Economic Efficiency or Gender Equality: Conceptualizing an Equitable “Social Framing” for Economic Evaluations to Support Gender Equality in Disaster Risk- and Environmental-Management Decision-Making

• Main Author: Cheney Shreve
• Format: Article
• Language: English
• Published: MDPI AG 2016-07-01
• Series: Resources
• Subjects: cost–benefit analysis; cost effectiveness analysis; gender equality; disasters; environment; ethics; gender mainstreaming; disaggregated data
• Online Access: http://www.mdpi.com/2079-9276/5/3/25

It is unlikely that cost–benefit approaches will be effective in identifying investments that support gender equality without a relevant “social framing”. Criteria for a “social framing” are lacking, yet cost–benefit approaches often guide investment decisions for disaster risk and environmental management. Mainstream approaches typically do a poor job identifying and characterizing costs and benefits, and often fail to address distributive concerns (i.e., how costs and benefits may be distributed throughout society, to whom, etc.). Gender-blind investments may project responsibility for equality “problems” onto one sex, potentially augmenting gender inequalities and disaster risk. This article examines evidence from the gender, disaster, and development literature to identify distributive concerns and criteria for an equitable “social framing” for economic evaluations. Primary distributive concerns identified regard assumptions of women’s homogeneity, agency, “active” participation, and the influence of customary practice and displacement on disaster vulnerability. The need for a “gender-responsive” “social framing” that considers the needs of men and women in relation to one another is evident. Second, cost–benefit studies focused on gender equality concerns are reviewed and the “social framing” is critiqued. Results show most studies are not “gender-responsive”. Women’s health concerns, often exacerbated by disasters, are sidelined by assumptions regarding distributive concerns and reductive outcome measures.