Exponential projections of brazilian science: models and quantitative analysis of national scientific production published in the last 30 years
DOI:
https://doi.org/10.5433/1981-8920.2021v26n1p53Keywords:
Scientific production, Segmented regression, Lattes platform, BrazilAbstract
Introduction: Introduction: The study examines the growth of Brazilian scientific production in the period 1990 - 2017, based on a sample composed of approximately 5.8 million scientific articles indexed to the Lattes platform. Points of change were identified in the exponential growth rate of scientific production in eight major areas of knowledge. Such points, estimated through an exponential growth model, segment scientific production in periods marked by constant growth rates. The periodization of results facilitates the contextualization of scientific production in the face of scientific policies implemented in recent decades.Objective: to produce indicators for inputs for discussions on the recent performance of national science and to contribute to analyzes based on information made available on the Lattes Platform.
Methodology: highlights the Lattes Platform as an essential database for understanding Brazilian science and, based on data collection, applies segmented regression models that include the quantitative transformations of scientific activity over the analyzed period.
Results: They found that the total of Brazilian scientific production grew at an exponential annual rate of 6.61% between the years 1990 to 2017, however observing a slowdown in the growth of scientific production in the areas evaluated in the first half of the 2000s. Health and Biological Sciences areas registered the lowest growth rates.
Conclusions: reinforce the relevance of the Lattes Platform in assessments of national scientific production and point out new paths and questions for future research that may contribute to the understanding of the status quo of Brazilian scientific makings.
Downloads
Download data is not yet available.
References
ABITEBOUL, S.; BUNEMAN, P.; SUCIU, D. Gerenciando dados na Web. Rio de Janeiro: Campus, 2000.
ACEMOGLU, D.; AKCIGIT, U., ALP, H., BLOOM, N., KERR, W. Innovation, reallocation, and growth. American Economic Review, v. 108, n. 11, p. 3450-91, 2018.
BORNMANN, L.; MUTZ, R. Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, v. 66, n. 11, p. 2215-2222, 2015.
BORNMANN, L.; WAGNER, C.; LEYDESDORFF, L. BRICS countries and scientific excellence: A bibliometric analysis of most frequently cited papers. Journal of the Association for Information Science and Technology, v. 66, n. 7, p. 1507-1513, 2015.
BRUSILOVSKIY, E. The piecewise regression model as a response modeling tool. Philadelphia: University of Pennsylvania, 2004.
MCZGEE, V.; CARLETON, W.T. Piecewise regression. Journal of the American Statistical Association, Issue 331, p. 1109–1124, 1970.
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO (CNPq). Termo de Adesão e de Condições de Uso Sistema de Currículos da Plataforma Lattes. Brasília: CNPq, 2020. Disponível em: https://wwws.cnpq.br/cvlattesweb/pkg_cv_estr.termo. Acessado em 25 Jan. de 2020.
CROSS, D.; THOMSON, S.; SINCLAIR, A. Research in Brazil: A Report for CAPES by Clarivative Analytics. São Paulo: Clarivative Analytics, 2017.
DE SOLLA PRICE, D. J. O desenvolvimento da ciência: análise histórica, filosófica, sociológica e econômica. Rio de Janeiro: Livros Técnicos e Científicos, 1976.
DE SOLLA PRICE, D. J. Little science, big science. New York: Columbia University, 1963.
DIAS, T. M. R.; MOITA, G. F. Um retrato da produção científica brasileira baseado em dados da Plataforma Lattes. Brazilian Journal of Information Science: research trends, v. 12, n. 4, p. 62-74, 2018.
DRORI, G. S.; MEYER, J.W.; RAMIREZ, O.F.; SCHOFER, E. Science in the modern world polity: Institutionalization and globalization. Palo Alto: Stanford University Press, 2003.
EGGHE, L.; RAO, R. Classification of growth models based on growth rates and its applications. Scientometrics, v. 25, n. 1, p. 5-46, 1992.
HAYNE, L. A.; WYSE, A. T. S. Econometric Analysis of Brazilian Scientific Production and Comparison with BRICS. Science, Technology and Society, v. 23, n. 1, p. 25-46, 2018.
KELLNER, A. W.A. Editors of Brazilian journals-a hard life that is getting harder! Anais da Academia Brasileira de Ciências, v. 89, n. 1, p. 1-2, 2017.
LANE, J. Let's make science metrics more scientific. Nature, v. 464, n. 7288, p. 488, 2010.
LERMAN, P. Fitting segmented regression models by grid search. Journal of the Royal Statistical Society: Series C, v. 29, n. 1, p. 77–84, 1980.
MINNITI, A.; VENTURINI, F. The long-run growth effects of R&D policy. Research Policy, v. 46, n. 1, p. 316-326, 2017
MITCHELL, R. Web scraping with Python: Collecting more data from the modern web. 2.ed. Newton: O’Reilly Media, 2018.
MUELLER, S.P.M. A publicação da ciência: áreas científicas e seus canais preferenciais. DataGramaZero: Revista de Ciência da Informação, v.6, n.1, p.1-12, 2005.
MUGNAINI, R.; DAMACENO, R. J. P.; DIGIAMPIETRI, L. A.; MENA-CHALCO, J. P. Panorama da produção científica do Brasil além da indexação: uma análise exploratória da comunicação em periódicos. Transinformação, v.31, e190033, p.22-36, 2019.
NELSON, R. R. The Simple Economics of Basic Scientific Research. Journal of Political Economy, v. 67, n. 3, p.297–306, 1959. Disponível em: http://jstor.org/stable/1827448. Acesso em: 22 Jan. 2020.
PERLIN, M. S.; SANTOS, A.P; IMASATO, T.; BORESTEIN, D.; SILVA, S. The Brazilian scientific output published in journals: A study based on a large CV database. Journal of Informetrics, v. 11, n. 1, p. 18-31, 2017.
CORE TEAM. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2020.
RODRIGUES, R. S.; QUARTIERO, E.; NEUBERT, P. Periódicos científicos brasileiros indexados na Web of Science e Scopus: estrutura editorial e elementos básicos. Informação & Sociedade, v. 25, n. 2, p.26 – 42, 2015. Disponível em: https://periodicos.ufpb.br/ojs/index.php/ies/article/view/117. Acesso em: 23 Jan. 2020.
SAS, S. STAT 9.3 User’s guide. Cary, New York: SAS Institute Inc, 2011.
SIDONE, O.J.G.; HADDAD, E.A.; MENA-CHALCO, J.P. A ciência nas regiões brasileiras: evolução da produção e das redes de colaboração científica, Transinformação, v. 28, n. 1, p. 15-32, 2016.
SOUZA, J. F. Captchas Negated by Python reQuests. CNPQ GitHub repositor; GitHub, 2018. Disponível em: https://github.com/josefson/CNPQ. Acessado em 24 Jan. 2020.
SOUZA R. F.; SABINO, W. GetLattes: Read and process data from Lattes currriculum platform. Zenodo, 2020.
TAGUE, J.; BEHESHTI, J.; REES-POTTER, L. The law of exponential growth: evidence, implications and forecasts. Library Trends, v.30, n.1, p.97 – 114, 1981.
SPERBERG-MCQUEEN, C. Extensible Markup Language 1.0. New York: World Wide Web Consortium, 2000. Disponível em http://www. w3. org/TR/2000/REC-xml-20001006, Acessado em: 22 Jan. 2020.
VAN RAAN, A. On growth, ageing, and fractal differentiation of science. Scientometrics, v. 47, n. 2, p. 347–362, 2000.
WILSDON, J. Knowledge, networks and nations: Global scientific collaboration in the 21st century. London: Royal Society Policy document, 2011.
ZHANG, L.; POWELL, J.W.; BAKER, D. P. Exponential growth and the shifting global center of gravity of science production, 1900–2011. Change: The Magazine of Higher Learning, v. 47, n. 4, p. 46-49, 2015.
ACEMOGLU, D.; AKCIGIT, U., ALP, H., BLOOM, N., KERR, W. Innovation, reallocation, and growth. American Economic Review, v. 108, n. 11, p. 3450-91, 2018.
BORNMANN, L.; MUTZ, R. Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, v. 66, n. 11, p. 2215-2222, 2015.
BORNMANN, L.; WAGNER, C.; LEYDESDORFF, L. BRICS countries and scientific excellence: A bibliometric analysis of most frequently cited papers. Journal of the Association for Information Science and Technology, v. 66, n. 7, p. 1507-1513, 2015.
BRUSILOVSKIY, E. The piecewise regression model as a response modeling tool. Philadelphia: University of Pennsylvania, 2004.
MCZGEE, V.; CARLETON, W.T. Piecewise regression. Journal of the American Statistical Association, Issue 331, p. 1109–1124, 1970.
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO (CNPq). Termo de Adesão e de Condições de Uso Sistema de Currículos da Plataforma Lattes. Brasília: CNPq, 2020. Disponível em: https://wwws.cnpq.br/cvlattesweb/pkg_cv_estr.termo. Acessado em 25 Jan. de 2020.
CROSS, D.; THOMSON, S.; SINCLAIR, A. Research in Brazil: A Report for CAPES by Clarivative Analytics. São Paulo: Clarivative Analytics, 2017.
DE SOLLA PRICE, D. J. O desenvolvimento da ciência: análise histórica, filosófica, sociológica e econômica. Rio de Janeiro: Livros Técnicos e Científicos, 1976.
DE SOLLA PRICE, D. J. Little science, big science. New York: Columbia University, 1963.
DIAS, T. M. R.; MOITA, G. F. Um retrato da produção científica brasileira baseado em dados da Plataforma Lattes. Brazilian Journal of Information Science: research trends, v. 12, n. 4, p. 62-74, 2018.
DRORI, G. S.; MEYER, J.W.; RAMIREZ, O.F.; SCHOFER, E. Science in the modern world polity: Institutionalization and globalization. Palo Alto: Stanford University Press, 2003.
EGGHE, L.; RAO, R. Classification of growth models based on growth rates and its applications. Scientometrics, v. 25, n. 1, p. 5-46, 1992.
HAYNE, L. A.; WYSE, A. T. S. Econometric Analysis of Brazilian Scientific Production and Comparison with BRICS. Science, Technology and Society, v. 23, n. 1, p. 25-46, 2018.
KELLNER, A. W.A. Editors of Brazilian journals-a hard life that is getting harder! Anais da Academia Brasileira de Ciências, v. 89, n. 1, p. 1-2, 2017.
LANE, J. Let's make science metrics more scientific. Nature, v. 464, n. 7288, p. 488, 2010.
LERMAN, P. Fitting segmented regression models by grid search. Journal of the Royal Statistical Society: Series C, v. 29, n. 1, p. 77–84, 1980.
MINNITI, A.; VENTURINI, F. The long-run growth effects of R&D policy. Research Policy, v. 46, n. 1, p. 316-326, 2017
MITCHELL, R. Web scraping with Python: Collecting more data from the modern web. 2.ed. Newton: O’Reilly Media, 2018.
MUELLER, S.P.M. A publicação da ciência: áreas científicas e seus canais preferenciais. DataGramaZero: Revista de Ciência da Informação, v.6, n.1, p.1-12, 2005.
MUGNAINI, R.; DAMACENO, R. J. P.; DIGIAMPIETRI, L. A.; MENA-CHALCO, J. P. Panorama da produção científica do Brasil além da indexação: uma análise exploratória da comunicação em periódicos. Transinformação, v.31, e190033, p.22-36, 2019.
NELSON, R. R. The Simple Economics of Basic Scientific Research. Journal of Political Economy, v. 67, n. 3, p.297–306, 1959. Disponível em: http://jstor.org/stable/1827448. Acesso em: 22 Jan. 2020.
PERLIN, M. S.; SANTOS, A.P; IMASATO, T.; BORESTEIN, D.; SILVA, S. The Brazilian scientific output published in journals: A study based on a large CV database. Journal of Informetrics, v. 11, n. 1, p. 18-31, 2017.
CORE TEAM. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2020.
RODRIGUES, R. S.; QUARTIERO, E.; NEUBERT, P. Periódicos científicos brasileiros indexados na Web of Science e Scopus: estrutura editorial e elementos básicos. Informação & Sociedade, v. 25, n. 2, p.26 – 42, 2015. Disponível em: https://periodicos.ufpb.br/ojs/index.php/ies/article/view/117. Acesso em: 23 Jan. 2020.
SAS, S. STAT 9.3 User’s guide. Cary, New York: SAS Institute Inc, 2011.
SIDONE, O.J.G.; HADDAD, E.A.; MENA-CHALCO, J.P. A ciência nas regiões brasileiras: evolução da produção e das redes de colaboração científica, Transinformação, v. 28, n. 1, p. 15-32, 2016.
SOUZA, J. F. Captchas Negated by Python reQuests. CNPQ GitHub repositor; GitHub, 2018. Disponível em: https://github.com/josefson/CNPQ. Acessado em 24 Jan. 2020.
SOUZA R. F.; SABINO, W. GetLattes: Read and process data from Lattes currriculum platform. Zenodo, 2020.
TAGUE, J.; BEHESHTI, J.; REES-POTTER, L. The law of exponential growth: evidence, implications and forecasts. Library Trends, v.30, n.1, p.97 – 114, 1981.
SPERBERG-MCQUEEN, C. Extensible Markup Language 1.0. New York: World Wide Web Consortium, 2000. Disponível em http://www. w3. org/TR/2000/REC-xml-20001006, Acessado em: 22 Jan. 2020.
VAN RAAN, A. On growth, ageing, and fractal differentiation of science. Scientometrics, v. 47, n. 2, p. 347–362, 2000.
WILSDON, J. Knowledge, networks and nations: Global scientific collaboration in the 21st century. London: Royal Society Policy document, 2011.
ZHANG, L.; POWELL, J.W.; BAKER, D. P. Exponential growth and the shifting global center of gravity of science production, 1900–2011. Change: The Magazine of Higher Learning, v. 47, n. 4, p. 46-49, 2015.
Downloads
Published
2021-03-31
How to Cite
Nascimento, D. S. A., Souza, R. F., Junior, J. J. da S., & Silva, L. R. da. (2021). Exponential projections of brazilian science: models and quantitative analysis of national scientific production published in the last 30 years. Informação & Informação, 26(1), 53–73. https://doi.org/10.5433/1981-8920.2021v26n1p53
Issue
Section
Artigos
License
Copyright (c) 2021 Informação & Informação
This work is licensed under a Creative Commons Attribution 4.0 International License.
A revista se reserva o direito de efetuar, nos originais, alterações de ordem normativa, ortográfica e gramatical, com vistas a manter o padrão culto da língua e a credibilidade do veículo. Respeitará, no entanto, o estilo de escrever dos autores. Alterações, correções ou sugestões de ordem conceitual serão encaminhadas aos autores, quando necessário.
O conteúdo dos textos e a citação e uso de imagens submetidas são de inteira responsabilidade dos autores.
Em todas as citações posteriores, deverá ser consignada a fonte original de publicação, no caso a Informação & Informação.
