The shocking news that the population of Kibera, “Africa’s largest slum”, may not in fact be 1 million people comes as a shock mainly to people who think statistics = truth, even when the provenance of those statistics is questionable. Earlier this year I put together a bar chart which brought together a few different sources to create a picture of Kibera’s growth. Bear in mind that these figures are conservative, and that some sources randomly estimate Kibera’s population at over 1 million.
Table 1: Population Growth in Kibera 1963-2010 (Source: de Smedt, Richards and Godfrey 2003)
As the sage said, “all models are wrong, but some are useful” – which is to say that the models which Kibera’s former population estimates were based on were very wrong, but that the presence of “Africa’s largest slum” in the middle of Nairobi was very useful. It meant that international visitors (particularly the UN agencies and NGOs, many of which have their regional offices in Nairobi) didn’t have to travel very far to visit the poverty that was their raison d’etre. (Of course few of them ever bothered to travel even that far.)
So where did those figures come from? By definition the dead hand of the state doesn’t weigh too heavily on informal settlements, so even our friendly neighbourhood tax collector is of limited use. Most population estimates are extrapolations based on past growth or statistical surveys of a limited section of the population; these approaches have fairly obvious holes in, but they are useful. The problem comes when people with more limited understanding accept those figures as definitive and start to reuse them.
In the absence of actual data (such as an official census), NGO staff make a back-of-envelope estimate in order to plan their projects; a postgraduate visiting the NGO staff tweaks that estimate for his thesis research; a journalist interviews the researcher and includes the estimate in a newspaper article; a UN officer reads the article and copies the estimate into her report; a television station picks up the report and the estimate becomes the headline; NGO staff see the television report and update their original estimate accordingly.
All statistical hell breaks loose, and the population of Kibera leaps ever higher. Every actor at every stage has a motive for using the upper end of that initial estimate, rather than more conservative figures – planning, funding, visibility, and so on – but no single person is responsible for inflating the figure progressively further from reality. Eventually – census! – followed by headlines trying to explain why the previous figures were so high, and what this means for the people who live there (and the rest of the country).
This is not the problem. The problem is that any further analysis – in health, education, sanitation – using that inflated figure as a basis is also going to be wrong. The solution, as ever, is to invest in better data collection rather than relying on policy wonks to imagineer your slum. Mikel reminds us that previous Kibera mapping efforts came up with more accurate estimates long before the census: nobody listened, of course, proving once again that the problem is not the technology – the problem is everything else.