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Child Marriage in TogoChild marriage is a very prevalent problem in Togo, a country in West Africa. In Togo, approximately 22% of girls under the age of 18 are married. Despite a large number of child marriages, there are many social and political aspects of Togolese society that propel child marriage in Togo. Here are five reasons child marriage continues in Togo.

  1. Poverty is one of the leading causes of child marriage in Togo. As one of the world’s poorest countries, more than 30% of the Togolese population faces extreme poverty. Many impoverished families arrange marriages for their daughters to help the family’s financial situation. Poverty also influences other problems that drive child marriages in Togo such as access to education and health.
  2. Health Issues: Many children in poverty predominantly suffer from health issues. Togo has a 50% life expectancy rate for children under 5. The death of a child for a family in poverty can create financial strain primarily when families rely on children to do housework or farming. The financial stress often pushes parents to marry their daughters as soon as possible to ease the financial strain. This forces many young girls into arranged marriages with strangers.
  3. Lack of Education: Education also plays a crucial role in driving child marriage. Young girls in Togo are married off if they do not reach a certain level of education. This especially impacts young girls in poverty who cannot go to school because they are helping their parents raise their siblings, do housework or farm. Almost half of the illiterate Togolese women in their early 20’s were married before the age of 18.
  4. Financial Dependency: Establishing financial independence for young women is essential for ending child marriages in Togo. Although many families marry their young children as a means to escape poverty, child marriage is counterproductive to ending the cycle of poverty for young girls in Togo. A girls’ rights advocate from Togo for PLAN International, Yolande, explains that marriage, especially at a young age, keeps girls from being financially independent. She states that “Most of the married girls in Togo come from poor families. Marriage keeps girls in poverty and prevents them from becoming financially empowered and flourishing as individuals.”
  5. No Political Support: Even though poverty often leads to child marriage in Togo, the lack of policies prohibiting child marriage allows child marriage to continue. It is illegal in Togo for girls to marry under the age of 18. However, girls can marry before the age of 18 with parental consent. Without the proper legislation for the prohibition of child marriage in Togo, child marriage will continue.

Working Toward a Solution

Many organizations are working to end child marriage in Togo. Women’s WorldWide Web (W4) is an online crowdfunding platform working specifically in Togo. They promote education and the empowerment of women. Their programs aim to provide income-generation for women who have been affected by young marriage. This helps women gain financial independence and create sustainable livelihoods for themselves.

Togo’s child marriage prevalence is mainly due to poverty itself, the rippling effects and the lack of government support for child marriage prohibition legislation. However, there are many organizations like W4.org fighting for these young women and their rights. With their efforts and the push for proper legislative policies, young Togolese girls may one-day gain financial and personal independence.

– Kaitlyn Gilbert
Photo: Flickr

Phone Data

Literacy is one of the most significant contributing factors to eradicating poverty. Telenor, a Norwegian research group, believes it has found a way to measure literacy rates in developing countries using mobile phone data.

Currently, an estimated 750 million people around the world are unable to read and write. Two-thirds of these people are women, according to MIT Technology Review. UNESCO studied the effects of illiteracy in South American communities and found that illiteracy correlates to higher unemployment rates, poor health, exploitation and human rights abuse.

In order to address the growing concern of widespread illiteracy in developing countries, Telenor, led by Pål Sundsøy, developed a machine-learning algorithm to figure out which communities have the highest rates of illiteracy.

Using mobile phone data, Telenor’s algorithm evaluates a variety of factors to predict literacy rates in developing countries including the location of calls, number of incoming versus outgoing text messages and the diversity of social contacts.

When evaluating the probability of illiteracy, geographic location is one of the most deciding factors. Sundsøy believes that the algorithm is able to identify slum areas where economic development is low and illiteracy is high by analyzing where calls are placed.

Additionally, a higher quantity of outgoing messages and a lower number of incoming messages may also hint at illiteracy. Telenor’s model takes this information into consideration since people do not typically send texts to contacts who they know can’t read.

The diversity of an individual’s social network is also a helpful indicator of literacy since those who are illiterate are more likely to concentrate their efforts on communicating with a few people. The relationship between the diversity of social contacts and illiteracy is also supported by a strong three-way correlation between economic well-being, illiteracy and diversity of social contacts.

By identifying which communities are at risk for low literacy rates, Telenor’s mobile phone data algorithm can make literacy programs more effective in developing countries.

The National Literacy Programme in Namibia (NLPN) states that their main challenge to boosting literacy rates is limited funding for the program. Implementing Telenor’s algorithm would make a significant impact on programs like NLPN that have finite resources by helping organizations to identify and allocate resources to communities that have a higher concentration of illiterate people.

While regional and gender disparities continue to persist in current illiteracy data, the development of powerful resources like Telenor’s algorithm will help raise literacy rates in developing countries and make it easier for literacy programs to target those who at a greater disadvantage.

Daniela N. Sarabia

Photo: Pixabay