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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A propensity score approach in the impact evaluation on scientific production in Brazilian biodiversity research: the BIOTA Program

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Autor(es):
Colugnati, Fernando A. B. [1, 2] ; Firpo, Sergio [3] ; Drummond de Castro, Paula F. [1] ; Sepulveda, Juan E. [4] ; Salles-Filho, Sergio L. M. [1]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Estadual Campinas, Inst Geosci, Dept Sci & Technol Policy, Lab Studies Org Res & Innovat GEOPI, BR-13083970 Campinas, SP - Brazil
[2] Univ Fed Juiz de Fora, Dept Clin Med, BR-36036330 Juiz De Fora, MG - Brazil
[3] Sao Paulo Sch Econ FGV, BR-01332000 Sao Paulo - Brazil
[4] Univ Estadual Campinas, Inst Econ, BR-13083857 Campinas, SP - Brazil
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: SCIENTOMETRICS; v. 101, n. 1, p. 85-107, OCT 2014.
Citações Web of Science: 6
Resumo

Evaluation has become a regular practice in the management of science, technology and innovation (ST\&I) programs. Several methods have been developed to identify the results and impacts of programs of this kind. Most evaluations that adopt such an approach conclude that the interventions concerned, in this case ST\&I programs, had a positive impact compared with the baseline, but do not control for any effects that might have improved the indicators even in the absence of intervention, such as improvements in the socio-economic context. The quasi-experimental approach therefore arises as an appropriate way to identify the real contributions of a given intervention. This paper describes and discusses the utilization of propensity score (PS) in quasi-experiments as a methodology to evaluate the impact on scientific production of research programs, presenting a case study of the BIOTA Program run by FAPESP, the State of So Paulo Research Foundation (Brazil). Fundamentals of quasi-experiments and causal inference are presented, stressing the need to control for biases due to lack of randomization, also a brief introduction to the PS estimation and weighting technique used to correct for observed bias. The application of the PS methodology is compared to the traditional multivariate analysis usually employed. (AU)

Processo FAPESP: 08/58628-7 - Avaliação de Programas da FAPESP: desenvolvimento e aplicação de métodos para avaliar impactos e para criar avaliação continuada
Beneficiário:Sergio Luiz Monteiro Salles Filho
Modalidade de apoio: Auxílio à Pesquisa - Regular