Juglares? — Annotations on Internal Migration and Demographic Aspects of Researchers in Colombia

Abstract

The juglar vallenato was a wonderer, traveling on the back of a mule from town to town across the Caribbean coastal region of Colombian, singings about love and nature. Are the modern Colombian researchers also the juglares of science? This study aims to identify patterns in Colombian researchers, examining their demographic aspects and disciplines, as well as the relationship internal migration and science funding at the municipality level. To do this, we use the complete and official sample of Colombian researchers to unveil those patterns issued by Colciencias/MinCiencias. Most of the scientific workforce is dedicated to social sciences and engineering and technology. There is a heterogeneous gender disparity by disciplines. While the median chronological age for researchers is around 43 the median academic age is 5. There is a significant although weak correlation between academic and chronological age. There is an increasing trend in the population of researchers in fields such as economics and business, electrical electronic and information engineering, other engineering and technologies, and other agricultural sciences, whereas a decreasing trend in fields such as biological, chemical science, and educational sciences. Male researchers by disciplinary area have migrated internally more compared to female researchers. Female researchers migrated more compared to male researchers in just seven disciplinary areas, mostly from natural sciences and engineering and technology. There is a gender parity for internal migration scholars in just nine areas such as social sciences and humanities. However, for the remaining 25 areas, there are more male researchers who have migrated compared to female ones, particularly in engineering and technology and social sciences. Over 45% of researchers have migrated internally to the main cities or from main cities to other main cities. Finally, there is a strong and significant correlation between the municipal net migration rate and total science funding invested by the public sector and institutions.

Full text

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Juglares? — Annotations on Internal Migration and Demographic Aspects of Researchers
in Colombia
Julián D. Cortés
School of Management and Business, Universidad del Rosario; Colombia
Engineering School, Universidad de Los Andes, Colombia
julian.cortess@urosario.edu.co; jd.cortes14@uniandes.edu.co
Abstract
The juglar vallenato was a wonderer, traveling on the back of a mule from town to town across the
Caribbean coastal region of Colombian, singings about love and nature. Are the modern Colombian
researchers also the juglares of science? This study aims to identify patterns in Colombian researchers,
examining their demographic aspects and disciplines, as well as the relationship internal migration and
science funding at the municipality level. To do this, we use the complete and official sample of Colombian
researchers to unveil those patterns issued by Colciencias/MinCiencias. Most of the scientific workforce is
dedicated to social sciences and engineering and technology. There is a heterogeneous gender disparity by
disciplines. While the median chronological age for researchers is around 43 the median academic age is 5.
There is a significant although weak correlation between academic and chronological age. There is an
increasing trend in the population of researchers in fields such as economics and business, electrical
electronic and information engineering, other engineering and technologies, and other agricultural sciences,
whereas a decreasing trend in fields such as biological, chemical science, and educational sciences. Male
researchers by disciplinary area have migrated internally more compared to female researchers. Female
researchers migrated more compared to male researchers in just seven disciplinary areas, mostly from
natural sciences and engineering and technology. There is a gender parity for internal migration scholars in
just nine areas such as social sciences and humanities. However, for the remaining 25 areas, there are more
male researchers who have migrated compared to female ones, particularly in engineering and technology
and social sciences. Over 45% of researchers have migrated internally to the main cities or from main cities
to other main cities. Finally, there is a strong and significant correlation between the municipal net migration
rate and total science funding invested by the public sector and institutions.
Keywords: internal migration; scientific mobility; academic mobility; researcher career; demography
Introduction
The juglar vallenato (i.e., minstrel), was a wonderer, a musician traveling on the back of a mule from town
to town across the Caribbean coastal region of Colombian. Juglares sang melodies about love, their
affection towards the land, birds, and rivers, or just carrying messages from one pueblo to another with the
help of guitars and accordions [1]. A juglar vallenato was a mobile by nature and art/profession. In this
study, we attempted to draw a connecting line between juglares and the modern Colombian researcher. As
the juglar vallenato did, are the Colombian researcher also a mobile subject who migrates from pueblo to
pueblo or city to city, singing lectures and training their mentees with the help of their test tubes, statistical
software, and cultural capital, or are they mostly non-movers? Also, what other aspects could be revealed
by studying such migration patterns through the lens of gender, scientific disciplines, and science funding
at the municipality level? This study aims to identify patterns in the Colombian scientific workforce,
examining their demographics and disciplines, as well as the relationship between national mobility and
science funding at the municipality level. For the first time—to the best of our knowledge—we use the
complete and official sample of Colombian researchers to unveil those patterns.
We built on the mature literature on innovators' migration and mobility [2, 3]. By restricting the
discussion to core journals on science of science [4], since the 1980s the community of practice showed

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interest in the relationship between researchers' age, mobility and productivity [5, 6]. Ever since, the vast
majority of studies have focused on understanding the positive—not so the negative—effects of innovators
mobility and migration on the production of scientific-technical knowledge, economic returns, and career
paths effects in both international (from and to one or multiple countries) and organizational-cognitive
settings (from and to economic sectors, universities, firms, research fields), mostly in the global north, with
a few exceptions on global perspectives [7, 8, 17–26, 9, 27–36, 10, 37–40, 11–16]. A growing agenda
focused on the global south—particularly in China [41–43], India [44, 45], Latin America [46–48], and the
Middle East-Africa [49]—had provided insights in the relation of international mobility and migration on
research performance, productivity, collaboration, and impact; internal migration; the criteria of host-
country selection and causes of return to the country of origin; and migrants' gender composition and
differences.
We contribute to this tradition by expanding the research scope of internal migration of researchers
to another middle-income country, disciplinary and gender composition and differences, and the
relationship between internal migration dynamic, and science funding. This multi-perspective could be used
to understand the demographic, disciplinary composition, internal migration patterns, academic-
chronological age features, and municipality and regional strengths and weaknesses in terms of scientific
workforce to attend the national system of science requirements with evidence-based insights. After this
introduction, the following sections will present the data sources and methods used, followed by the results
analysis and discussion, and finishing with the conclusions, limitations, and further research agenda of this
study.
1 Methodology
1.1 Data
Data on Colombian researchers was sourced from the open access data set issued by the Ministry of Science
Technology and Innovation (MinCiencias) of Colombia [50]. This data set has information on six national
evaluations in 2013, 2014, 2015, 2017, 2019, and 2021. The complete dataset with the results of the six
evaluations has 77,237 observations (rows), 30 variables (columns), and 2,317,110 elements (cells). Table
1 presents the types and description of variables. The data set has anonymized information on academic
profile and portfolio, and diverse demographic aspects, from age to disability, if any, for each researcher.
Information related to projects and programs of science, technology and innovation funded by MinCiencias
from 2007 to 2020 was also consulted [51]. Demographic and economic data at the municipality level was
sourced from the National Administrative Statistics Department (DANE) [52, 53].

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Table 1 Type and description of variables
#
Variable
Type
Description
1
ID_CONVOCATORIA
number
id of the call
2
NME_CONVOCATORIA
plain text
name of the call
3
ANO_CONVO
date and time
year in which the call was issued
4
ID_PERSONA_PR
plain text
person identifier
5
ID_AREA_CON_PR
plain text
researcher's main oecd knowledge area identifier
6
NME_ESP_AREA_PR
plain text
specialty of the researcher's principal oecd area of knowledge
7
NME_AREA_PR
plain text
main researcher's oecd knowledge area
8
NME_GRAN_AREA_PR
plain text
main researcher's major area of knowledge oecd
9
NME_GENERO_PR
plain text
researcher's gender
10
NME_PAIS_NAC_PR
plain text
researcher's country of birth
11
NME_REGION_NAC_PR
plain text
researcher's region of birth
12
NME_DEPARTAMENTO_NAC_PR
plain text
department of birth of researcher
13
NME_MUNICIPIO_NAC_PR
plain text
municipality of birth of researcher
14
COD_DANE_NAC_PR
plain text
dane homologation code for municipality of birth
15
ID_NIV_FORMACION_PR
plain text
highest level of education attained
16
NME_NIV_FORM_PR
plain text
name of the highest level of education attained
17
NRO_ORDEN_FORM_PR
number
importance of the level of training, with 0 being the lowest value
18
ID_CLAS_PR
plain text
category achieved by the researcher
19
NME_CLASIFICACION_PR
plain text
name of the category achieved by the researcher
20
ORDEN_CLAS_PR
number
order of importance of the category achieved by the researcher
21
EDAD_ANOS_PR
number
age in years from the date of birth to the last month of the call window
(2017-07)
22
NME_PAIS_RES_PR
plain text
country where the researcher is located
23
NME_REGION_RES_PR
plain text
region where the researcher is located
24
NME_DEPARTAMENTO_RES_PR
plain text
department where the researcher is located
25
NME_MUNICIPIO_RES_PR
plain text
municipality where the researcher is located
26
COD_DANE_RES_PR
plain text
dane code for the municipality where the researcher is located.
27
ID_VICTIMA_CONFLICTO
plain text
population victim of the armed conflict
28
TXT_GRUPO_ETNICO
plain text
researcher's ethnic group
29
TXT_POBLACION_DISCA
plain text
population in situation of disability
30
INST_FILIA
plain text
list of institutions that the researcher indicates to have affiliation
separated by pipe (|)
Source: MinCiencias [50].
Table 2 reports a selection of descriptive statistics. The total number of researchers has multiplied by 2.6
times between 2013 and 2021. The gender ratio female/male researchers between the same period increased
from 0.51 to 0.64, revealing an increasing involvement of female researchers but also a revealing a sustained
majority of male researchers in the country. The average age is 44.7 years, with a minimum average of 41.2
and a maximum of 47.5. When we look at the researchers by category based on their academic seniority
(i.e., research output, academic degree, mentoring, and so forth) the ratio of junior/senior researchers
decreased from 7.6 in 2013 to 4.1 in 2021, revealing an increasing number of seniors compared to junior
researchers. Finally, the main national and department capitals of the country, such as Bogotá, Medellín
and Cali, were the most frequent place of birth and residence for researchers.

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Table 2 Total unique researchers ID by gender, average age, and most frequent place of birth and residence
2013
2014
2015
2017
2019
2021
Total unique researchers ID
7578
8147
9867
12787
16492
20396
Male
5010
5261
6363
8009
10204
12374
Female
2570
2886
3504
4778
6288
8014
Average age – Male
47.5
45.5
45.3
44.5
43.7
41.2
Average age – Female
47.5
43.3
43.9
43.3
42.8
42.2
Category:
Junior
5102
5043
5893
7393
9636
12706
Associate
1807
2056
2747
3584
4337
4577
Senior
671
1048
1154
1698
2469
3032
Emeritus
-
-
-
112
50
81
Top-5 most frequent city/municipality of birth by unique researchers ID 2013-2021
Bogotá
7393
Medellín
3032
Santiago de Cali
1568
Barranquilla
1235
Bucaramanga
1085
Top-5 most frequent city/municipality of residence by unique researchers ID 2013-2021
Bogotá
9593
Medellín
4497
Santiago de Cali
2155
Barranquilla
1685
Bucaramanga
1208
Source: MinCiencias [50].
1.2 Methods
We study multiple internal migration and demographic aspects of the Colombian scientific workforce using
well-known methods and (modified) indicators. First, we produced population pyramids by grand
disciplinary areas [54] and also explore the relationship between academic and chronological age. It is
crucial to notice that the academic products in the Colombian science system are quite diverse and different
since the researchers and groups assessments not only consider research papers but also thesis
supervised/mentoring, innovation-technological products developed, and the appropriation and
communication of science. Here we are considering all products and not only papers to compute the
academic age of researchers. This is a modified index which consider the difference between
  
. To maintain uniformity with the literature, we refer
to the academic age as the same as the knowledge-production age that considers all types of
knowledge/mentoring output and not just publications. Second, we computed the ratio of researchers by
disciplinary area, or   , where  is the ratio,  is the number of researchers for 41 OECD
disciplinary areas with 10 or more subjects and  the total number of researchers in that year. Third, we
modeled a directed network, being the source the municipality of birth  and the target municipality of
residence , to produce a visualization of the internal migration flow. We used an axis-based node-link
called hive plots. Such representation place nodes uniformly across spaced axis arranged radially (i.e.,
aspect). Compared to the canonical network representation, hive plots increase the interpretation of network
patterns since it uses network properties as foundations instead of aesthetic layout [55]. Fourth, we
calculated the net migration rate, or   󰇛󰇜
, where  is net internal migration rate,
 is the number of immigrating researchers entering to that municipality (i.e., ID researcher from
municipality place of birth  entering to municipality place of residence ),  is the number of emigrating
researchers leaving that municipality (i.e., ID researcher from municipality place of birth  entering to
municipality place of residence ), and  is the total number of researchers for that year.

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2 Results and discussion
Fig. 1 reports the population pyramid by six OECD grand disciplinary areas for the 2021 national
assessment call. Most of the scientific workforce in Colombia is dedicated to work in fields related to social
sciences and engineering and technology, whereas fewer researchers in agricultural sciences or humanities,
leaving in the middle medical and health sciences and natural sciences researchers. At a first glance, is
noticeable the gender disparity in engineering and technology and natural sciences concerning the higher
composition of male researchers, whereas in social sciences and medical and health sciences female
researchers seem to have a higher participation. Concerning median age, female researchers in engineering
and technology are the younger groups compared to the more senior of males in medical and health sciences.
Two test confirmed that mean age differences between male and female researchers is significant, being
female younger than male researchers in average.
In concrete, 34% of female researchers work in social sciences (median age: 41.4 years), 21% in
medical and health sciences (44 years), and 18% in natural sciences (42.1 years). On the other hand, 27%
of male researchers work in social sciences (44.7 years), 25% in engineering and technology (41.6 years),
and 21% in natural sciences (43.2 years). The combined percentage of all genders is less than 10% in
agricultural sciences. The younger group are female researchers in engineering and technology (39.5 years)
and the more senior group are males in medical and health sciences (45.5 years). A Welch two-sample t-
test confirmed that there is a significant difference in the mean age between the two groups 󰇟󰇛󰇜  
    󰇠, with the 'Female' group having a lower mean age (     ) than the
'Male' group (     󰇜. The 95% confidence interval for the difference in means ranged
󰇟󰇠. Considering the age skewed distribution, we check further conducting a Wilcoxon rank-sum
test with continuity correction, which also found a significant difference between groups 󰇟 
   󰇠.

6
Fig. 1 Population pyramid by grand areas (OECD-Fields of Science classification), 2021. Source: MinCiencias [50].
Fig. 2 reports the relationship between academic and chronological age by grand research areas. The median
academic age in the country is 5 years (  ) with a maximum observation of 44 years. The junior
disciplines considering the juvenile max observations are the humanities and engineering with the oldest
academic subject of 28 academic years. Overall, there is a significant although weak correlation between
chronological and academic age,󰇛󰇜       , with 95% confidence intervals from
󰇟 󰇠. By disciplinary and gender groups, the higher correlation between chronological and academic
age is for men in agricultural sciences (  󰇜 and the lowest is also for men in the social sciences ( 
󰇜.

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Fig. 2 Academic and chronological age by grand areas (OECD-Fields of Science classification), 2021. Source: MinCiencias
[50].
Fig. 3 and Table 3 offer a more refined perspective of researchers by field normalized by the total number
of researchers and its trends between 2013 and 2021. The ratio of researchers of disciplines such as
biological, chemical science, and educational sciences are among the top ten, however they show a
downward trend. Health sciences and clinical medicine researchers show stagnation, whereas those in
disciplines such as economics and business, electrical electronic and information engineering, other
engineering and technologies, and other agricultural sciences show an upward trend. In contrast, when we
examine the bottom ten disciplines, researchers working on philosophy, ethics and religion, and social and
economic geography are showing an upward trend just recently (2019, 2021). Most of the remaining
disciplines among the bottom ten, show stagnation after a brief increasing in the early assessments back in
2013 particularly in biotechnology (e.g., medical biotechnology, industrial biotechnology, agricultural
biotechnology, and environmental biotechnology), other medical sciences and nanotechnology.

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Fig. 3 Three map – Mean ratio of researchers by disciplinary area over the total of researchers with 10 or more subjects by
discipline 2013-2021. Source: MinCiencias [50].

9
Table 3 Top and bottom 10 average ratio of researchers by disciplinary area over total with 10 or more subjects by
discipline, 2013-2021
Source: MinCiencias [50].
Fig. 4 displays a radial graph of the percentage of internal by gender, disciplinary area, and the female/male
ratio based on 2021 assessment. In general, male researchers by disciplinary area migrate substantially more
compared to female researchers. Female researchers migrated more compared to male researchers in just
seven disciplinary areas, mostly from natural sciences and engineering and technology. There is a gender
parity for just nine areas, particularly in social sciences and humanities. For the remaining 25 areas, there
are more male migrants compared to female researchers, particularly in engineering and technology and
social sciences.

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Fig. 4 Radial graph for percentage and female/male ratio internal migrant researchers by disciplinary area, 2021. Source:
MinCiencias [50].
To have a general sense of the internal migration dynamic between departments with most of the
municipalities, Fig. 5 displays a directed network. Each axis and color correspond to a department and each
node a municipality and node-size is proportional to the number of incoming links. The link color
corresponds to the department of birth. Prima facie, there is a clear pattern of national mobility from small-
medium municipalities to their correspondent department capital and the country’s capital (i.e., Bogotá);
and also from department capitals to Bogotá.
As an illustrative case, let's consider the three most populous capitals: Bogotá (~7.5 million
inhabitants, 2019), Medellín (~2.5 million) and Santiago de Cali (~2.2 million) [52]. For the complete
sample of researchers (   ) 28% were born and registered their residence in Bogotá,
8% in Medellín, and 3% in Santiago de Cali, thus around ~40% of researchers in Colombia have not
migrated and are concentrated in the three most populous capitals. Besides the substantial proportion of
researcher residents in those cities, they are also migration hubs for hundreds of others. The most frequent
source-destiny cities are Bogotá-Medellín (256 researchers), Medellín-Bogotá (212), Santiago de Cali-
Bogotá (210), Bogotá-Santiago de Cali (202), and Bucaramanga-Bogotá (210), the latter as the only
exception to these in-between main cities dynamic. At a more refined scope, at least one researcher from
498 municipalities has immigrated to Bogotá, whereas researchers born in Bogotá have emigrated to 98
different municipalities. For Medellín, researchers have immigrated from 310 municipalities, whereas
researchers born there have emigrated to 58 different municipalities. Finally, for Santiago de Cali,
researchers have immigrated from 201 municipalities whereas researchers born there have emigrated to 47
other municipalities.
0,0
0,2
0,4
0,6
0,8
1,0
1,2
1,4
Other natural sciences
Environmental biotechnology
Computer and information sciences
Industrial biotechnology
Agricultural biotechnology
Physical sciences
Other engineering and technologies
Political science
Biological sciences
Law
Mathematics
Arts (arts, history of arts, performing…
Health sciences
Other social sciences
Economics and Business
Chemical engineering
Medical engineering
Agriculture, Forestry and Fisheries
Basic medicine
Animal and Dairy science
Materials engineeringSociology
Other humanities
Educational sciences
Languages and Literature
Earth and related Environmental…
Other agricultural sciences
Veterinary science
History and Archaeology
Civil engineering
Electrical engineering, Electronic…
Other agricultural sciences
Clinical medicine
Media and communications
Social and economic geography
Environmental engineering
Chemical sciences
Other medical sciences
Nano-technology
Mechanical engineering
Medical biotechnology
Female/Male Ratio % Female migrants % Male migrants

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Fig. 5 National mobility network between the top-10 departments with the highest number of municipalities and Bogotá
(yellow), 2021. The color of the link is the same as the node source. The frame below shows the migration flow (from place
of birth to place of residence) between main cities or municipalities at the center of the network, 2021. Source: MinCiencias
[50].
Based on the information from 33 municipalities, Fig. 6 presents a bubbles plot to visualize the relation
between the added value per capita (2019) in the x-axis, the net migration rate in the y-axis 2013-2021, and
the total funding of STI projects/programs transferred to institutions in those municipalities in current prices
COP as the bubble size (2008-2017). Around COP560 billion current prices have been invested in STI
related projects/programs already completed or under execution 2008-2017, which is around USD252
million (COP current prices divided by the average exchange rate 2008-2017) [56]. Institutions in Bogotá,
Medellín, Santiago de Cali and Santander have received the vast amount of ~78% for STI funding. In sum,
there is a strong, positive and significant correlation between the net migration rate and the total funding of
STI projects/programs,󰇛󰇜      , with 95% confidence intervals from 󰇟 󰇠.
Therefore, municipalities with a higher national mobility dynamic are also those which institutions have
received and invested most of their resources for executing STI related projects/programs.

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Fig. 6. Bubbles plot of the value added per capita for municipalities for 2019 and the net migration rate for researchers
2013-2021 and the total funding received in billions COP 2008-2017. Source: DANE [52, 53] and MinCiencias [50].
3 Discussion and conclusion
The research agenda on innovators' mobility has contributed to understanding the effects of that
phenomenon on the production of knowledge and multiple socio-cultural-economic dimensions. We
contributed to this tradition by studying demographic aspects, national funding, and internal migration
aspects for the Colombian case. The very first finding was the demographic composition of researchers by
gender, age and discipline. First, there are more males than female researchers, however the gap is
narrowing. The narrowing gender gap of women in science is a bittersweet premonition rolling around since
the early 1980s [57]. As the involvement of women in science is increasing [57], disparities persist on a
higher concentration and benefit for men on science awards, credit and tenure-track positions [58–60],
despite highly similar rates for both women and men in research productivity and impact [61, 62]. Some of
the explanatory factors concerning the gender gap point to demographic inertia, explicit and implicit biases
in research profiles assessments, discrimination, natural differences, assumptions and stereotypes in
professional interactions [59, 61, 63, 64].
We found that both women and man are mostly in social sciences; there are more women in medical
and health sciences; and more men in both natural sciences and engineering and technology. This gender
composition echoes the gender composition of the scientific workforce. A global survey reported a gender
parity in social science and psychology, whereas 15% or less of the corresponding authors figured as women
in fields such as physics and astronomy, engineering, and mathematics [65]. Concerning medical and health
sciences, women's participation is over the 30% average [65]. Explanatory factor for the gender disparity
in scientific areas are diverse, from the influence of teachers' expectancies on women to follow careers on
social sciences and humanities and the men self-concept to follow careers on STEM [66], to parental beliefs
[67], more funding balance and fairness for women in social sciences [68], and parent/motherhood decision
[69, 70]. For both women and men, the average age is well above 40 years, being women in engineering
and technology the younger group and men in medical and health sciences the oldest one. Despite the higher
age average that over 40 years might appear, this is a common phenomenon in academia. Higher education
is where people over 65 are mostly employed and the professorate is a population that has surpassed all
other occupation groups in the workforce [71]. A national assessment found that 47.3% of the scientific
-10
0
10
20
30
40
50
60
70
0 5.000.000 10.000.000 15.000.000 20.000.000 25.000.000 30.000.000 35.000.000 40.000.000 45.000.000 50.000.000
Net migration rate 2013-2021
Added value per capita in COP for cities/municipalities, 2019
STi activities funding in billion COP, 2008-2017

13
workforce is between 40-54 years and 25% is 55 and older [72]. On the other hand, the weak correlation
between chronological and academic career found here, opens multiple discussions concerning the
researcher’s role in the research system, in ways beyond the visible/traditional outputs in academia such as
research papers. For instance, ~6% of the researchers have the average age for pension in Colombia: ~60
years (57 for women and 62 for men). However, they have the academic age equivalent to a junior/early
career researcher (between 1 and 14 academic years) [73]. This segment of the population is mostly in the
social sciences (570 researcher), natural sciences (317), and medical and health sciences (285). Colombia
just recently enter into the production of knowledge path in the late 1990s-early 2000s, despite countless
financial and institutional restrictions [58, 74]. Therefore, the profiles of the universities were —and still
are— teaching oriented instead of research oriented, then enrolling graduate personnel for teaching,
administrative and outreach activities, not research-related ones. In sum, the proposed proxy between
academic and chronological age should be consider with multiple limitations when used in assessment in
middle-low developing countries —even if desegregated by discipline— since the introduction of these
type of countries in the global science ecosystem [72].
Concerning the researcher’s population trends, significant differences can be drawn from a
comparative analysis with the USA and Norway scientific workforce. The only researcher-fields among the
top ten most populous that showed an upward trend in Colombia, were those in economics and business;
electrical electronic and information engineering, other engineering and technologies; and other agricultural
sciences. Taking as a comparison with the economics and business segment, in the USA only 3% of workers
that majored in social sciences are employed as social scientists —being the majority in social services,
legal and education; or in management-business and finance [75]. USA workforce projections in STEM
and Colombian trend similarities lie in science and engineering managers, computer and mathematical
scientists, and health care practitioners and technicians were related, except for the absence of other
agricultural sciences in the USA. Estimates from PhD degree granted by field in Norway, displays an
increasing trend in engineering and technology, social sciences, and medical and health sciences, which are
similar to that of Colombia’s, except for medical and health sciences, which shows stagnation. There is
also a decreasing trend in natural science in Norway, which echoes a similar decreasing trend in biological
sciences, which is among the largest scientific force field in Colombia [76].
Considering the limitations of discussing the findings here with international migration, the gender
gap in most disciplines, is also a reflection of other international realities. In Germany [19], the return
migration streams are gendered imbalanced, and for those men who return they composed the ~65% of
positions as senior professionals compare to women. Also, the highest proportion of women by discipline
that emigrates in Germany is concentrated in agricultural, biological and environmental sciences;
biochemistry, immunology; neuroscience; pharmacology; and psychology. These findings share a few
limited similarities with Colombia, where there is a higher female/male ratio in disciplines such as other
natural sciences; environmental biotechnology; industrial biotechnology; agricultural biotechnology, but a
total absence of social and health and medicine disciplines.
The limited national studies of internal migration [44] found that, in the Indian contexts, scientists
concentration in their home state has being decreasing over the years, a dynamic mostly explained by the
proximity of their new place of residence to their home state. In a similar fashion, Colombian researchers
have migrating from their home municipality to their correspondent department city-capitals, which usually
are the national centers where research and development institutions/activities happen, where funding is
allocated, and wealth creation take place, as confirmed by the correlation analysis between the net migration
rate and STI funding received [33, 77].
At the global level, over 70% of scholars have non-migrated/stay in the country, most of them
affiliated with the same institution throughout their careers [78, 79]. However, it is common that scholar in
Colombia have experienced internal migration from small-medium municipalities to capital cities or in-
between capital cities and have no experience migration since were already born in capital cities. An
important and tragic phenomenon certainly associated with the history of armed conflict of the country that

14
certainly have influence the internal migration of scholars and people is the forced displacement produced
by over half a century of armed conflict. The total number of victims of violent displacement in Colombia
is over 8.2 million, around ~20% of the total population [80]. The armed conflict surely has produced a
speeding up impact in the forced migration of people and knowledge from small municipalities/rural areas
to the cities, however it is more of a sort of informed intuition instead of an aim of this study.
Further stages of this project would include more sources regarding local/international institutional
mobility instead of an only place of birth and residence since that does not account for scientific career
changes. Including the effect of local and international migration in the structure of collaboration, scientific
impact and career advancement and opportunities of Colombian researchers and comparative frameworks
with other countries and institutions will enrich the methodological considerations for international
comparisons. Adding not only the positive aspects but also the null or negative factors that scholar’s
mobility would produce in the middle-long terms, is essential for a nuanced view of the phenomena, open
to dissenting evidence-based assessment of the local contexts that, as noticed, would need more refined
observations than those found in global studies. Finally, a significant population of the Colombian
researchers are juglares. They are mostly man and very young in the business of creating knowledge, but
their chronological age is like the aging population of scholars worldwide. Many of them are no longer at
home. Some of them to look after better luck in the cities and the universities and citadels of knowledge,
other to save their lives and their families. Now, they went there not to sing songs about love, rivers or
rivals, but to add their voice to the local and global concert of science.

15
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