Portuguese Women in Science and Technology (S&T): Some Gender Features Behind MSc. and PhD. Achievement

Chagas Lopes, Margarida (2006): Portuguese Women in Science and Technology (S&T): Some Gender Features Behind MSc. and PhD. Achievement.

Abstract

Portuguese Women in S&T - Abstract Most research based upon institutional data has been dealing with the situation of Portuguese women in Science and Technology as if it would be a homogeneous set. Quite the opposite, whilst women in science are performing increasingly better than men since the early school ages, indeed a Portuguese idiosyncrasy comparing to other PISA countries, they are still underrepresented in most technological fields. Among other determinants this feature ascribes most Portuguese graduate women to occupations where career prospects are quite uncertain and worse than men's in the same qualification levels. Either by career requirements or in reason of one's seeking to improve knowledge and apply to a better job, post-graduation undergoing appears therefore as an obvious way out strategy. Nevertheless, even high skilled Portuguese women in scientific occupations face generally weaker opportunities and have to take more time than men to achieve a post-graduation. A Project in the behalf of Portuguese Foundation for Science and Technology provided us longitudinal data on PhD. and MSc. Trajectories within four Portuguese universities. By investigating such a data on the basis of a Hazard-Survival Model and Cox Regression Analysis we could identify some of the main gender determinants behind obstacles and time to achieve MSc (author abstract)

• Item Type: MPRA Paper
• Language: English
• Keywords: Gender and Science; Obstacles to post-graduation achievement; Hazard Survival Models; Portugal.
• Subjects: A - General Economics and Teaching > A2 - Economic Education and Teaching of Economics > A23 - Graduate; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; I - Health, Education, and Welfare > I2 - Education and Research Institutions > I23 - Higher Education ; Research Institutions; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; J - Labor and Demographic Economics > J7 - Labor Discrimination > J70 - General

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