Gender system and development in the last 20 years

Alessandra De Rose, Università di Roma "La Sapienza"
Anna De Pascale, University of Rome
Francesca Fiori, Università di Roma "La Sapienza"

Women, Development Environment: Gender refers to the differences in socially constructed roles and opportunities associated with being a man or a woman and the interactions and social relations between men and women. Gender equality and women's empowerment are human rights that lie at the heart of development. The Beijing Conference clearly established that gender equality is central to progress in development and democracy since the promotion of gender equality is both a means and an end for the enjoyment of human rights by women and men and for a sustainable development. The State of World Population 2009 (UNFPA 2009), argues that the international community’s fight against climate change is more likely to be successful if policies, programmes and treaties take into account the needs, rights and potential of women. Better use of the world's female population could increase economic growth, reduce poverty, enhance societal well-being and help ensure sustainable development in all countries. The scope of this study is to describe the macro relationship among gender system, female empowerment and social, economic and environmental indicators both in the Northern and in the Southern regions of the world. Our data cover the main topics related to gender (population increase, aging, marriage and fertility, health and survival, social status, economic resource, power) coming from different data sources (UNSTAT and EUROSTAT and related data-sets) and from thematic publications (Women’s World, MDGs, EU Report on Equality, OECD Report on Gender and Sustainable Development). Etc.). Comparative indicators are calculated separately for countries of Europe, Canada, USA, Japan, Israel, Australia and for Africa, Asia, Latin America around the year 2005, according to the available data. We performed a multidimensional descriptive analysis based on the Principal Components Analysis (PCA methods).

Presented in Poster Session 2

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