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Introduction
Universities and regional development
Importance of universities in a regional innovation system
Knowledge spillovers
Evidences of spatial localization
Scientific landscape in 1990 -2010
Accelerated growth of production in emerging scientific
nations (China, Brazil and India)
Increase of scientific collaboration (over 70% of their
production from domestic collaboration)
Spatial scientometrics
Analyzes spatial patterns of scientific activity
The importance of geography in process of creation and
diffusion of knowledge
3
Colaboração científica
A ciência moderna é cada vez mais colaborativa
O aumento da colaboração científica revela-se de
muitas maneiras:
Número de participações em projetos de
pesquisa
Número de orientações acadêmicas
Número de coautorias acadêmicas
5
Colaboração científica
Embora existam diferenças claras entre áreas nos
números absolutos de artigos de coautoria, todas as
áreas apresentam um padrão semelhante
6
Artigos em coautoria estão se tornando mais frequentes
Brasil (1990-2010): Área de Ciências Exatas
8
Scientific collaboration in numbers
How to measure scientific collaboration?
Co-authorship in scientific research
Curriculum Lattes (CNPq)
Main system of curriculum information for the Brazilian
scientific community
Information is publicly available
But the process of data extraction and mining is complex
Scriptlattes (MENA-CHALCO et al, 2013)
Summary of database
Total of CVs Total of scientific publications
1.131.912 7.351.957
9
Identification of major knowledge areas (Scriptlattes)
Major Knowledge Areas (CNPq)
Engineering
Humanities
Applied Social Sciences
Linguistics, Letters and Arts
Agricultural Sciences
Exact and Earth Sciences
Health Sciences
Biological Sciences
Other areas
11
Identification of co-authorship (Scriptlattes)
Author A; Author B. Impacts of... Revista XX , São Paulo. 2007.
Researcher A Researcher B
Author A; Author B. Impacts of .... Revista XX , São Paulo. 2007.
Similar titles
Coauthorship between researchers A and B
Bibliographical Production selected in CL
Articles in scientific journals
Expanded abstract published in proceedings of conferences
Book published/organized
Book chapter published
12
Full counting method
Researcher A
Researcher B
Researcher C Researcher D
Region X Region Y Region Z
Region X Region Y Region Z
Region X 1 2 2
Region Y 2 0 1
Region Z 2 1 0
Full counting method
Contains the total number of interregional co-authorships
(symmetric matrix)
Main diagonal: contains the total number of intraregional co-
authorships
Co-authorships associated to 1.347 Brazilian cities (dimension of
matrix)
⇒ 210 matrices of interregional co-authorships
by year (1990-2010) and major knowledge areas (9 + total)
13
Region X Region Y Region Z ... ... ... ... ...
Region X 1 2 2 ... ... ... ... ...
RegionY 2 0 1 ... ... ... ... ...
Region Z 2 1 0 ... ... ... ... ...
... ... ... ... . ...
... ... ... ... . ...
... ... ... ... . ...
... ... ... ... . ...
... ... ... ... ... ... ... ... ...
14
Scientific production in Brazil: 1992-1994
Scientific production measured by authorship in scientific publications
15
Scientific production in Brazil: 2007-2009
Scientific production measured by authorship in scientific publications
17
Increase of scientific production by knowledge areas
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
I-II II-III III-IV IV-V V-VI
Engenharias
Ciências Humanas
Outros
Ciências Sociais Aplicadas
Linguística, Letras e Artes
Ciências Agrárias
Ciências Exatas e da Terra
Ciências da Saúde
Ciências Biológicas
Total
I - (1992-1994)
II - (1995-1997)
III - (1998-2000)
IV - (2001-2003)
V - (2004-2006)
VI - (2007-2009)
Gro
wth
rate
⇒ evidence of slowing-down of scientific production in Brazil
18
Spatial deconcentration
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1,0 26,0 51,0 76,0 101,0 126,0 151,0 176,0
1992-1994
1995-1997
1998-2000
2001-2003
2004-2006
2007-2009
Number of cities (ordered by individual production)
Pro
po
rtio
no
fto
tal
pro
duct
ion
90% of scientific production concentrated in
1992-1994 48 cities
2007-2009 102 cities
20
Scientific collaboration in Brazil
Total of Scientific Co-authorships
1992-1994 547.249
2007-2009 9.445.399
Main links in 2007-2009
Interregional links Intraregional links
Campinas/SP – São Paulo/SP 76.716 São Paulo/SP 1.343.394
Ribeirão Preto/SP – São Paulo/SP 74.078 Rio de Janeiro/RJ 630.049
Niterói/RJ – Rio de Janeiro/RJ 75.224 Porto Alegre/RS 393.888
Rio de Janeiro/RJ – São Paulo/SP 72.500 Belo Horizonte/MG 375.734
Seropédica/RJ – Rio de Janeiro/RJ 65.348 Ribeirão Preto/SP 278.218
Porto Alegre/RS – São Paulo/SP 47.343 Campinas/SP 212.248
21
Expansion of domestic scientific collaboration
0
200
400
600
800
1000
1200
1400
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
ENG HUM SOC LIN AGR EXA SAU BIO TOTAL
Nu
mb
ero
fci
ties
in t
he
net
wo
rks
22
Co-authorship network: Agricultural Sciences (1990 -2010)
Individual degree in the network
Capão do Leão/RS – Pelotas/RS 53.451Piracicaba/SP – Campinas/SP 30.695Lavras/MG – Viçosa/MG 29.334
Viçosa/MG 370.118São Paulo/SP 143.982Lavras/MG 143.559
23
Co-authorship network: Health Sciences (1990 -2010)
Individual degree in the network
Ribeirão Preto/SP – São Paulo/SP 95.120Campinas/SP – São Paulo/SP 78.023Rio de Janeiro/RJ – São Paulo/SP 66.852
São Paulo/SP 2.220.749Ribeirão Preto/SP 426.694Rio de Janeiro/RJ 388.479
Role of geographical proximity
Does space still matter for scientific interactions?
Did this effect decrease over time?
How to measure this effect?
Dimensions of proximity
Geographical, institutional, cognitive and social proximity
Dimensions occur together
24
Average Distance (for 105 main cities)
1992-1994 1995-1997 1998-2000 2001-2003 2004-2006 2007-2009
357,8 Km 387,6 Km 425,4 Km 490,5 Km 493,9 Km 465,2 Km
25
Spatial interaction modeling: Data
scientific collaborations between regions i and j
– measured by co-authorships in scientific publications
and : total of scientific publications in regions i and j
– measured by authorship in scientific publications
: geographical proximity between regions i and j
– measured by physical distance (Kilometres)
: institutional proximity between regions i and j
– dummy variable (1 if both regions have public universities)
26
Spatial interaction modeling for count data
Nature of data
Linear regressionmodel Count Data
Poisson model
Specification testIs there unobserved heterogeneity
(overdispersion)?
Negative binomial model
Specification test
Zero-inflatedNegative binomial
model (ZINB)
Negative binomial model
Specification test
Zero-inflatedPoisson model
(ZIP)Poisson model
27
Estimation results
1992-1994 1995-1997 1998-2000 2001-2003 2004-2006 2007-2009
Poisson
Origem – Destino (𝛼1 = 𝛼2) 0,8212714*** 0,7795005*** 0,8220109*** 0,7858146*** 0,7973171*** 0,7885987*** (0,0799382) (0,0678417) (0,0683882) (0,0579629) (0,054490) (0,0578959)
Distância Geográfica (𝛽1) -0,0019558*** -0,0019253*** -0,0017452*** -0,0015338*** -0,0015431*** -0,0017769*** (0,0003065) (0,0002531) (0,0002097) (0,0001606) (0,0001556) (0,0001774)
Distância Institucional (𝛽2) 0,3644302*** 0,4162181*** 0,1609404*** 0,3136939*** 0,2940121*** 0,4287121*** (0,176917) (0,1436342) (0,1254923) (0,1061115) (0,1068666) (0,1163698)
Constante (𝛼0) -7,857116*** -7,251477*** -7,874573*** -7,340407*** -7,597752*** -7,356414*** (1,304543) (1,149595) (1,215009) (1,060104) (1,034923) (1,116736)
Binomial Negativo
Origem – Destino (𝛼1 = 𝛼2) 0,8521451*** 0,8111029*** 0,7492518*** 0,7274424*** 0,7358830*** 0,6437665*** (0,0254626) (0,0215507) (0,0252036) (0,0219370) (0,0219320) (0,279855)
Distância Geográfica (𝛽1) -0,0008051*** -0,0008671*** -0,0007708*** -0,000797*** -0,0008311*** -0,0008877*** (0,0000654) (0,0000471) (0,0000387) (0,0000035) (0,000392) (0,000359)
Distância Institucional (𝛽2) 0,2046957*** 0,134085*** 0,2595981*** 0,1823897*** 0,0738276*** 0,2052725*** (0,0975923) (0,0765383) (0,0687016) (0,0634148) (0,0598206) (0,0589084)
Constante (𝛼0) -8,848608*** -8,256593*** -7,296663*** -6,709063*** -6,811066*** -5,024858*** (0,2523885) (0,2435624) (0,340571) (0,2793517) (0,3146031) (0,4536341)
Heterogeneidade (𝛼) 6,08251* 5,08992* 4,562474* 3,848097* 3,618955* 3,750808* (0,1914479) (0,116746) (0,0913702) (0,0664739) (0,0644162) (0,0666601)
Notas: i) 𝑛2=11.025 observações; ii) os erros-padrão estão entre parênteses; iii) ***, ** e * referem-se às estimativas
estatisticamente significantes aos níveis de significância de 0,001, 0,01 e 0,05, respectivamente.
28
Interpretation of the results
Characteristics of origin and destination regions
Positive and statistically significant
Institutional proximity
Positive and statistically significant
Geographical proximity
Negative and statistically significant
The value -0.0017769 means that for each additional 100
kilometers between two researchers, the probability for
collaboration decreases by about 16,3%, holding all other
variables constant
Effect is not linear: ↑ 300 Km (600 Km) ⇒ ↓ 41,3%
(65,6%) probability for collaboration
- Geographical distance still plays a crucial role
29
Results by knowledge areas
⇒ The effects of geographical distance on scientific networks are different
30
Conclusion
Overview of the evolution of scientific activity in Brazil (1990-2010)
Accelerated growth of scientific production and
collaboration
But there are evidences of slowdown
Spatial heterogeneity of scientific production
Knowledge flows are concentrated in the Southeast and
South regions
Evidence of spatial deconcentration of scientific production
and collaboration
Scientifically less traditional regions gained prominence
Role of geographical distance on scientific collaboration networks
Distance still plays a crucial role in determining the
intensity of knowledge flows
Effects varies between knowledge areas
31
Reference
The notes for this lecture were based on the following
paper:
“Scholarly Publication and Collaboration in Brazil: The
Role of Geography”
Sidone, O., Haddad, E. A. and Mena-Chalco, J. (2016)
Journal of The American Society for Information
Science and Technology
32
Questão
Em Tese de Doutorado defendida no IPE-USP no dia
24/11/2015, Ana Maria Bonomi Barufi concluiu que
“economias de aglomeração reforçam alguns dos
mecanismos que geram concentração espacial e
desigualdade regional”.
Discuta a conclusão da Dra. Barufi considerando
aspectos relacionados às preferências locacionais de
trabalhadores e firmas.
Código Ingresso Curso Nome P1 P2 Exercícios Subtotal
478424 2012/1 12051 Achiles Romero Riego 18.50 16.00 2.50 37.00
7929210 2011/2 12051 Amanda Amorim de Andrade
8557785 2013/1 12051 Amanda Broering Galvao Pereira 16.00 16.00 3.75 35.75
8071770 2013/1 12051 Andre Kamnitzer Bracco 20.00 18.00 5.00 43.00
8558059 2013/1 12051 Andreza Lopes da Silva 21.25 13.00 8.75 43.00
8012710 2012/1 12051 Bruno Hiromitsu Taba 17.50 21.00 5.00 43.50
8012679 2012/1 12051 Caio Madeira da Silva 22.00 15.00 8.75 45.75
8962526 2014/1 12051 Carlos Alberto Victorino Junior 19.25 12.00 11.25 42.50
8012901 2012/1 12051 Daniel Baracat de Freitas 25.25 10.00 6.25 41.50
7209054 2012/1 12051 Daniel Bomfim Hansen
8962613 2014/1 12051 Daniel Mariz de Oliveira Simantob 22.50 20.00 10.00 52.50
8479725 2013/1 12051 David Birmann 23.00 14.00 8.75 45.75
8138294 2013/1 12051 Edson Augusto Pereira de Moraes 19.50 16.00 8.75 44.25
8963295 2014/1 12051 Ernesto Assuncao França de Mello 18.75 25.00 11.25 55.00
8557997 2013/1 12051 Euler Santos de Sousa 20.50 16.00 5.00 41.50
8071554 2013/1 12051 Ezio Pontes de Souza Filho 20.50 18.00 2.50 41.00
8963580 2014/1 12051 Felipe Atilio Pinheiro Tredezini 15.00 9.00 10.00 34.00
8013301 2012/1 12051 Felipe Tank
8537222 2014/1 12051 Gabriel Marcondes dos Santos 16.50 15.00 10.00 41.50
8558063 2013/1 12051 Gabriela Martins Bueno 21.75 17.00 10.00 48.75
7663121 2012/1 12051 Gabrielle Carlos Paes 16.25 18.00 6.25 40.50
7699524 2012/1 12051 Geraldo Majela Damiao Nogueira 14.50 16.00 10.00 40.50
8012540 2012/1 12051 Giovana Mendonca Espinosa 15.50 10.00 6.25 31.75
8557451 2013/1 12051 Giovanna Abuhab Terezan 21.00 13.00 7.50 41.50
8479493 2013/1 12051 Guilherme de Lima Regio 16.50 13.00 11.25 40.75
4465389 2011/1 12051 Guilherme Neves de Oliveira 21.50 16.00 11.25 48.75
8012147 2012/1 12051 Guilherme Rodrigues da Silva 12.75 12.00 10.00 34.75
8801471 2014/1 12051 Guilherme Rodrigues Pereira 16.50 15.00 8.75 40.25
8016284 2012/1 12051 Heitor Antonio Ramos da Silva 21.00 14.00 7.50 42.50
8557635 2013/1 12051 Isabella Beck 14.50 8.00 10.00 32.50
8628766 2014/1 12051 Izabel Antunes Guarda Faez 26.00 24.00 11.25 61.25
6490631 2013/1 12051 Jefferson Lécio Leal 26.50 28.00 8.75 63.25
8557423 2013/1 12051 Joao Henrique Chalegra de Barros 14.00 12.00 7.50 33.50
9321978 2015/1 12051 Joao Luiz Goes Macedo Bicarato 14.50 8.00 6.25 28.75
7600047 2011/1 12051 Joseph da Silva Pavao Neto 22.00 26.00 3.75 51.75
8557962 2013/1 12051 Juliana Ferraz Salles Kesselring 19.50 18.00 10.00 47.50
4265921 2012/1 12051 Lucas Alvarenga Costa
8557486 2013/1 12051 Lucas da Cunha Rego Logiodice 4.00 10.00 0.00 14.00
8558574 2015/1 12051 Lucas da Silva Placides 13.50 14.00 6.25 33.75
8557826 2013/1 12051 Lucas Mendes Santos 17.25 19.00 8.75 45.00
7929203 2011/2 12051 Manuel Soares Duarte de Oliveira 23.50 23.00 6.25 52.75
8962871 2014/1 12051 Marcos Hernan Costa Manso Croce 13.00 16.00 10.00 39.00
8963207 2014/1 12051 Maria Alice da Silva Nunes 9.50 15.00 10.00 34.50
8139131 2013/1 12051 Mateus Calderam Villaca 20.50 21.00 6.25 47.75
4482660 2013/1 12051 Mathias Dahmer 13.50 16.00 11.25 40.75
8963465 2014/1 12051 Nicole Pitelli Biason 18.75 6.00 11.25 36.00
8479962 2013/1 12051 Otavio Cury Morello 23.75 23.00 8.75 55.50
6819779 2009/1 12051 Paulo Sergio Weber da Silva Bianchi 10.00 5.00 15.00
8558320 2013/1 12051 Pedro Davi Drugowick Ferreira 23.50 24.00 7.50 55.00
8963322 2014/1 12051 Pedro Ferreira Barchi 26.25 21.00 2.50 49.75
8071384 2012/1 12051 Pedro Uther Dantas Trajano
8012561 2012/1 12051 Rafael Angotti Miranda 10.00 15.00 7.50 32.50
8560452 2013/1 12051 Rafael Ferreira Caetano 15.75 8.00 2.50 26.25
8013350 2012/1 12051 Rafael Henrique de Meletti 16.25 17.00 7.50 40.75
8963743 2014/1 12051 Rafael Sammarco Branco Junior 19.75 24.50 11.25 55.50
8557382 2013/1 12051 Rebeca Junqueira Camillo de Carvalho 20.00 10.00 8.75 38.75
8014768 2013/1 12051 Richard Henrique Martins da Cunha 17.75 12.00 10.00 39.75
8963527 2014/1 12051 Santos Telfo Rojas Zegarrundo 12.00 11.00 11.25 34.25
8558208 2013/1 12051 Thais Haddad 22.75 21.00 8.75 52.50
8012130 2012/1 12051 Thiago Andrade Martiniano da Silva 6.50 14.00 5.00 25.50
8557569 2013/1 12051 Thomaz Lopes Macetti 16.25 13.00 2.50 31.75
8558282 2013/1 12051 Vinicius Querino Andraus 16.75 20.00 5.00 41.75
8963423 2014/1 12051 Vitor Fernandes Jaguanharo Carvalho 17.25 18.00 10.00 45.25
8557430 2013/1 12051 Viviane da Silva Dilly 18.50 11.00 7.50 37.00