Gender Statistics

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Over the years, the world has been embracing statistics as a tool for development. What statistics does is that it gives facts and figures that aid in decision making. This has brought us into an era where decisions are not made blindly and policies being put in place, or revised, work better due to evidence-based decision making. As we familiarize ourselves more with statistics, we realize that factoring in aspects of age, gender, geographical locations, among others, gives a clearer picture of the data being collected. You will find that what has a positive effect on women has a negative or neutral effect on men; that what affects the young might not affect the old; or that a certain issue experienced by someone in Western Kenya might not be relevant to individuals at Eastern Kenya. For the Sustainable Development Goal (SDG) 5, achieve gender equality and empower all women and girls, to be achieved, we first require sex-disaggregated data. This will ensure that decisions made on gender are backed up by facts.

Developing Gender Statistics: A practical tool prepared by UNECE Task Force on Gender Statistics Training for Statisticians states that Gender Statistics are the basis for analysis to assess differences in the situations of women and men and how their conditions are changing or not. In this way, gender statistics raise consciousness and provide the impetus for public debate and change. Gender statistics are also required for research to support the development and testing of explanations and theories to understand better how gender operates in a society. All of these uses form the basis for developing policies to foster greater gender equality. Furthermore, gender statistics are needed to monitor and evaluate the effectiveness and efficiency of policy developments.

Gender statistics is mainly sex-disaggregated data. The disaggregation is in the social, economic, political aspects, among others. It helps us determine which gender requires to be given attention in a particular case. Take, for example, a case where in a certain locality, the majority of the population being affected by malaria are the women. After careful observation, it is realized that the women are at a higher risk because the path they use to go to fetch water has a stagnant pond infested by mosquitoes which are known for spreading malaria. The duty to fetch water is left solely to the women, meaning the men rarely go to the river. The decision to be made here will be to do away with the pond. If the data was not disaggregated by sex, the decision would have been most likely to provide more mosquito nets, mosquito repellants and the likes to the locality. As much as this would have helped, it would not have eliminated the main cause of the high number of malaria cases. In this case, we see that different factors that are only present in the lives of women affect the well-being of the community. The same goes for the male population.

SDG 5 calls for empowerment of all women and girls. With gender statistics, we are only decisions and policies away from achieving the goal. At Considr, we are champions of gender statistics and as we work together with different stakeholders in the gender sector, we are hopeful that come the year 2030, SDG 5 will be fully achieved, and if not, almost fully achieved.



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