Data Driven Detroit (D3) is proud to count among its staff a number of members with a history of doing data-driven and socially conscious work. Today we profile the work of Kat Hartman, one of D3’s Research Analysts and the head of our Communications Team. Hartman, a graduate of the University of Michigan School of Art and Design’s Master of Fine Arts program, has worked in Ethiopia, Tanzania, and Botswana as a graphic designer for health campaigns by government and non-government organizations. She is interested in data-driven design, including surveying her target audience to create the most effective and accessible designs possible. Originally brought on to D3 for the One D Scorecard, Hartman now focuses on enhancing public accessibility through data visualizations. Her ongoing projects include the Urban Innovation Exchange.
In 2011, Hartman coauthored an analysis of Botswana’s child labor situation (Botswana’s Current Child Labour Issues – Where Do We Stand and Where Do We Go From Here?) for the United Nations’ Children’s Fund, better known as UNICEF. Painting an accurate picture of the current state of child labor in Botswana is complicated from the very start, thanks to definitions of “child labor” that differ from each other depending on the source. In order to discuss child labor usefully, we must first have a precise definition for it. Child labor is easy to imagine, but it’s hard to operationalize a definition for it. If we think of child labor as “young children having to do hard labor”, how young must the child be, and how hard must the labor be, in order for us to take issue with it? We must also be sensitive to the cultural and economic realities of developing nations, without succumbing to moral relativism that might excuse harmful behavior.
The report found that, while most of Botswana’s children were generally safe from exploitation through child labor, a significant minority of the population was at considerable risk: “The average number of hours worked by those [children who are] actually working is over 24 hours per week. More specifically, approximately 50% of these children are below the age of fourteen. This is in clear violation of both international and national labor legislation.” The authors also discuss several approaches to reducing child labor: poverty alleviation, education, policy development, raising civic awareness, capacity building, and additional research.
The report also quotes the UN’s Central Statistical Office to describe the tension between the need for data in policy-making and the difficulty in gathering certain kinds of data:
There is a widespread agreement that policy that is “evidence-based” – i.e. based on facts – is likely to be more effective and better targeted than policy that is not based on hard data. Unfortunately, the very nature of child labor – and, in particular, the fact that it is often done in the privacy of the home or family business rather than in the more public spheres – means that without special studies government will not have good knowledge of its nature and extent…
That sentiment rings true to us here at Data Driven Detroit: our best policies, on the local, state, and national level, are not those that are driven by ideology or even so-called “common sense,” but by rigorously verifiable evidence.
UNICEF went on to publish a detailed analysis of the article’s results (Child Work and Child Labor in Botswana), further developing the topics, findings, and solutions presented in Hartman’s report.