Mobile Phones and Gender Inequality: Can We Hear Her Now?

While the growth of mobile phones is undeniably impressive, when we look at issues more closely, mobile phones are far from being the panacea that some purport it to be. This master thesis [PDF] by Kari Mackey adds to a literature that examines the relationship between mobile phones and gender inequality. 

Here’s the abstract: 

Are mobile phones the best vehicle for reducing gender inequality in the developing world? ICT experts champion the use of mobile phones to improve women’s lives, and various stakeholders have invested millions of dollars to launch mobile phone programs for women. Yet, given high female illiteracy rates, patriarchal societies, and other structural and cultural barriers in developing countries, many scholars contend that limited access to ICTs can perpetuate gender inequality. Rooted in the theory that women’s empowerment and equality are inseparable and necessary components for the realization of sustainable economic and social development, this paper aims to determine if stakeholders are jumping on the mobile phone bandwagon too soon by using a multivariate regression of cross national data to demonstrate whether or not mobile phones fall short of advancing women at the same rate that men develop.

And a snapshot from the conclusion: 

According to this study, mobile phones alone are not enough to reduce gender inequality. In fact, there appears to be no relationship between mobile phones and gender inequality, or one particular vehicle that is shown to be best at closing the gender gap. Rather there seems to be various moving parts working in unison. While increasing women’s literacy, reducing religious favoritism, and strengthening democracy are demonstrated by this study to be statistically significant contributors to greater gender equality, this research was limited in scope. There are 40 surely other variables out there, such as cultural attitudes, affecting gender inequality that have yet to be put through the rigorous test of statistical analysis. In order to determine what they are, it is clear that better data and additional scholarship are needed.