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RESEARCH ARTICLE

Large publishing consortia produce higher
citation impact research but coauthor
contributions are hard to evaluate

Keine offenen Zugänge

Tagebuch

Statistical Cybermetrics Research Group, University of Wolverhampton, Wolverhampton, Vereinigtes Königreich

Mike Thelwall

Schlüsselwörter: scientometrics, collaboration, research consortia, research impact, citation impact,
MNLCS

ABSTRAKT

This paper introduces a simple agglomerative clustering method to identify large publishing
consortia with at least 20 authors and 80% shared authorship between articles. Based on Scopus
journal articles from 1996–2018, under these criteria, nearly all (88%) of the large consortia
published research with citation impact above the world average, with the exceptions being
mainly the newer consortia, for which average citation counts are unreliable. On average,
consortium research had almost double (1.95) the world average citation impact on the log scale
gebraucht (Mean Normalised Log Citation Score). At least partial alphabetical author ordering was
the norm in most consortia. Der 250 largest consortia were for nuclear physics and astronomy,
involving expensive equipment, and for predominantly health-related issues in genomics,
medicine, public health, microbiology and neuropsychology. For the health-related issues, except
for the first and last few authors, authorship seem to primarily indicate contributions to the
shared project infrastructure necessary to gather the raw data. It is impossible for research
evaluators to identify the contributions of individual authors in the huge alphabetical consortia of
physics and astronomy and problematic for the middle and end authors of health-related consortia.
For small-scale evaluations, authorship contribution statements could be used when available.

EINFÜHRUNG

The frequency and scale of academic research collaboration varies within and between fields
but has grown steadily over time (Fortunato et al., 2018). Whilst arts and humanities scholars
often work alone (Larivière et al., 2006; Wuchty et al., 2007), some types of experimental and
applied research require large teams (de Solla Price, 1986). Interdisciplinary collaboration may
be needed to solve complex real-world problems (z.B., Moore et al., 2017; Olds, 2016), in einem
process that has been called mode 2 Wissenschaft (Gibbons et al., 1994). Big teams may also be
needed to operate large-scale equipment, such as the Large Hadron Collider, and collabora-
tion may sometimes be more efficient by combining expertise. Weak or strong collaborations
have also been formed to create specific resources of common value, such as the Human
Genome Project (Roberts, 2001), leading to their landmark paper (International Human
Genome Sequencing Consortium, 2001), epigenomics mapping (Bernstein et al., 2010), Und
gene product function ontologies (Gene Ontology Consortium, 2014). Trotzdem, Forschung
consortia may be formed through policy decisions or in response to research funding require-
gen, which may be less successful (Defazio et al., 2009) or primarily benefit less successful
Partner (Hoekman et al., 2013).

Zitat: Thelwall, M. (2020). Groß
publishing consortia produce higher
citation impact research but coauthor
contributions are hard to evaluate.
Quantitative Science Studies, 1(1),
290–302. https://doi.org/10.1162/
qss_a_00003

DOI:
https://doi.org/10.1162/qss_a_00003

Erhalten: 6 April 2019
Akzeptiert: 5 Juni 2019

Korrespondierender Autor:
Mike Thelwall
m.thelwall@wlv.ac.uk

Handling-Editor:
Ludo Waltman

Urheberrechte ©: © 2019 Mike Thelwall.
Veröffentlicht unter Creative Commons
Namensnennung 4.0 International (CC BY 4.0)
Lizenz.

Die MIT-Presse

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Close collaboration can also occur around data when a discipline collaborates to create
standards and repositories to systematically exchange information (z.B., AACR Project GENIE
Konsortium, 2017; Buniello et al., 2018; Costa et al., 2016; Vermeulen et al., 2013; Welter
et al., 2013). These are problematic to evaluate with scientometric methods because the
primary output of such collaborations is not a set of journal articles.

A more recent reason to collaborate on some types of research is that competing groups
using similar methods to address a shared problem may lead to a situation in which the wrong
answer achieves statistical significance and is published, whereas combining the competing
teams would give the correct result (Ioannidis, 2005; Munafò et al., 2017). This occurred for
Genome-Wide Association Studies (GWAS), Zum Beispiel. In this field, multiple teams at-
tempted to identify single nucleotide polymorphisms (SNPs) on the human genome that are
associated with genetic diseases or health problems. Each team generated its own data set,
typically consisting of hundreds or thousands of human volunteers and genetic information
on a sample of SNPs. Only positive results were published and many negative results were
discarded, which led to incorrect results being published when they accidentally achieved
statistical significance, unless more stringent thresholds were used (Pe’er et al., 2008). A
side-effect was the “winner’s curse,” with the effect of SNPs being overestimated in studies
that found them (Garner, 2007). The solution adopted by the community included pooling
data sets to improve statistical power so that the number of discarded negative results would
be reduced. In this situation the incentive to form consortia was statistical and improved re-
search validity and power (Psaty et al., 2009).

Collaboratively authored journal articles may be valued by their coauthors in research
evaluation exercises because they tend to be more cited than solo articles in many fields, al-
though the citation advantage of collaboration has diminished over time (Larivière et al., 2015).
An advantage of team science is the ability to apply novel combinations of expertise, aber die
research produced is not more novel than less collaborative research in some fields (Wagner
et al., in press). The GWAS example above illustrates that large teams may be needed to make
research more predictable. Author ordering may be a problem in large collaborations, making it
difficult to assess individual scholars’ contributions. Although alphabetical author ordering is
not the norm in any broad field of science (Levitt & Thelwall, 2013; Waltman, 2012), es scheint
unlikely that a large group of authors on a long-term project would be able to precisely deter-
mine relative contributions, and partial or full alphabetical ordering would be a logical solution
to this. A common biomedical solution is to order the main contributors at the start and end of
the author list nonalphabetically, with the remaining authors ordered alphabetically in the mid-
dle (Mongeon et al., 2017).

Despite much evidence about collaboration in general within fields, science-wide, or from
an individual funding program, no previous science-wide study has investigated the prev-
alence of publishing consortia, their impact, or use of alphabetical ordering. This is important
because research evaluation exercises often need to evaluate the contributions of individual
authors or departments, which may be difficult for large collaborative papers. This article uses
a heuristic to identify publishing consortia throughout science from 1996–2018 to investigate
impact and authorship order, and a manual classification of their type for deeper insights into
their contributions to science.

(cid:129) RQ1: Do large publishing consortia produce higher impact research?
(cid:129) RQ2: Does authorship order reflect contributions in large publishing consortia?
(cid:129) RQ3: Which types (fields, reason for existence) of large publishing consortia exist?

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2. METHODEN

Alle 67,608,187 Scopus records of type journal article published between 1996 Und 2018 war
downloaded between November 2018 und Februar 2019. Articles tagged with other catego-
Ries, such as review papers or editorials, were excluded to focus on a standard document type.
The data included the author names, as recorded by Scopus, up to a maximum (usually) von
100. Each author was also assigned a unique ID by Scopus and these IDs were used to com-
pare authors, even though they are likely to be sometimes incorrect, to reduce errors caused
by authors having the same common name. Scopus author IDs are automatically assigned by
an author name disambiguation algorithm that prioritises precision (d.h., attempts to avoid con-
flating different researchers with the same name; Moed & Plume, 2013). Its accuracy seems to
be high, since a study of Japanese-funded authors found it to have precision of 99% (99% von
papers associated with an author ID were correctly assigned) and recall of 98% (98% of an
author’s papers were assigned to their ID; Kawashima & Tomizawa, 2015). Duplicate IDs
occurred in these lists when authors had multiple affiliations, reducing the total number of
unique authors, for articles with large sets. Zum Beispiel, a paper with thousands of authors
would have 100 author IDs in Scopus, with as few as 30 being unique if they had about three
affiliations each. Duplicate IDs were removed before subsequent processing.

Document clustering has previously been used to identify scientific topics (Sjögårde &
Ahlgren, 2018; Waltman et al., 2010) and network mapping has been used to identify collab-
oration patterns (Xie et al., 2016), but the task here is different: to identify groups of articles
created by a mostly common set of authors. A heuristic was used to identify publishing con-
sortia. A set of articles was classified as a large consortium product when all had at least 20
(unique) authors, each article had at least 80% of authors in common with one other article in
the set, and the collection contained at least three articles, building collections through a sim-
ple agglomerative clustering algorithm. These values (80%, 20 Und, less critically, 3) war
chosen after manual inspection of the data with the aim of getting the most generous definition
that included few false consortia (d.h., one that did not self-define as a coherent group). A com-
monality of 80% allows for moderate changes in the composition of a consortium.

The consortium identification method used would be defeated by consortia with hundreds
of authors that substantially changed author name orders, since the number of authors in com-
mon would then be hidden by the Scopus 100 author maximum threshold. No examples were
found of consortia that were split into separate groups because of this, but others may not have
been found. The single linkage agglomeration method allows a consortium to evolve gradu-
ally. Zum Beispiel, a group of authors that maintained a size of over 20 Menschen, published at
least one article every year, and had a personnel changeover rate of under 20% would appear
as a single cluster of papers. This is because an article with, sagen, 20 authors would cluster with
a second if up to four of these authors changed. It would cluster with a third paper with an
overlap of less than 80% if another paper in the cluster had an overlap of at least 80%
(Figur 1).

In partial validation of the method and parameters chosen, most of the consortia identified
had given themselves names and so were formal research groupings. The clustering rules may
still have been too conservative, Jedoch, because there is no evidence about the extent to
which clusters were missed. Insbesondere, research groupings with selective authorship (z.B.,
only contributing authors from a consortium pool) would be omitted.

RQ1: The Mean Normalised Log Citation Score (MNLCS; Thelwall, 2017) was calculated
for each consortium to assess whether it produced research with a citation impact above the
world average. This is a field normalised citation impact indicator that divides the citation

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Figur 1. Three articles with partially overlapping authors clustered into one group. Colours indi-
cate authorship overlaps. Although articles 1 Und 3 have fewer than 80% authors in common, Sie
both have 80% in common with article 2 and so are grouped into a single cluster.

score for each paper by the world average of all papers published in the same field and year.
This avoids advantages for older articles (because they are normalised against contemporary
articles) and for high citation fields (because they are normalised against articles from the same
field). The log transformation ln(1 + C) was applied to all citation counts before any calculation
to reduce the impact of individual highly cited articles so that (A) the data is less skewed and it
is more reasonable to average it with the arithmetic mean and (B) the resulting figure is less
subject to variability (Thelwall & Fairclough, 2017). Most articles were in multiple fields and in
these cases the arithmetic mean of the values for each field was used.

RQ2: Alphabetical ordering of authors is not straightforward to assess, because a consortium
may use partial or full alphabetical ordering (Mongeon et al., 2017) and authors may fall into
alphabetical order by accident. Partial alphabetical ordering can also be a side effect of cul-
tural differences in contributions because, Zum Beispiel, Chinese last names are more likely to
start with Z than American last names. A nonalphabetic systematic ordering may also be used
for articles originally written in languages, such as Chinese, that do not use the Latin alphabet
(but alphabetical ordering from China is rare: Liu & Fang, 2014), and may use radical and
stroke sorting or pronunciation order. Darüber hinaus, consortia may make different decisions about
how to deal with issues such as prefixes (and their capitalisation), hyphenated names, double
last names, accented characters in the extended Latin alphabet, cultures where the second
name is the given name, cultures where the penultimate name is the family name, and whether
to use the full first name(S) or the initials when ordering. Because of these issues, articles in
perfect alphabetical (or equivalent) order according to the rules of a consortium may appear to
be not lexically sorted based on the information available to Scopus or in the original article, In
addition to any transcription errors. A heuristic was therefore used to judge the degree of al-
phabetical ordering. This was designed to be sensitive to partial alphabetical orderings after
observations of this in some consortia. The alphabetical ordering heuristic used was to count
the proportion of consecutive distinct (with different last names and/or first initials) authors that

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were in alphabetical order, according to their last name and first initial, as recorded in Scopus.
Thus a score of 18/19 for an article with 20 authors indicates that the nth author was alpha-
betically before the (N + 1)th author for all consecutive pairs of distinct authors except one. An
average, an article should score 50%, and values that substantially deviate from this indicate a
degree of deliberate alphabetical order. For convenience of analysis, articles were split into
groups based on the extent of alphabetical author ordering: close to alphabetical (90%+);
partial alphabetical (zwischen 60% Und 99%); close to nonalphabetical (aus 40% Zu 60%);
and anti-alphabetic (Below 40%). A large-team biomedical article with an average sized set
(60%) of alphabetically ordered middle authors and half of the remaining authors alphabeti-
cally ordered by accident (Mongeon et al., 2017) should therefore score 80% and fall com-
fortably into the partial alphabetical set. The Scopus limit to 100 author affiliations affects the
accuracy of this for a minority of the consortia. Although the average number of authors for a
consortium article was 38, consortia with over 100 and partial alphabetical ordering might
have this hidden if most of the first 100 authors were in an initial nonalphabetical section,
although this seems unlikely.

RQ3: The largest 250 consortia were examined (all those with at least 17 Papiere) and man-
ually clustered by discipline and consortium type. This clustering was performed by examining
basic properties of the consortium and, from acknowledgments, methods descriptions and
web searches, identifying the scope of the grouping. This was an inductive and iterative pro-
Prozess, with the initial classifications being revisited and subsequently reclassified into a smaller
number of different types. The largest consortium of each type was then singled out for a more
detailed description, based on a brief publication history and, if relevant, web explorations.
Physics and astronomy consortia appeared to be very similar and were ignored after the
first few.

The key data behind the results, including a list of consortia, is on Figshare (https://doi.org/

10.6084/m9.figshare.8214050.v1).

3. ERGEBNISSE
Based on Scopus journal articles from 1996–2018, the largest apparent consortium has 755
articles and 3,927 consortia have at least three articles, totaling 31,340 Papiere. Das ist 0.05%
of the set examined. The largest 250 consortia include between 16 Und 755 articles, account-
ing for 14,135 articles. Daher, large publishing consortia are numerically common in academia
but are very rare overall, at least as defined by the heuristic used here.

3.1. Consortium Size

Consortium size follows a power law, which gives a straight-line shape on a dual logarithmic
scale (Figur 2). There are many small consortia (in terms of the number of papers published)
and few large ones, with no evidence of any size being unusually common. A power law can
be produced if there is a positive feedback mechanism, but it is not clear how such a mech-
anism could operate here.

3.2. RQ1: Consortium Citation Impact

Der 3,927 publishing consortia produced research with an average citation impact of MNLCS
1.954. On the log-normalised scale, this is almost double the impact of the world average
(=1). Because of the (typically) shrinking effect of the log normalisation part of MNLCS, groß
publishing consortia usually publish research with several times more citation impact than the

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Figur 2. Sizes of consortia identified in Scopus publications 1996–2018.

world average, although the exact ratio depends on the average (untransformed) Zitat
counts involved.

The overwhelming majority (87.5%: 3,427) of individual consortia had an MNLCS above
the world average of 1, including the largest 93. The first MNLCS below 1 was for research
from a single department (in den Vereinigten Staaten) rather than a multi-institution consortium. A
Spearman correlation between latest year of the first published article from a consortium
and MNLCS of −0.818 (p = 0.000) confirms that consortia with a lower impact score tend
to be the newer ones for which the MNLCS value is less reliable due to a shorter time to accrue
citations. Tatsächlich, for very recently published articles, most have a normalised impact below the
mean as an artifact of the dominance of zeros, further explaining this result (z.B., to give an
extreme example, if only 1 out of 100 recently published articles had been cited, 99 of them
would have a field and year normalised citation score of 0, which is below the world average
von 1). All the 1,050 consortia with their first articles published before 2006 (for which citation
counts are mature and hence most robust) had an average impact above the world average
(d.h., MNLCS > 1). This is clear statistical evidence that large publishing consortia reliably
produce research with citation impact substantially above the world average.

A tiny positive Spearman correlation between cluster size (number of articles published by
a consortium) and MNLCS of 0.072 (p = 0.000) suggests that the number of articles published
by a consortium has little relationship with the average impact of its research. This may be due
to a variety of conflicting factors, Jedoch, such as consortium age, type and discipline.

3.3. RQ2: Author Alphabetical Order

Although two fifths (38%) of the consortia largely avoid any kind of alphabetical ordering (An
average for their papers), a fifth (22%) are in perfect or close to perfect alphabetical ordering
and two fifths (38%) are in partial alphabetical order (über 60% but less than 90% of consec-
utive different author names being in alphabetical order) (Tisch 1). Counting by paper rather

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Tisch 1. Extent of alphabetical ordering, as judged by the proportion of consecutive pairs of distinct
authors in the author list recorded in Scopus that were in alphabetical order, based on their last
name and first initial. For reference, a long list of random authors would have an alphabetical score
von 50%. For a consortium, the classification is based on the average extent of alphabetical ordering
across all of its papers

Author order
Close to alphabetical: mindestens 90%

Consortia
873 (22%)

Papers
13,622 (43%)

Partial alphabetical: über 60% and below 90%

1,488 (38%)

10,028 (32%)

Close to nonalphabetical: aus 40% Zu 60%

1,546 (39%)

7,623 (24%)

Anti-alphabetic: below 40%

20 (1%)

67 (0%)

Total

3,927

31,340

than by consortium, three quarters of papers in consortia (75%) have at least partial alphabet-
ical ordering (über 60%). This figure is higher than for consortia (60%) because the biggest
consortia are more likely to use alphabetical ordering. The largest 19 consortia all have aver-
age alphabetical ordering rates of at least 84%, mit 16 of them above 90%.

3.4. RQ3: Consortium Types

Eight types of consortia were identified from manual examinations of the papers written by the
largest 250 (Tisch 2). The types are distinguished based on the apparent consortium purpose
and broad field. This typology is one coherent way of differentiating between consortia based
on their apparent purpose, rather than a definitive typology. The largest example of each type
is discussed below. Most of the types of consortia are organised around a specific narrow
task or equipment, although some are subcollections within a department or funded broad
research groups.

3.4.1. Nuclear physics: The ATLAS collaboration

The ATLAS Collaboration at CERN (atlas.cern/discover/collaboration) hatte 755 journal articles
from 2010–2018 in high energy or nuclear physics journals (z.B., Journal of High Energy
Physik: 23%). ATLAS (A Toroidal LHC ApparatuS) at the Large Hadron Collider (LHC) ist ein
large multinational particle detector project using specialised equipment. Its publications
record particle properties, behaviours, or searches (z.B., “Search for lepton-flavor violation in
= 13 TeV with the ATLAS detector”),
different-flavor, high-mass final states in pp collisions at
including for the Higgs boson.

ﬃﬃ
S

The role of the multinational consortium is as a fixed pool of skills to design and run the
experiments. Authorship is in alphabetical order (an average of 98% alphabetical using the
methods above). Although an average of 87 authors are recorded per paper, the collaboration
has hundreds of authors and all are listed on all papers associated with the apparatus during
their project tenure.

3.4.2. Astronomy: The HESS collaboration

The HESS Collaboration (www.mpi-hd.mpg.de/hfm/HESS/pages/collaboration/) is a multina-
tional consortium around a single stereoscopic astronomy telescope system. Es ist 150 publica-
tions from 2004 Zu 2018 record and analyse phenomena observed in space (z.B., “Discovery
of very high energy γ-ray emission from Centaurus A with H.E.S.S.”).

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Tisch 2. Unique combinations of fields and tasks for consortia publishing at least 17 Papiere, with examples of projects

Field
Nuclear physics

Astronomy

Typ

Beispiele (NEIN. of papers)

A series of experiments or data analysis

with equipment for measuring particles,
such as at the Large Hadron Collider

Users of an expensive type of telescope

(z.B., “High Energy Stereoscopic
System” telescopes)

ATLAS Collaboration (755); CLEO Collaboration

(400); D0 Collaboration (349)

HESS Collaboration (150); MAGIC Collaboration

(138); Fermi-LAT Collaboration (136)

Genomics

A shared genomics methods-based generic

GEBA project (148); Joint Center for Structural

Aufgabe (z.B., Genomic Encyclopedia of Bacteria
and Archaea project with two research groups;
Und, “a semiautomated high-throughput
pipeline at the Joint Center for Structural
Genomics”) or a disease-based task

Genomics (85); Consortium on the Genetics of
Schizophrenia (27); OCD Collaborative
Genetics Study (25); IMAGE project (21);
Cancer Genome Atlas Research Network (19)

Medicine

Registry or longitudinal cohort study for disease,

Swiss HIV Cohort Study (120); CONFIRM

based upon large collaboration at multiple sites
(z.B., “Swiss [] outpatient clinics [] HIV patients”)

registry (52); Systemic Lupus [] cohort (32);
UNS. Extrahepatic Biliary Malignancy
Konsortium (26); Canadian Scleroderma
Research Group (20); Chronic Total Occlusion
Multicenter U.S. Registry (19); IDACO Investigators
(19); EUROCARE Working Group (18)

Microbiology

Long-term monitoring of antimicrobial

CHINET (52); Canadian Nosocomial Infection

resistance or infection rates

Surveillance Program (19)

Medicine

Departmental research

Public health

Collaborative cohort-based project to
investigate public health issues
(z.B., healthy eating, Altern, cancer risk factors)

Neuro-psychology

Funded project with shared broad goal (z.B., finden

how “biological, psychologisch, and environmental
factors during adolescence may influence brain
development and mental health”)

Department of Orthopaedic Surgery, Chiba
Universität (46); Division of Hematology,
Mayo Clinic (33); Division of Hematology,
Jichi Medical University (32)

JACC Study (43); JPHC Study Group (33);
Food4Me (27); EMAS study group (26);
European Male Ageing Study (20); Global
Network for Women’s and Children’s
Health Research (19)

IMAGEN Consortium (24)

The role of the multinational consortium seems to be again a fixed pool of skills to design
and run the experiments. Authorship is always in alphabetical order (an average of 95%
alphabetical using the methods above), with an average of 92 recorded in Scopus but all
articles having hundreds of authors.

3.4.3. Shared genomics task: GEBA project

The Genomic Encyclopedia of Bacteria and Archaea (GEBA) project is a joint initiative by the
Leibniz-Institute DSMZ–German Collection of Microorganisms and Cell Cultures and the U.S.
Department of Energy (DOE) Joint Genome Institute (JGI) to systematically select and sequence

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bacterial and archaeal genomes (Wu et al., 2009). Es ist 148 Scopus publications from 2009–
2015 identified for the cluster had an average of 35 authors, with orders varying substantially
between articles. All except one were published in the Springer environmental biology journal
Standards in Genomic Sciences and reported a complete, or near complete, genome for bac-
teria or archaea. It has sequenced 250 bacteria and archaea genomes (jgi.doe.gov/our-science/
science-programs/microbial-genomics/phylogenetic-diversity), so the cluster is an incomplete
record of its activities. Most of its articles had titles starting with “Complete genome sequence
of” (125) or “Genome sequence of” (14). Zum Beispiel, one article was a short report that sum-
marised key properties of the genome of an orange seawater bacterium, as well as reporting
that the complete sequence had been recorded in GenBank, with wider project results in the
Genomes OnLine Database (Riedel et al., 2012).

The role of the consortium is presumably to combine the multiple types of equipment and
other expertise needed to efficiently sequence and analyse genomes. Since author orders and
numbers vary (although a standard list is sometimes at the end (z.B., Bristow; Eisen; Markowitz;
Hugenholtz; Kyrpides; Klenk) the set seems to reflect the relative contributions of the partici-
Hose. Paper authors are, on average, In 49% alphabetical order using the methods above,
confirming that this is not used.

3.4.4. Medical cohort for a disease: Swiss HIV cohort study

The Swiss HIV Cohort Study (SHCS) has been from 1998 “a systematic longitudinal study en-
rolling HIV-infected individuals in Switzerland” (www.shcs.ch), gathered from multiple hospi-
tals and clinics. It includes the Swiss Mother and Child HIV Cohort Study (MoCHiV). Der
120 papers in the cluster were from 2000–2018, had an average of 57 authors and were pub-
lished in many different journals, with the most common being AIDS (13%) and Journal of
Infectious Diseases (12%). The publications seem to cover a wide range of HIV-related re-
suchen, and appear in many journals. There is no typical paper for the consortium. As an ex-
reichlich, one paper reports a type of cancer risk for patients (Clifford et al., 2008).

The role of the consortium is presumably to collect and manage information on the study.
Author order varies by paper. The first few authors are typically not in alphabetical order, Aber
the remainder are (an average of 85% alphabetical using the methods above). Daher, jede
paper seems to have a small group of main authors: perhaps those that planned the study,
conducted the analysis and wrote the paper, with the remaining authors perhaps awarded
coauthorship for contributions to data collection and management.

3.4.5. Microbiology: Antimicrobial resistance in China

The China Antimicrobial Surveillance Network (CNINET) originates from 2005 and is an ongo-
ing surveillance program in China for antimicrobial resistance (including antibiotic resistance).
Its sister program, the China Antimicrobial Resistance Surveillance System (CARSS), focuses on
regional comparisons (Hu et al., 2018) but did not appear as a consortium in the Scopus data.
Only one other consortium of this type appeared in this data, from Canada, despite similar
international data collection exercises (World Health Organization, 2017). CNINET’s 52
Scopus publications were almost all (51) published in the Chinese Journal of Infection and
Chemotherapy from 2008–2017 had an average of 32 authors. The publications describe re-
sistance associated with one genus, such as “CHINET 2009 surveillance of antibiotic resis-
tance in enterococcus in China.” This focuses on a genus of lactic acid bacteria related to
human medical conditions such as urinary tract infections and meningitis. Its data was from
14 hospitals in China. There are also generic surveillance papers, wie zum Beispiel, “CHINET 2008

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surveillance of bacterial resistance in China.” The value of a long-term coherent consortium
for this task is presumably in standardising methods for reliable comparisons over time
(Hu et al., 2016), as well as general efficiency gains.

The role of the consortium is presumably to manage access to data or testing at the different
sites, because the authors have multiple hospital affiliations. Author order varies between pa-
pers, except for the general surveillance papers. Zum Beispiel, the first 13 authors were the
same and in the same order for the 2008 Und 2009 general surveillance papers. Authors are
in an average of 50% alphabetical order (d.h., exactly that expected if alphabetical consider-
ations are ignored) using the methods above.

3.4.6. Medical department research: Orthopaedic surgery at Chiba University

The Department of Orthopaedic Surgery at Chiba University Hospital in Japan had a cluster of
46 papers from Scopus 2009–2017, mainly published in spine-related journals, such as Spine
(37%) and European Spine Journal (20%), with an average of 22 authors. Its research includes
both spinal and joint injuries and it seems to be a highly successful award-winning research
Gruppe (www.ho.chiba-u.ac.jp/en/dpt/orthopaedic.html). The main author of many papers,
Professor Seiji Ohtori, had two records in Scopus that accounted for 391 publications
(Author ID: 7004456445, 197 publications 2009–2014; ID: 56008400700, 194 publications
2012–2019).

The cluster is a department rather than a consortium. Most papers include only authors
within the department. Authors are not in alphabetical order (average: 52%). Author order
varied between papers, although often with the same first author and similar sequences of last
authors and two of the three professors (as listed in the department website in 2019) listed last
except in four cases. Papers by the department not included in the cluster had fewer authors
(z.B., 6: “Segmental Pedicle Screw Instrumentation and Fusion Only to L5 in the Surgical
Treatment of Flaccid Neuromuscular Scoliosis”), or a smaller overlap than 80% due to a col-
laboration (z.B., 22 authors, but several were from other universities, “Use of Bioelectrical
Impedance Analysis for the Measurement of Appendicular Skeletal Muscle Mass/Whole Fat
Mass and Its Relevance in Assessing Osteoporosis among Patients with Low Back Pain: A
Comparative Analysis Using Dual X-ray Absorptiometry”). Daher, the cluster of 46 articles rep-
resents under a quarter of the output of the department: a highly collaborative ad hoc subset.

3.4.7. Public health risk factors: The JACC study

The JACC Study (Japan Collaborative Cohort Study for Evaluation of Cancer Risk) enthalten 46
papers published from 2002–2008, mainly in the Journal of Epidemiology (72%), mostly ex-
amining specific risk factors for a type of cancer (z.B., “Smoking, alcohol drinking and esoph-
ageal cancer: Findings from the JACC Study”). This study gave a lifestyle questionnaire to
73,424 people from 1988–1990 and tracked their health problems until the end of 1997
(Iso et al., 2002). This provided a rich data source to investigate the relationship between life-
style factors, diseases and mortality.

The cluster is a named consortium from different universities, hospitals and health centers
created around a shared, funded task. Authors are not in alphabetic order (47% of distinct author
pairs in alphabetical order). Authorship presumably reflects contributions to leading the exten-
sive shared data gathering task for the initial questionnaires or the follow-up health outcomes
Information. An average of 40 authors (min: 34; max: 50) wrote each paper, with varying author
Befehl (no more than four papers with the same first author), although the last-listed about 10

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authors tended to be in a similar order. Daher, authorship seems to reflect roles in the data col-
lection process, with the first authors presumably carrying out the analysis for a paper.

3.4.8. Neuropsychology: The IMAGEN consortium

The IMAGEN Study is a consortium funded by a series of EU, national and other grants to
follow a cohort of 2,000 young Europeans from the age of 14 to track adolescent brain devel-
opment through questionnaires, brain imaging and tests (imagen-europe.com). Its publications
from 2011–2016 cover different aspects of behaviour and brain development (z.B., “No differ-
ences in ventral striatum responsivity between adolescents with a positive family history of
alcoholism and controls”), with an average of 26 authors per article.

The cluster contains about a quarter of the articles from the project, since its website reports
104 journal articles from 2010–2018. Author order is typically alphabetical in the middle but
not at the start (presumably the main authors for the study) and end (presumably consortium
Führer). There is an average of 77% alphabetical ordering using the methods above. Die Rolle
of the consortium seems to be partly to maintain and update core information about the cohort
and partly to get additional information for specific analyses.

4. DISCUSSION AND CONCLUSIONS

This paper introduces a new method to identify large publishing consortia as well as evidence of
their research impact, use of alphabetical ordering, and broad types. The results show that there
are large publishing consortia in nuclear physics, astronomy, and some health-related fields. Der
heuristics used to identify these consortia cannot be used to estimate the prevalence of large stable
research groups because others may have different publishing agreements or may produce other
types of output. Thus the 0.05% of Scopus articles included in them underestimate the extent of
large publishing consortium output. The highest profile huge research collaboration in the last 50
Jahre, the Human Genome Project, was not included because of this. Zusätzlich, modifications to
the heuristics (z.B., 70% authors in common; minimum 10 authors per paper) would produce
different results. Trotzdem, the existence of publishing consortia of many types is confirmed
by the examinations above of individual groups that found them all to be named and clearly iden-
tifiable entities, or at least collections of papers within departments or research groups.

Whilst the physics consortia seem to have been formed because of the expense and per-
haps complexity of the equipment required for specific tasks, the health-related consortia
mainly reflect the need to systematically gather large quantities of diverse high-quality
human-related (life-related in the remaining cases) data to have sufficient statistical power
or variety to investigate a health issue. As with the GWAS case discussed above, some health
issues cannot be resolved on a small scale or may give statistically misleading answers from
repeated small-scale experiments, so combining data is essential for progress.

The publishing consortia found have research impact that tends to be substantially, Und
almost universally, above the world average for the fields and years in which they published.
This may be due to the consortia typically involving economically advanced nations (z.B.,
Sud & Thelwall, 2016) or the increased likelihood to attract self-citations (Bornmann, 2017;
van Raan, 1998) from the large teams but, from the example examined, it seems more likely
that these teams produce research that is valuable to their disciplines, justifying the human and
financial resources that seem to have been invested in many of them. Trotzdem, the results
exclude all consortia that did not create at least three Scopus-indexed consortia and might (Wenn
they had no other goals) be characterised as failing, so the conclusions should not be extrap-
olated to nonpublishing consortia.

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From a scientometric perspective, to evaluate the impact of the work of individual aca-
demics or departments from their citations it is useful to be able to attribute an appropriate
share of an output to its contributors. This is complicated by publishing collaborations, espe-
cially if partial or full alphabetical ordering is used. Zum Beispiel, if five different groups might
have produced five competing analyses of a single medical issue (z.B., whether green tea af-
fects cancer risks) but instead publish one more powerful combined study, then four fewer
papers would be published and the combined paper would have many authors. Presumably
economies of scale would apply (z.B., one analysis instead of five; one study design instead of
five), so that the total amount of work for the combined paper would be less than five times the
amount for any individual paper. Whilst the efficiency and power improvements are good for
Wissenschaft, a scientometric attempt to share credit for a single paper (z.B., with fractional author
counting) would be unfair in this context. Umgekehrt, for a publishing consortium that rewards
participants that manage data gathering but are otherwise not active, it might be reasonable to
assign fractional value (Hagen, 2013) to the less active participants. For the previously noted
biomedical phenomenon of middle author alphabetical ordering (Mongeon et al., 2017), Die
middle authors (if accurately identified) could potentially be awarded equal but lesser credit to
the remaining authors. Daher, a scientometric exercise would need to make a reasoned judge-
ment about how to deal with contributions from large publishing consortia. For health-related
consortia, it seems to be an ethical necessity to ensure that participation in collaborations that
aid public health should not be discouraged by under-rewarding participants, so evaluators
should be extremely careful when considering this option.

COMPETING INTERESTS

The author has no competing interests.

FUNDING INFORMATION

No funding has been received.

DATA AVAILABILITY

The key data behind the results, including a list of consortia, is on Figshare (https://doi.org/
10.6084/m9.figshare.8214050).

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