On the Criteria for Receiving a Research Productivity Fellowship from the Brazilian National Council for Scientific and Technological Development in Mathematics and Statistics

Marcos Eduardo Valle, Fábio Sakuray

Abstract


The fellowship of research productivity (PQ) granted by the national council for scientific and technological development (CNPq), besides the financial support, renders a significant status among Brazilian researchers of all areas of knowledge. Consequently, both the profile and the criteria for holding a PQ fellowship become of interest to the entire Brazilian scientific community. In this paper, we model the decision criteria as a weighted sum of the scientific production and the supervisory experience of an applicant for PQ fellowship. The scientific production is measured as the number of publications grouped according to  the QUALIS system provided by the Brazilian federal agency for the improvement of higher education (CAPES). The Lattes curricula of the successful applicants for the PQ fellowship in the field of mathematics and statistics, along with the curricula of many non-PQ fellows of similar institutions, were used to estimate the criteria adopted in the last call for PQ
fellowship in category 2. By allowing a certain tolerance, the model reproduced the decision criteria within acceptable bounds using the previous and the current QUALIS systems over a database composed of 234 curricula. As a consequence, the model may help to decide whether a researcher applicant is worthy to receive a PQ fellowship. Furthermore, it confirmed the recognized value of publications in journals with an elevated rank in the QUALIS system.

Full Text:

PDF (ENGLISH)

References


D. Arruda, F. Bezerra, V. A. Neris, P. R. de Toro, and J. Wainer. Brazilian computer science research: Gender and regional distributions. Scientometrics, 79(3):651–6, 2009.

R. B. Barata and M. Goldbaum. Perfil dos pesquisadores com bolsa de produtividade em pesquisa do CNPq da área de saúde coletiva. Cadernos de Saúde Pública, 19(6):1863–1876, 2003.

V. Franc and S. Sonnenburg. Optimized cutting plane algorithm for large-scale risk minimization. Journal of Machine Learning Research, 10:2157–2192, Oct. 2009.

N. Garcia and L. Casado. Comunicado 003/2012 – área de Matemática, Probabilidade e Estatística: Atualização do webqualis. Available at: http:

//www.capes.gov.br/images/stories/download/avaliacao/Qualis_-_Matematica.pdf, 2012. Accessed on June, 2012.

S. Haykin. Neural Networks and Learning Machines. Prentice-Hall, Upper Saddle River, NJ, 3rd edition edition, 2009.

E. A. Oliveira, E. A. Colosimo, D. R. Martelli, I. G. Quirino, M. C. L. Oliveira, L. S. Lima, A. C. S. Silva, and H. Martelli-Junior. Comparison of brazilian researchers in clinical medicine: are criteria for ranking well-adjusted? Scientometrics, 90(2):429–443, 2012.

E. A. Oliveira, A. L. P. Ribeiro, I. G. Quirino, M. C. L. Oliveira, D. R. Martelli, L. S. Lima, E. A. Colosimo, T. J. Lopes, A. C. S. Silva, and H. Martelli-Junior. Profile and scientific production of CNPq researchers in cardiology. Arquivos Brasileiros de Cardiologia, 97(3):186–193, 2011.

N. C. Santos, L. F. Cândido, and C. L. Kuppens. Produtividade em pesquisa do CNPq:Análise do perfil dos pesquisadores da química. Química Nova, 33(2):489–495, 2010.

A. C. Scarpelli, F. Sardenberg, D. Goursand, S. M. Paiva, and I. A. Pordeus. Academic trajectories of dental researchers receiving CNPq’s productivity grants. Brazilian Dental Journal, 9(3):252–256, 2008.

M. A. Silveira e Pereira Neves, R. C. Antunes, E. S. R. Júnior, and C. Q. Gorgati. Evolução das bolsas de produtividade em pesquisa e dos editais universais do CNPq no programa básico de zootecnia: 2002 a 2006. Revista Brasileira de Zootecnia, 36(0):369–376, 2007.

S. Sonnenburg, G. Rätsch, S. Henschel, C. Widmer, J. Behr, A. Zien, F. de Bona, A. Binder, NewAuthor9, and V. Franc. The shogun machine learning toolbox. Journal of Machine Learning Research, 11:1799–1802, Aug. 2010.

G. A. Toffoli and S. M. S. P. Ferreira. Mapeamento da produção científica de pesquisadores brasileiros de ciências da comunicação: período de 2000 a 2009. Psicologia USP, 22(2):399–422, 2011.

V. N. Vapnik. Statistical Learning Theory. John Wiley and Sons, New York, NY, USA, 1998.

V. N. Vapnik. The Nature of Statistical Learning Theory. Springer, 2 edition, 1999.

M. Viana and M. Soares. Documento de área 2009 – Matemática, Probabilidade e Estatística. Available at: http://qualis.capes.gov.br/arquivos/

avaliacao/webqualis/criterios2007_2009/Criterios_Qualis_2008_01.pdf, 2009. Accessed on May, 2012.




DOI: https://doi.org/10.5540/tema.2014.015.03.0237

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.


Trends in Computational and Applied Mathematics

A publication of the Brazilian Society of Applied and Computational Mathematics (SBMAC)

 

Indexed in:

                       

         

 

Desenvolvido por:

Logomarca da Lepidus Tecnologia