RESEARCH ARTICLE - IA de Investigación especializada en el MIT

ARTÍCULO DE INVESTIGACIÓN

A converging global research system

Jonathan Adams1,2

and Martin Szomszor3

1Institute for Scientific Information, Clarivate Analytics, Londres, Reino Unido
2Policy Institute, King’s College London, Londres, Reino Unido
3Electric Data Solutions Ltd., Londres, Reino Unido

un acceso abierto

diario

Palabras clave: citation impact, colaboración, convergence, global network, research policy

Citación: Adams, J., & Szomszor, METRO.
(2022). A converging global research
sistema. Estudios de ciencias cuantitativas,
3(3), 715–731. https://doi.org/10.1162
/qss_a_00208

DOI:
https://doi.org/10.1162/qss_a_00208

Revisión por pares:
https://publons.com/publon/10.1162
/qss_a_00208

Supporting Information:
https://doi.org/10.1162/qss_a_00208

Recibió: 14 Junio 2022
Aceptado: 30 Julio 2022

Autor correspondiente:
Jonathan Adams
jonathan.adams@kcl.ac.uk

ABSTRACTO

We examine the hypothesis that research collaboration has enabled a global research network
to evolve, with self-organizing properties transcending national research policy. We examine
research output, bilateral and multilateral collaboration, subject diversity, and citation impact
encima 40 años, in detail for the G7 and BRICK groups of countries and in summary for 26 otro
naciones. We find that the rise in national output was strongly associated with bilateral
collaboration until the 2000s but after that by multilateral partnerships, with the shift
happening at much the same time across countries. There was a general increase in research
subject diversity, with evenness across subjects converging on a similar index value for many
countries. Similar diversity is not the same as actual similarity but, En realidad, the G7 countries
became increasingly similar. National average citation impact (CNCI) rose and groups
converged on similar impact values. The impact of the largest economies is above world
promedio, which is a phenomenon we discuss separately. The similarities in patterns and timing
occur across countries despite variance in their research policies, such as research assessment.
We suggest that the key agent facilitating global network self-organization is a shared concept
of best practice in research.

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INTRODUCCIÓN

Research is increasingly collaborative. For many large research economies, international col-
laboration now accounts for more academic publications than purely national (doméstico) afuera-
put. In this paper we discuss whether the effect of increasing overlap and commonality
between leading research entities becomes a self-organizing force that drives convergence
in the global research system and acts systemically, irrespective of local policy and manage-
ment structures.

Precio (1963, 1965) described “the world network of scientific papers” and the conventions
of citation referencing that underpinned universal aspects of the global research system. Esto es
linked to the concept of an “invisible college” in research such that the development of ideas
is influenced by the structure in which it takes place (Crane, 1972). The idea that a global
research network might have self-organizing properties has also been suggested before, en
the context of collaboration (Wagner & Leydesdorff, 2005), and it has been argued that
changes in patterns of international collaboration have taken research into a Fourth Age, a
global network in which nations must engage but cannot own the outcomes, because the lead-
ing edge of impactful activity and innovative discovery has gone beyond national boundaries
(Adams, 2013; Wagner, 2018).

Derechos de autor: © 2022 Jonathan Adams
and Martin Szomszor. Published under
a Creative Commons Attribution 4.0
Internacional (CC POR 4.0) licencia.

La prensa del MIT

A converging global research system

Wagner and Leydesdorff (2005) discussed whether preferential attachment (more con-
nected network nodes are more likely to receive new links: see Albert & Barrabás, 2002; Precio,
1965) might be the model for a structuring mechanism in scientific collaboration. This would
facilitate the emergence of a self-organizing system where the selection of a partner and the
location of the research rely upon choices made by the researchers themselves rather than
national or institutional incentives or constraints.

What functionally would we mean by self-organization in the context of a global research
system and what further evidence might there be of this? The “invisible college” implies that
conventions in research practice cross other boundaries, such as national borders and—to
some extent—disciplinary frontiers. The latter is more nuanced because some disciplinary dif-
ferences are evident: Scientists publish primarily in journals, conference proceedings are
widely used by technologists, and monographs are preferred among the humanities. Nonethe-
menos, what we expect to see is a shared though largely unconscious pattern of behavior. Esto es
the evolution of good research practice, long established and nurtured by leaders in each field
as they train succeeding generations, creating a consensus as new communities join the global
endeavor, leading to convergence.

The best (sensu more esteemed within their disciplinary networks) researchers would seek
to work with one another. This connection might initially be local but improved communica-
tion would facilitate links over increasing distance (“the republic of creative minds: Each giant
calling to another through the desolate intervals”: Nietzsche, 1873/1996) promoting interna-
tional collaboration, subsequently emulated by the wider community.

We suggest two lines of inquiry to seek for evidence of this. Primero, in addition to the relative
volume of international collaboration, what other trends in research publication can be seen
and how similar are such trends in different countries? Segundo, noting the degree to which
governmental intervention through policy and funding has become a major locally organizing
influence on research, to what extent do national policy and practice differentiate the timing
and direction of national responses?

The socioeconomic context for this analysis is important because we will argue that global
societal shifts are central to the changes we have observed rather than the local and national
research policy environment. The speed and efficiency of communication are key factors.
Prior to the 1980s travel was relatively expensive and communication was either slow (por
letter) or costly (by phone). Por ejemplo, the data for the global economic models of that time
were moved in boxes of punch cards between Boston, Cambridge (Reino Unido), and Paris (Adams,
2017). The research world of the 1980s was G8 centric and relatively stable from year to year,
and its published medium was the lingua-Americana of the then dominant transatlantic
research axis. Some of the best research output from Germany, Francia, and the Soviet Union
was unavailable in English (Van Leeuwen, Moed et al., 2001) and the BRICK research econ-
omies were only just emerging (note that we use BRICK rather than BRIC because in addition
to Brazil, Russia, India, and China we focus on South Korea).

The settled research world of 1980 was dominated by the G7 group of large economies
(United States, Canada, Reino Unido, Francia, Alemania, Italia, Japón), which authored over
60% of the papers indexed in the Web of Science in the 1980s. The Soviet Union separately
authored somewhat more than 5% of output recorded in Anglophone journals and perhaps as
much again in Russophone journals.

Through the 1990s, more people started traveling to more conferences; information in new
digital forms became available and transferable; and the appearance of the Internet enabled

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A converging global research system

rapid, low-cost communication. Research investment spread to more countries and informed,
quantitative research performance analyses increased the confidence of governments that
public-sector research would be a key investment in securing economic competitiveness
through a highly trained workforce and technological innovation. Countries that previously
had little research presence expanded and developed their research bases. As communication
became faster, and access to literature became global, researchers in many countries shifted
their best work into Anglophone journals to gain visibility. Two other changes influenced the
evolution of global research networks: One was the transition in Europe marked in November
1989 by the fall of the Berlin Wall; the other was the exponential rise in the research status of
Porcelana.

The global growth of research investment created an opportunity for new partnerships to
develop. The US-EU axis consequently became less dominant and, desde 2017, the G7 have
collectively produced less than half (acerca de 42% en 2020) of a globally expanding indexed vol-
ume of research articles and reviews that had grown fivefold in 40 años. The Soviet Union’s
5% share of world output in the 1980s fell markedly and did not expand after 1990; Russian
researchers now author only around 2.5% of indexed journal papers. Porcelana, sin embargo, grew its
published research output (excluding strictly Chinese language journals) from less than 1%
prior to 1990 to an astonishing 25% of indexed global output in 2020, challenging the
long-held scientific leadership of the United States (Johnson, Adams, & Grant, 2021; Johnson,
Adams et al., 2022).

Changes in patterns within Europe also reflect the evolving philosophy of collaboration.
Hoekman, Frenken, and Tijssen (2010) showed that proximity had become a more important
determining factor in collaborative research than shared nationality for 33 countries and 313
regions within the EU. Wagner, Parque, and Leydesdorff (2015) examined research interconnec-
tions across the globe over two decades and showed that while the global network has grown
denser, it has not become more clustered, meaning the increased intensity of connections are
not grouping into exclusive “cliques.” This reflects the increasingly “open” nature of funda-
mental scientific research and contributes to the spread of the “invisible college.”

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In this paper we look across countries (38 en total, 12 in detail) by drawing on analyses that
consider the extent to which national changes in research publication patterns were local or
general. We suggest that the relevant test is whether there is synchronicity across countries and
regions or whether distinct phases can be seen corresponding, Por ejemplo, to the adoption of
national research assessment. The conclusions from this address another key question raised
by Wagner et al. (2015): the balance in roles between the policy initiatives of nations and the
self-organization of researchers who are globally networked.

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2. MÉTODOS

The analysis covers the period from 1981 a 2018, thus including years prior to the appear-
ance of the Internet. It refers solely to research articles and reviews (which are deemed to be
substantive and original academic papers) published in the approximately 20,000 journals
indexed in Clarivate’s Web of ScienceTM and for which the available publication data are
comprehensive and consistently indexed.

These publication data were sourced for 38 relatively prolific research economies covering
a broad geographical spread and including the G7 and BRICK groups of countries (Mesa 1).
The selected countries accounted for 35,666,890 (92%) del 38.8 million papers indexed in
the database over the period (rising from 87% en 1981 a 95% en 2018).

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Mesa 1. Countries covered in the analysis. Two groups (G7 and BRICKs, covering 12 countries)
are illustrated graphically in the body of the paper. Data for the other 26 countries are shown
graphically as Supplementary information. Analytical commentary covers all countries

Data in the core paper

Data in the appendixes

G7
Canada

Francia

Alemania

Italia

Japón

Reino Unido

United States

BRICKs

Brasil

Porcelana

India

Russia

South Korea

EU (otro)
Austria

Bélgica

Dinamarca

Finland

Greece

Hungary

Irlanda

Global (otro)
Argentina

Australia

Egypt

Indonesia

Iran

Israel

México

Países Bajos

New Zealand

Norway

Poland

Portugal

España

Suecia

Saudi Arabia

Singapur

South Africa

Suiza

Taiwán

Assignment to country was based on author addresses and whole counting of papers was
usado, where each paper is assigned once to each country given in an author affiliation. Nosotros
recognize that there are sound arguments in favor of fractional partitioning of output and
impacto (waltman & van Eck, 2015; Potter, Szomszor, & Adams, 2020), although these take
interpretation away from the raw, source data, and we will address an alternative approach
on these lines in a separate analysis.

Each country’s indexed papers were counted in total and then deconstructed by collabora-
tion mode: doméstico, with no international coauthor; bilateral, with at least one coauthor from
just one additional country; and multilateral, with two or more coauthoring countries (see also
Potter et al., 2020). Papers were counted and analyzed separately by collaboration mode.

The diversity of national output was indexed by

(cid:129) collating each country’s spread of papers across the 254 Web of Science subject-based

journal categories, including null counts;

(cid:129) normalizing these counts against the world average for year and category to account for

global variation in category size and content; y

(cid:129) calculating a Gini index of evenness (Gini actually indexes disparity so the index of

diversity is shown as (1 − Gini)).

The methodology follows Egghe and Rousseau (1990) and Moed (2006) and has previously
been described in detail in a paper that summarized part of these results for 11 of the countries
(Adams, Rogers et al., 2020).

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A converging global research system

The annual average Category Normalized Citation Index (CNCI) was calculated for all
countries. The citation count of each paper was normalized against the world average for
its relevant document type, journal category, and publication year. As noted, whole counting
was used throughout and no fractional attribution was applied. It has long been known that
internationally coauthored papers have a higher average citation count than comparable
domestic papers (Narin, stevens, & Whitlow, 1991). There is thus an interaction between
collaboration and indexed citation impact.

The principal illustrations that follow focus on the G7 and the BRICKs (see the caption to
Mesa 1) to provide informative contrasts while avoiding the confusion of too many similar,
overlapping, and cross-cutting graph lines.

Supplementary graphics including the other countries are shown in the appendixes and
reference is made to these in discussion. Note that the graphics in the Supplementary
information have been simplified to “gray out” the lines for countries other than the G7 and
BRICK groups, as a color palette for 38 lines is problematic.

3. RESULTADOS

3.1. Publication Volume

Over the 38 years from 1981 a 2018 there was a four- to fivefold net global growth in the
indexed number of research papers. The total annual number of papers indexed in the Web of
Science was about 465,000 en 1981 and over 2.15 million in 2018. Some of that increase was
an expansion in journal size (more papers) and some was due to additional journal titles. Este
commercial investment in journal indexing was a response to the output of academic material
of sufficient quality.

Overall publication output increased for almost all countries in this study throughout the
period from 1981 and it appeared to do so at a similar rate, with some indication of an
acceleration for the already relatively productive G7 from the early 1990s. A widely rec-
ognized exception was that of China, but much of that country’s accelerated publication
“growth” can be explained by a shift from a powerful R&D demand system underpinning
domestic industry into a responsive, public-facing research base. Russia’s output, por estafa-
contraste, reflects the signs of a traumatic post-Soviet shift in resources for academia and
research institutes. India’s research output was much slower until 2000, while Japan’s out-
put appears to have slowed since 2000. By the end of the period, the BRICK economies
were generally catching up with G7 growth rates, while China was forging ahead
(Cifra 1).

As noted in Section 2, a graph of data for all 39 countries could be a mass of lines, pero en
fact a common trend across national data broadly appears because few lines actually cross,
which implies that the growth rate of most countries followed a similar pattern (ver
Supplementary information). Outside the G7 and BRICK groups, Iran had a notably steep rise
until 2010, when its “growth” rate slowed to that of other countries of a similar size, y esto
may be a further indication of a well-established research base shifting its output into Anglo-
phone journals.

Gross national output is composed of both domestic papers (with no international coau-
thors) and papers produced through international collaboration. The next section explores
how much of each country’s apparent growth was by an increase in domestic capacity and
how much by collaboration.

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A converging global research system

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Cifra 1. Total annual papers published in journals indexed in the Web of Science for G7 (solid line) and BRICK (dotted line) countries.
Output is shown on a logarithmic scale. Output appears to have risen at similar rates for all countries except Russia and China. The country
sequence in the key is ordered by output in 2018. Data for additional countries is available as Supplementary information.

3.2.

International Collaboration

International research coauthorship in the 1980s was limited (5–10% for most medium and
large countries) and was mostly bilateral (Adams, 2013). The data analyzed here indicate that
this pattern started to change in the 1990s and that partnerships began to transform into net-
obras. The evidence for this, within increased national publication capacity (Cifra 1), is that
después 2005 bilateral collaboration grew as an absolute count of papers but not relative to total
producción, while multilateral collaboration continued to expand in relative terms. These shifts
occurred at similar times across multiple countries.

The counts for the bilateral papers of the G7 and BRICK economies were summed across
el 38 partner countries for which data were analyzed. For the G7, there is a similar trajectory
of rising bilateral coauthorship until around 2000, when it flattens for most countries at around
25–30% of total output. US bilateral collaborations started from a lower point and continued
to grow until also reaching this band. The log-plot of the bilateral collaboration data makes
clear the climb, the near-synchronous flattening of relative growth and the similar proportions
that bilateral partnerships make up (Cifra 2).

The collaboration patterns of the BRICK countries are initially more volatile, a likely con-
sequence of the evolving research economies. South Korea’s exceptionally high bilateral col-
laboration in the 1980s was dependent on US research dependency and initially declines,
whereas Brazil and India had rising levels of collaboration. As their research bases mature
so these BRICK curves flatten in the 2000s but at a lower level (15–20%) than the G7 nations.
Japan is the G7 exception and it too flattens out with bilateral collaboration at about 20% de
total output.

The data for all 38 countries support this general picture, with a rise in bilateral collabora-
tion into the early 2000s and then a general flattening. A swathe of countries had a level of

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Cifra 2. Bilateral collaboration as a logged percentage of total annual articles and reviews published in journals indexed in the Web of
Science for the G7 and BRICK countries. For the G7, the relative volume of bilateral collaboration rises markedly and then (except for the
United States) flattens from around 2000. For the BRICK countries it also flattens at about the same time, but patterns in the 1980s and
1990s are more variable. The country sequence in the key is ordered by bilateral share in 2018. Data for additional countries is available as
Supplementary information.

bilateral collaboration that was similar to the G7, around 25–30% (available as Supplementary
información).

Multilateral collaboration follows a trajectory that differs from bilateral collaboration
(Cifra 3). Multilateral collaboration rises throughout the period at a similar rate for the G7
countries, so the most collaborative in 1981 remain so in 2018. Although an inflection to a
slightly slower growth rate after 2000 is evident across countries, the proportion of papers that
have multinational authorship continues to rise and the curves never flatten. Como era de esperar, el
Western EU network is prominent.

The BRICKs take time to settle into a pattern, but after 2000/2005 they follow a similar tra-
jectory to the G7. The growth rate in multilateral collaboration as a share of national output
seems to be sustained for all these countries through to the present. The exception is China,
which has the lowest level of multilateral collaboration and a much greater proportion of bilat-
eral relationships, which may reflect nationally funded partnerships rather than collective ini-
tiatives such as the EU Framework Programs.

The general pattern is repeated in the analysis for the full group of 38 countries, muchos
of which have rather higher rates of multilateral collaboration than the G7. These include
Indonesia, the research profile of which is strongly dependent on such links, and the Scan-
dinavian group (available as Supplementary information).

A detailed example for the United Kingdom (Cifra 4) deconstructs the pattern by which
purely domestic output falls and continues to decline as collaboration becomes pervasive.
What this suggests is that progressively more complex and wide-ranging networks enabled
the United Kingdom to expand its output, first through bilateral collaboration with G7 partners

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Cifra 3. Multilateral collaboration as a percentage of total annual papers published in journals indexed in the Web of Science, for the G7
and BRICK countries. The relative volume of multilateral collaboration generally increases more steeply in the early 1990s. It rises at a slightly
slower rate for the G7 countries after 2000. For the BRICK countries, the patterns in the 1990s are more variable, but by the 2000s they follow
the same trajectory as the G7. China’s flatter pattern is partly a consequence of exponential increase in its domestic volume. Country sequence
in key is ordered by multilateral share in 2018. Data for additional countries is available as Supplementary information.

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Cifra 4. UK output and international coauthorship between 1981 y 2018. Domestic output declines as a share of the total. Bilateral
coauthorship with the United States becomes a constant share in the 1990s and with the European Union in the 2000s. Multilateral growth
becomes predominant and publication expansion shifts to the Rest of the World (RoW). Similar diagrams are available for the most prolific
countries by publication volume.

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in North America and Europe, and later through multilateral networks beyond those historical
and regional associations.

The United Kingdom’s most frequent and historically strongest research partner was the
United States, the sole coauthor of around 3% of UK papers in 1981. The US coauthored share
increased to 6% of UK papers by 2000 but did not then rise further. If the European Union is
analyzed, for comparable “bilateral” analysis with the United States, as a single bloc, then its
collaboration with the United Kingdom was about 6% en 1981, increasing to 17% en 2004 pero
then continuing at no more than 19% of UK papers every year since 2009. A further cross-
section is provided analyzing “trilateral” coauthorship between the United Kingdom, European
Union and United States. This was less than 1% of UK papers before 1990, rose to 10% por 2016
and then it too leveled off. Collaboration with the Rest of the World (RoW) expanded throughout
el 38 años, sin embargo, and now accounts for about 32% of UK output and rising. Within this,
12% of UK total paper count has coauthors from the United States, the European Union and
another country.

3.3. Research Subject Diversity

Collaboration increases a country’s capacity and makes additional financial, workforce and
intellectual resources available. That enables not only expansion but also diversification of
research activity. Research portfolios can become more wide-ranging because collaboration
and networks increase effective national capacity and competency. An analysis of the publi-
cation counts across Web of Science journal-based subject categories using the Gini index
confirms that research activity generally shifts towards a more even distribution. These counts
are normalized against the global distribution of publications each year, because journal cate-
gories innately vary in volume. Gini measures inequality, so the index is displayed as (1 − Gini) a
illustrate changing evenness in distribution (Adams et al., 2020).

The United States and United Kingdom had the most evenly distributed publication portfolios
en 1981. As the output being indexed for other countries increased (Cifra 1) so their portfolios
became more even. The BRICKs were initially less diverse than the G7 in 1981 and so had
capacity for a noticeable, rapid shift towards evenness, except for Russia and—recently—Brazil
(Cifra 5).

Not only did national research portfolios become more evenly spread across research sub-
jects. They also began to converge on similar Gini values. This should not be interpreted as
global homogeneity: it is multiple economies arriving at a similar spread of evenness. Esto es
because different mixes can produce the same numeric value for a diversity indicator.

There is likely to have been a wide range of underlying specialization and diversity across
the full set of 38 countries in 1981 and some of this will have been preserved in a general trend
towards evenness that is reflected across all countries. The majority become more even until
their research subject diversity levels off close to the same broad band ((1 − Gini) = 0.6–0.75)
by the end of the period (see Supplementary information).

Diversity is not interdisciplinarity, but it enables interdisciplinarity. Was the change in even-
ness linked to international collaboration or promoted by domestic policies to support a more
diverse research base given the emerging prominence of interdisciplinary needs and opportu-
niidades (Committee on Science, Ingeniería, and Public Policy, 2004)? The components of
diversity associated with domestic and internationally collaborative papers can be distin-
guished by separating these groups of papers prior to calculating the diversity coefficient.
When this is done, using the United States as an example from the G7 and India as an example

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Cifra 5. Gini coefficient of evenness of publication spread across Web of Science journal categories for G7 and BRICK countries between
1981 y 2018. Note that the vertical axis shows (1 − Gini) because the coefficient is intended to expose inequalities. The G7 countries’
diversity converges and evenness for the USA and United Kingdom reduces in doing so. The BRICK countries appear to be evolving towards
a similar value. Country sequence in key is ordered by subject diversity in 2018. Data for additional countries available as Supplementary
información.

from the BRICKs group, it becomes apparent that national research subject diversity in the
1980s was closely reflected in domestic diversity, that the diversity of international collabora-
tion rose consistently over the next four decades, and that international collaborative diversity
was a more important factor by the end of the period, mientras, in the case of the United States,
domestic research diversity tended towards greater selectivity. This is most evident in the data
for the United States and other G7 countries, but is still apparent in the data for India and other
BRICKs (Cifra 6).

3.4. Research Similarity

The research subject diversity of countries may trend towards greater evenness and converge
on a similar index value, pero, as noted, this does not necessarily indicate that they have
increased the similarity of their portfolio content. Two countries with different distributions
across subjects can generate the same index value of diversity. To make a complete analysis
would require a large number of pairwise comparisons (encima 700 para 38 countries) so only two
examples (Germany and South Korea, which are both technology-oriented) are illustrated here
and then only for national research similarity to the other G7 and BRICK countries.

The annual correlation between the relative frequency of publications across 250 journal
categories for each pair of countries was calculated. We are not interested here in multivariate
analysis but only the degree of pairwise similarity. This is a simplistic analysis of the degree to
which the relative abundance of publications across subjects is the same. Sin embargo, a high
positive correlation indicates a similar spread, a high negative correlation indicates a different
and complementary portfolio, and a lack of correlation indicates a random pattern of similarity
and dissimilarity.

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Cifra 6. Gini coefficient of research subject evenness for Web of Science journal categories for the United States and India. Whole country
data are split into domestic (no overseas coauthor) and internationally collaborative components. Net national research subject diversity
appears closer to domestic research subject diversity in 1981 but more closely linked with the subject diversity of international collaboration
por 2018.

The overall pattern is of increasing similarity in research profiles among the G7 economies
after the mid-1990s, while the BRICK economies remained much more distinctive. It should be
considered that this may in part be influenced by a combination not only of the increased
relative frequency of international collaboration but also of a shift to Anglophone publication
in journals indexed in Web of Science as researchers looked for a more global audience.

For Germany, similarity with France and Italy was high throughout and increased with the
United Kingdom and Canada, and with the United States, with which its indexed publication
record was strongly dissimilar in the 1980s. German research output became increasingly dis-
similar to that of China, India, and South Korea, as it did for Canada. Sin embargo, Russia and
Japan’s indexed research was relatively similar to Germany’s in the 1980s and continued to
be no less similar than that of Canada and the United Kingdom (Cifra 7, top panel).

South Korea was neither very similar nor dissimilar to other countries in the 1980s. Él
appears to be most similar to Japan and India and became increasingly similar to them after
2000. Asombrosamente, it was relatively dissimilar to the United States (with which it had strong
collaborative links in the 1980s) and increasingly diverged from the United States, United
Kingdom, and Canada in the 1990s and from Brazil, Alemania, and France after 2000. por estafa-
contraste, it converged on and has stayed very similar to China’s portfolio over 30 años (Cifra 7,
bottom panel).

3.5. Citation Impact

Citation rates are widely inferred, for very large samples, to be a sound reflection of the sig-
nificance of research papers (garfield, 1954; Moed, De Bruin, & Van Leeuwen, 1995). Es

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Cifra 7. Similarity between the research portfolios of the G7 and BRICK countries and those of Germany (arriba) and South Korea (abajo), como
measured by the correlation between the proportion of output across subject-based Web of Science journal categories.

likely that the systemic changes in output (Cifra 1) and collaboration (Figures 2 y 3) will
interact with citation impact.

CNCI rose for all economies at similar rates, but with most of the G7 (except Japan)
converging on a common value around 1.3. Convergence is a very likely consequence of
colaboración: If many papers are shared, then each national value is strongly influenced by
its partners’ contributions, and they by itself (Cifra 8).

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Cifra 8. Average Category Normalized Citation Impact (CNCI) of articles and reviews published annually by the G7 and BRICK nations
entre 1981 y 2018. Citation counts for individual papers are normalized by year and subject category before the average is calculated
(world average = 1.0). Countries in the key are ordered by average CNCI in 2018. Data for additional countries is available as Supplementary
información.

Brasil, India, and Russia appear to have reached a different CNCI plateau below the world
promedio, and their international collaboration is lower than that of the G7. Sin embargo, collab-
oration is also relatively less for South Korea, which has a rising CNCI line. This is now above
the world average and is on a continuing upwards trajectory.

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Looking across the full set of 38 countries (available as Supplementary information), el
only country that has a consistently declining CNCI is the United States. This apparent decline
may be partly explained by a shift in the United States’ relative position as others improved,
because index values are normalized against the pooled world average. As it starts with a high
CNCI value, it can only decline as others become more frequently cited than in the past. Alguno
smaller countries have extremely erratic year-to-year variation in CNCI, which can be
explained by their collaboration opportunities (Potter et al., 2020). Some countries—notably
in western Europe—have an average CNCI above that of the G7.

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4. DISCUSIÓN
We cannot “prove” whether (or not) increasing commonality between leading research entities
is a self-organizing force that has driven a convergence in global research and a rise in citation
indicators, nor can we prove that this has occurred irrespective of national policy and man-
agement structures. The point of discussion is what, on balance, the data for a large number of
countries suggest. Are their research trajectories similar or divergent? If they converged, did
they do so at similar times or variously?

We argue that the data in this paper strongly support the idea of a global research network
that has exhibited relatively synchronous convergence irrespective of differences in the timing
or nature of national research policies. We believe that implicitly self-organizing properties are

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essentially built upon a consensus view of “good science” emerging from concepts of Crane’s
(1972) “invisible college” in research.

The college is built upon shared ideas of how research should be practiced and what con-
stitutes good research, in terms of methods, sharing, openness, and publication. Internacional
collaboration made possible by social and technological change has drawn the global
research diaspora into a network, led by the giants in their field, in which nations not only
exist but must also engage because leading, impactful activity and innovation now take place
beyond national boundaries (Adams, 2013; Wagner, 2018).

This builds on and relates to ideas advanced by Wagner and Leydesdorff (2005). Our only
point of difference from them is that they reference specific models of preferential attachment
whereas we envisage a more generic model of research culture where disciplinary networks
emulate the “good practice” of research leaders.

This is not only an academic observation but also a conclusion with significant policy
implications. As Wagner et al. (2015) nota, “The network features an open system, attracting
productive scientists to participate … governments could gain efficiencies and influence by
developing policies and strategies designed to maximize network benefits—a model different
de [estrategias] designed for national systems.”

Better information flow, mutual awareness, and enhanced communication meant that research
output grew continuously for most countries over the four decades after 1981 (Cifra 1). It did
so initially through bilateral collaboration, but after the early 2000s bilateral coauthorships no
longer expanded relative to total output for most countries (Cifra 2). After this time, a rise in
multilateral collaboration became dominant (Cifra 3). There was a general increase in research
subject diversity and evenness across subjects converged on a similar index value for many coun-
intentos (Cifra 5), which appears to be associated with and is perhaps an inevitable consequence of
the rise in multilateralism (Cifra 6). Similar diversity indices are not the same as actual similarity,
but in fact the G7 countries did become increasingly similar (Cifra 7, arriba) as did the evolving
portfolios of the BRICK countries (Cifra 7, abajo). With rising collaboration, so national average
citation impact (CNCI) increased and groups converged on similar impact values (Cifra 8), con
the largest economies all settling at a common value well above the world average.

How can a large number of countries, including prolific publishers, have an average CNCI
above world average? The apparent anomaly of many countries doing better than the world
average they dominate is a consequence of shared publications. For both collaboration and
impact indices, the well-cited collaborative papers are counted every time in each country total
but only once in the world’s total. Less well-cited domestic papers are counted once in a coun-
try total and once in the world total. The net world CNCI is thus diluted by the aggregation of all
the domestic papers. Because these data characteristics are not properly understood, this leads
to misinterpretation and may mislead policy makers about the limitations of real achievement.

During the four decades covered by this analysis, research policies evolved and compre-
hensive research management interventions, such as national research assessment cycles,
were initiated sporadically by some countries. But not all followed distinct national paths.
Por ejemplo, the United Kingdom started university research evaluation in 1986 and institu-
tionalized this in 1992 via the Research Assessment Exercise (RAE). The UK policy was not
followed by France and Germany until after 2000, while Australia followed a similar path
to the United Kingdom only after 2008. The United States has never had a national system
of institutional research assessment. China meanwhile followed a path of exceptional expan-
sión, albeit with a lower rate of multilateral collaboration (Cifra 3).

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Despite such national differences in policy and management, we observe similarities in tra-
jectory, in the timing of shifts between bilateral and multilateral collaboration, and in conver-
gence upon similar values of diversity and citation impact across countries. No statistical test or
conceptual model can replicate this, but the appearance is of a global system with common
organizational properties across borders that override structural and policy differences between
a ellos. Although the United Kingdom initiated greater selectivity in and concentration of research
resources in the 1980s, the subject diversity of the research portfolio throughout this period
nonetheless remains stable (Cifra 5). The conclusion might be that, Por ejemplo, los unidos
Kingdom’s improvement in research performance in the 1990s compared to a downturn in
the 1980s (Adams, 2002) would have occurred whether or not the RAE had been introduced.

If there is a driver, a shared and systemic organizing factor, then it is most likely to be col-
laboration between like-minded research colleagues. Rising international collaboration,
enabled by enhanced physical and electronic communication, led to a greater sharing of ideas
and a consensus on both priorities and how they should be tackled and reported. It also
enabled apparent growth with constrained resources, so growth and diversity of national
research portfolios were seen to increase while domestic research volumes were actually
static. The continuing shift from pairwise to group projects increased the overlap of output
and the sharing of ideas and enabled a de facto resource pool that increased rather than reduc-
ing national diversity. Awareness of the significance of international research grew and CNCI
progressively rose as a group of nations shared the same pool of research objectives and
important, highly cited outputs, leading in turn to greater similarity and converging impact
indices.

These are global data, analyzed across a large number of research-active countries, cual
spawn not only general observations about self-organizing networks outside national bound-
aries but a series of other intriguing scenarios.

Por ejemplo, is the value at which the G7 are converging simply “about as diverse as you
can afford”? The diversity of national research portfolios increased as their activity became
more evenly spread across research subjects (Cifra 5). This was not in itself global homoge-
neity: It is multiple economies arriving at a similar degree of evenness. There is some evidence
in these data of a speculative balance point between selectivity and diversity. The United
States and the United Kingdom seemed to “overshoot” in the 1990s, perhaps supporting an
unsustainable portfolio, because after 2000 they increase in specialization again.

Is there one network or two groups? This is a subjective perspective but global tensions
between open research networks and demand-driven bilateral partnerships may provoke some
real bifurcation (Adams, Johnson, & Grant, 2022). The BRICK nations represent newer research
agendas that focus on innovative technology and economic competitiveness; they have higher
levels of bilateral research. The G7 represent a set of older research agendas that have moved
from old technologies to societal priorities, such as health and environment, supported by
open multilateral research. The details that differentiate national similarity in the German
and South Korean outcomes (Cifra 7) are reflected in other national analyses. Alemania, con
a strong industrial technology tradition, retains similarity with Russia and Japan but its evident
difference from China and South Korea points to important differences in detail.

South Korea’s CNCI is rising and it also has the highest level of research investment in the
world: Gross Expenditure on R&D (GERD) is already over 4% compared to an aspirational EU
target of 3%. South Korea’s domestic research base is focused on innovative technology and
strongly supported by domestic industry. CNCI for Brazil, India, and Russia seems to have pla-
teaued: Brazil has suffered from financial and strategic disruption to its research base; India has

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A converging global research system

yet to commit the investment required (its GERD is 0.65% of GDP and falling); and post-Soviet
Russia has yet to re-establish a formerly excellent higher education and research base. The past
appears to show a strong common trend, but whether that will continue for the future is a
political rather than analytical policy issue.

EXPRESIONES DE GRATITUD

We are particularly grateful for the well-informed suggestions of two anonymous reviewers.
The material in this paper was jointly analyzed and authored and the content has been
informed by discussions with Caroline Wagner, Loet Leydesdorff and our colleagues at the
Institute for Scientific Information.

CONTRIBUCIONES DE AUTOR

Jonathan Adams: Conceptualización, Curación de datos, Análisis formal, Investigación, Metodología,
Administración de proyecto, Validación, Visualización, Escritura: borrador original. Martin Szomszor:
Curación de datos, Análisis formal, Metodología, Software, Validación, Escritura: revisión & edición.

CONFLICTO DE INTERESES

Jonathan Adams is employed by Clarivate, which owns the Web of Science. Martin Szomszor
was employed by Clarivate at the time of analysis and is now an independent researcher.

INFORMACIÓN DE FINANCIACIÓN

No external funding was required for this research.

DISPONIBILIDAD DE DATOS

All the background data are available to academic researchers in institutions that subscribe to
the Web of Science.

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