles authored in two fields
(Family, Consumer, and Human Sciences; Social and Behavioral Sciences), and a negative signif-
icant predictor in six fields (Tables 6–8). In all 11 fields, the exponentiated coefficient is between
0.99 and 1.01, suggesting an increase or decrease of 0.1 OA article authored for each additional
year since terminal degree (Figure 4). Prediction of OA articles authored by professorial rank shows
a relatively wide range of exponentiated coefficients, from 0.88 (Family, Consumer, and Human
Sciences) to 1.12 (Biological and Biomedical Sciences). In two fields, increased professorial rank
has a significant negative relationship with OA articles authored (Family, Consumer, and Human
Sciences; Social and Behavioral Sciences), and in four fields increased rank has a positive relation-
ship with OA articles authored (Biological and Biomedical Sciences, Business, Health Professions
Sciences, and Physical and Mathematical Sciences).
5. DISCUSSION AND CONCLUSIONS
We found that 46.3% of the articles authored by the research professoriate in the United States over
a 5-year period are OA articles (including all types of OA). This result shows close agreement with
Piwowar et al.’s (2018) estimate based on Unpaywall data (46.7%–47.3%). The two regression
Quantitative Science Studies
1446
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Who’s writing open access (OA) articles?
models we performed for each broad field of study (one predicting APC OA articles authored and
one predicting Total OA article authored) yielded similar results. Both models reveal that federal
research grant support is an especially strong predictor of OA publishing activity, suggesting that
mandates by funding agencies to produce freely accessible research results are prompting greater
levels of OA publishing. Both models also demonstrate that greater overall publishing activity pre-
dicts that at least some of the articles authored will be available as OA articles.
The model predicting APC OA articles published and the model predicting Total OA articles
published differ with respect to the effect of gender on articles authored. In the APC OA model,
we found that male gender predicts greater APC OA article authorship counts in 10 of 11 fields,
including two fields (Education and Health Professions Sciences) where men are expected to author
more than 1.3 times as many APC OA articles as women. The Total OA model also shows that men
are more likely to have authored OA articles overall in most fields, but the factor by which men
author more OA articles than women is lower in the Total OA model than in the APC OA model
(cf. exponentiated coefficients in Figures 3 and 4). The gender gap in overall article output is well
documented (e.g., Ceci et al., 2014), and our results appear to mirror findings about the gender gap
in general: In most fields, men publish more OA articles than women, an effect that grows stronger
when APCs must be paid. Duch et al. (2012) found that access to research resources (including
grant support) and the relative career risks associated with different academic fields drive the gender
gap in publication rates and impact. In their study, career risk for different academic fields was a
function of “factors such as the time T to reach career independence, the fraction A of Ph.D. grad-
uates that go on to careers in academia, and the reciprocal of the salary premium of nonacademic
careers” (Duch et al., 2012, p. 7). Our data cover a different set of fields than Duch et al., precluding
direct comparison using their model of career risk. Nonetheless, it is notable that the fields in our
study with the greatest likelihood of men authoring more APC OA articles than women are
Education, Health Professions Sciences, and Biological and Biomedical Sciences, which represent
a diversity of average times to complete the Ph.D. degree (Bourke, Holbrook, et al., 2004) and offer
several career paths outside the academy.
Our results show that each additional year since terminal degree (a proxy for academic age)
predicts that a scholar will author as much as ±0.01 additional OA article (including APC OA
articles). In STEM fields (Biological and Biomedical Sciences; Physical and Mathematical
Sciences; Engineering), greater years since Ph.D. predicts fewer APC OA articles published, while
in Business, Social and Behavioral Sciences, and Family, Consumer, and Human Sciences greater
academic age predicts more APC OA articles published. The results for STEM fields appear to
contradict the position that OA publishing may be perceived as risky by younger scholars seeking
promotion or tenure (Agrawal, 2014), at least in those fields, suggesting that the perceived risk of
publishing in OA venues may be limited to non-STEM areas, or possibly there is an alternative cause
for field-level differences in the relationship between academic age and APC OA articles published.
Professorial rank also has a mixed relationship with (APC) OA articles published: Greater rank
has a negative relationship with (APC) OA articles authored in some fields and a positive relation-
ship in others. A positive relationship between rank and APC OA articles published was found in
STEM fields (Biological and Biomedical Sciences, Engineering, and Physical and Mathematical
Sciences), while a negative relationship was found in non-STEM fields (Business, Family,
Consumer, and Human Sciences; Humanities; and Social and Behavioral Sciences). In 10 of 11
fields, years since terminal degree and professorial rank have the opposite relationship with APC
OA articles published: In most STEM fields greater rank and fewer years since terminal degree pre-
dict greater APC OA articles, while in many non-STEM fields lesser rank and greater years since
terminal degree predict greater APC OA articles. Taken together, these results may indicate that
scholars who are promoted at a younger academic age are more likely to publish APC OA articles
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Who’s writing open access (OA) articles?
than their equally ranked but older colleagues in STEM fields, with the opposite set of conditions
describing most non-STEM fields. Nonetheless, field-level differences in APC OA publishing should
be considered in future studies on OA publishing behavior and understanding field-level differ-
ences in OA authorship may be a fruitful direction for future research.
Analysis of the relationship between institutional characteristics and (APC) OA articles
authored shows that scholars at AAU member institutions are more likely to author APC OA
articles in most fields, and are more likely to author OA articles overall in every field. Scholars
at private institutions are more likely to author APC OA articles in all but one field, and private
institution scholars are more likely to author OA articles overall in all but two fields. The AAU
(http://www.aau.edu) is an invitation-only group of 65 highly research-active North American
research universities, membership is considered highly prestigious, and scholars at member
institutions demonstrate higher rates of research publication and securing grants (Ali,
Bhattacharyya, & Olejniczak, 2010). Private institutions in the United States are often associated
with greater prestige than their public counterparts, evidenced by the consistently higher rankings
of American private institutions in national and global ranking schema (e.g., US News & World
Report; Times Higher Education). Clauset, Arbesman, and Larremore (2015) found that increased
institutional prestige is related to increased faculty production, and Way, Morgan, et al. (2019)
report that the prestige of a researcher’s place of work, rather than the prestige of the doctoral
program where they trained, has a positive effect on their scholarly productivity. Our data do
not allow direct testing of doctoral program versus current workplace prestige, but our findings
add “(APC) OA article authorships” to a growing list of scholarly productivity indicators that
appear to increase with the prestige of a researcher’s current institution.
Figure 1 reveals substantial field-level disparities in the proportion of APC OA articles
authored by scholars in different fields. Scholars in three STEM fields (Biological and
Biomedical Sciences, Physical and Mathematical Sciences, and Natural Resources and
Conservation) author more than 25% of their articles in an APC OA venue (Gold and Hybrid).
Engineering represents a conspicuous outlier among STEM fields, with only 19% of authorships
occurring in APC OA venues (cf. Piwowar et al., 2018; Figure 4). Engineering falls between the
range of other the other STEM fields and non-STEM fields; for example, Humanities scholars
author only 8.1% of their articles in APC OA venues, and Social and Behavioral Science scholars
author 13.1% of their articles in APC OA venues. In addition to the overarching trends, wherein
men at more resource-rich institutions author more APC OA articles, field-level differences in the
percentage of APC OA authorships must also be taken into account in studies of APC OA adop-
tion and when crafting policies to further democratize the research literature.
The demographic and institutional characteristics we examined show that scholars at more
prestigious universities (AAU members and private institutions), with greater federal research
funding support, and who are willing to absorb greater career risk (men, other than the most
highly qualified women; see discussion by Duch et al., 2012) tend to author more (APC) OA
articles. Rates of participation in OA authorship are also greater in STEM fields, proportional to
the total number of articles published (Figure 2). Among the goals of the rapidly growing OA
movement is to make research results freely available to the public with no restrictions; our results
indicate that the work of one subset of scholars (professors at institutions with greater resource
availability, mainly in STEM fields) is disproportionately represented among this freely available
portion of the literature. It has been suggested that OA articles and articles with greater “discover-
ability” (e.g., those available on websites such as Academia.edu) tend to be more highly cited
than paywalled articles (e.g., Archambault, Côté, et al., 2016; Niyazov, Vogel, et al., 2016).
Considering our results, the citation advantage of OA publishing likely benefits men at more elite
institutions with greater research grant support.
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Who’s writing open access (OA) articles?
The relatively new field of the science of science has provided valuable insights into the role of
institutional prestige in knowledge production (Clauset et al., 2015; Way et al., 2019). As Way
et al. note, research on the science of science sometimes falsely “…assumes, implicitly if not
explicitly, that meritocratic principles or mechanisms govern the production of knowledge,
p. 10733.” The OA publishing model succeeds in democratizing the products of knowledge
producers, but the knowledge producers whose work is published as OA articles are not nec-
essarily representative of the broader research community. The disproportionately larger num-
bers of OA articles from professors at elite institutions represent a challenge to the OA business
model: to increase the representation of scholars at a diversity of institutions backed by varying
levels of research support among the OA literature.
ACKNOWLEDGMENTS
The authors wish to thank R. Berdahl, P. Lange, W. Savage, T. Stapleton, J. Sullivan, G. Walker, R.
Wheeler, and C. Whitacre for valuable conversations and comments on drafts of this manuscript.
AUTHOR CONTRIBUTIONS
Anthony J. Olejniczak: Conceptualization, Data curation, Formal Analysis, Investigation,
Methodology, Project administration, Writing—original draft, Writing—review & editing.
Molly J. Wilson: Conceptualization, Data curation, Investigation, Methodology, Writing—
original draft, Writing—review & editing.
COMPETING INTERESTS
Both authors are employed by Academic Analytics, LLC. Academic Analytics, LLC management
had no oversight or involvement in the project and were not involved in preparation or review of
the manuscript.
FUNDING INFORMATION
Data and computational resources were provided by Academic Analytics, LLC.
DATA AVAILABILITY STATEMENT
The data tables used to perform this study and supplementary materials are available via OSF
(https://osf.io/sb8fq/) and have been assigned a DOI (10.17605/OSF.IO/SB8FQ). Records in the
data set are anonymized to protect the privacy of individual scholars; the full (nonanonymized)
data were offered to the editors and referees.
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