Much of the information that changes the world today comes from data from the collection of statistical studies on specific topics — including gender gaps.
So-called “developed countries” have invested in plans that involve such data collection. For example, if Google were a country, geolocation platforms to expand COVID-19 information would be available. However, many countries worldwide lack sufficient data to guide their plans and monitor results.
Therefore, for governments to respond adequately to gender equality issues, such as income disparities or the prevalence of gender-based violence, they need data to inform their decision-making.
The collection and screening of information is not a fast process. In many places, data is outdated, of low quality, or simply does not exist. In Latin America and the Caribbean, as well as in other underdeveloped areas and countries, the lack of reliable data and statistics is no exception.
A new study by Open Data Watch, in collaboration with the United Nations Economic Commission for Latin America and the Caribbean (ECLAC), revealed that the region suffers the worst gaps in more than half of the gender indicators. Disparities exist across all development issues, from the number of opportunities to the level of segregation, and most of these indicators have not been updated for more than two years.
According to the report, data mapping was needed to identify these gaps in five Latin American and Caribbean countries: Colombia, Costa Rica, Jamaica, Dominican Republic, and Paraguay. In this study, the variables to be documented for the well-being of women and girls were: health, education, economic opportunities, political participation, human security, and the environment. Besides, the analysis identified important data gaps in specific national and international databases.
In terms of gender indicators, the study covered 93 gender indicators, 84 included in the Sustainable Development Goals (SDGs). The lack of data was visible: almost a third of the indicators were missing from the five countries’ national databases, and a quarter was missing from international databases and organizations. Other indicators are available in the current databases but are not disaggregated by sex, making such data useless for addressing gender-specific issues.
Less data, more gaps in gender indicators
Health indicators may be the most studied among the gender indicators; however, not in other development variables. The most significant disparities in gender data gaps are environmental indicators such as housing adequacy, access to water, sanitation, transportation services, exposure to indoor pollution, and natural disasters. And 93% of these indicators lack data disaggregated by sex or have no data at all.
It is not surprising that public policies do not exist if one does not know what problems exist since, in order to implement political programs that address gender inequality, data disaggregated by sex are fundamental.
For example, data on access to health services can help understand whether women of reproductive age have adequate access to safely managed health services. Similarly, sex-disaggregated information on household access to electricity or gas for cooking can help us identify whether women or girls may be exposed to indoor air pollution.
The algorithms will not come to us
In addition to sex-disaggregated data, ensuring that the information is timely is also critical for measuring progress and developing specific public policies. Open Data Watch revealed that the largest proportion of the five countries’ indicators were years old, as they were last updated in 2017.
Paraguay, Colombia, and Costa Rica have the most up-to-date bases; however, some are more than nine years old and have not been updated. Almost as if Tik Tok or Instagram stories did not exist in our lives.
While all five countries studied have either a comprehensive national development plan or a gender equality plan to increase women’s quality of life and well-being, the report found that most lack time-bound goals and objectives linked to specific gender variables.
For example, in the case of Colombia, public policies have included the Pact for Women’s Equity in their development plan, which provides for measures to promote women’s autonomy in the physical, economic, political, and educational dimensions. The goal is consistent with SDGs indicators and proposes measurable metrics to monitor its objectives. However, many of the available indexes still have the same problem that Open Data Watch initially identified: they do not conform to international standards or lack data disaggregated by sex.
The problem of information is like a dragon biting its own tail for women in Latin America and, consequently, for many migrants arriving in the United States. Good plans will get nowhere without useful data, especially disaggregated by sex.
The report reveals that along with time-bound strategies to improve women’s and girls’ conditions, countries should adopt specific targets to improve the quality and availability of gender data.
Gaps in international databases should concern the UN, but national statistical offices are the global statistical system’s foundation. That is when we ask ourselves, who should push for data, the chicken or the egg, national governments or international organizations like the UN.
Perhaps the UN, with its leadership and support from the international community, can produce the fundamental indicators needed to close the equality gaps faced by women, girls, and other vulnerable groups within their countries and around the world. Data has now become another worrying variable that women must fight for and demand their rights.