When a disaster strikes, whether it is due to a natural phenomenon such as a hurricane or an earthquake, or a manmade conflict, women and men are not affected in the same way. The inequalities that exist in a society are likely to be amplified in a disaster, especially if gender is not properly understood as a factor.
The Human Development Report 2019 highlights that gender disparities remain among the most persistent forms of inequality across all countries and gender inequality is one of the greatest barriers to human development.
In this blog series, the Connecting Business initiative (CBi) looks at why such inequalities are amplified in disaster settings and what actions can be taken by stakeholders, including the private sector, to mitigate this.
What is Gender?
Gender and sex are not the same, but are commonly confused with one another. Sex refers to the biological characteristics pertaining to males and females. Gender, on the other hand, is the cultural and social construct that assigns certain status, roles and responsibilities to males and females in a society.
In other words, gender refers to the attitudes, feelings, and behaviours that a given culture associates with a person’s biological sex. Gender roles are therefore learnt.
The Impact of Gender in Disaster Management
Disasters do not discriminate, but their impact does. Looking at disaster mortality (see graph below), women are often disproportionately affected – and in some cases up to nine times more likely to die. The graph shows data from seven disasters from Asia in which sex and age disaggregated data was available. The gendered impact of disasters is context specific and has a connection to the overall gender inequality situation of a society. It is important to have sex and age disaggregated data available in disaster, to know who is affected.
Why does gender influence the outcome of disasters? There are three main reasons.
First, we are often dealing with gender data bias. In the past few years, as awareness around gender bias has grown, numerous articles and conversations have taken place to shine the spotlight on how the world tends to have a structural bias towards men. Gender-bias data treats men as the default and women as atypical – and it is life threatening, as data not only describes the world, but is being used to shape it.
One everyday example is from the automobile industry. Cars continue to be designed to the dimensions of an average man and crash dummies, used in research to improve car safety, are made in the shape of a man. We therefore have data on car safety that holds a strong gendered data bias. As a result, women are 47% more likely to be seriously injured in a car crash in comparison to men – despite the fact that men are more likely to be involved in a car crash.
This applies to disaster management as well: assets, and therefore losses, are more often registered under the names of the man of the family, and interviews for damage and needs assessments continue to overrepresent heads of the households (men), despite the fact that the man is often the most absent person at home and hence not always the best person to represent the needs of the entire family. This also means we often do not understand the impact on women even if they are the most affected.
In early warning systems (EWS), for example, women and men access, process, interpret and react to alerts in different ways. The alert communications, however, tend to favor male realities and behaviors. For example, EWS increasingly favors mobile devices, but they are more accessible to men than for women; GSMA states in its recent report that the gender gap in mobile internet use in low- and middle-income countries remains substantial, with over 300 million fewer women than men accessing the internet on a mobile. Lower access to education (and therefore to literacy), the “standard” alert timing often occurring when women are cooking or occupied in childcare activities, the overall responsibility of children or the elderly while reacting to the alerts, and alert communication directing people to shelters even if they do not have protection measures in place, further ignores female realities and disrupts women's real access to standard EWS.
Second, gender inequalities that exist in the society increase vulnerability to disasters, heighten exposure to risk and restrain capacity, often resulting in a post-disaster downward spiral of poverty and a widened poverty gap between women and men. Different inequality structures, such as access to education, land ownership and gender wage gap, contribute to poverty and disaster risk as poverty, for example, drives people to live in areas that may be exposed to floods or in buildings constructed with poor housing materials more likely to be damaged in a hurricane or an earthquake.
Third, women tend to be excluded from decision-making at all levels and have lower decision-making power in most societies. However, women can be powerful agents of change and play a key role in building resilience within households, the society and the economy.
What can be done to address gender inequalities amplified by disasters?
The international community recognizes the importance of gender in disaster management, and gender is recognized as an essential factor in the Sustainable Development Goals (SDGs), the Sendai Framework for Disaster Risk Reduction, and the Agenda for Humanity.
To turn such frameworks into a reality, all stakeholders – from governments to civil society, communities to the United Nations, and academia to the private sector – all have a role to play.
Why is this important for the private sector?
Stay tuned for our next blog, where we will talk more about the role of the private sector, and ask questions such as:
What sectors of the economy are the ones that disasters hit hardest?
What is the role of the Micro, Small & Medium Enterprises (MSMEs) and the business sector in addressing poverty and making communities more resilient?
How can gender considerations help businesses be more resilient to disasters?
Photo Credit: UNDP Haiti/Pierre Michel Jean