Donatien Beguy, African Population and Health Research Center
The truth is that data in Africa are not produced on time, not frequently enough, are of poor quality and aren’t accurate. This makes it difficult to make data driven decisions.
Religious teachers can feel uncomfortable explaining the science of evolution to their pupils.
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Many South African teachers don’t accept the theory of evolution. They feel deeply conflicted when they have to teach it to their pupils as part of the life sciences curriculum.
Citizen scientists have a great deal to contribute.
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The Australian census is just one way to gather data on people. We also freely give out information in other ways that can be used to study many things, and maybe even predict an election result.
Sampling is a powerful scientific tool - when it’s used honestly.
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Some water researchers are ignoring the evidence offered by sampling if it doesn’t fit their preconceived notions. But science should always be honest and open.
Ranking organisations call the shots about which universities are ‘best’.
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It is arrogant and hypocritical for ranking institutions to declare that they’re building Africa’s legacy or its global partnerships on the continent’s behalf.
In-depth surveys allow governments to drill their understanding down to street level.
Image courtesy GCRO/Clive Hassall
Without data, people don’t know what to believe or whom to trust. Empirical, thorough data collected by academics can help to fill important governance gaps.
Education groups need to make sure they use data to make useful comparisons that are in no way misleading.
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Analyzing electronic data from many doctors’ experiences with many patients, we can move ever closer to answering the age-old question: what is truly best for each patient?
Demand is growing for statistical ecologists to research climate change. Rapidly growing mega-cities in Africa, like Lagos, face the highest risks.
Reuters/Akintunde Akinleye
By linking censuses through time or by combining other information with the census, many more important policy questions can be answered than if we used one dataset alone.
When complex, dense information is presented visually it can make a huge difference.
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Honorary Enterprise Professor, School of Population and Global Health, and Department of General Practice and Primary Care, The University of Melbourne
Former postdoctoral researcher on machine learning applied to chemical engineering and currently science communicator for the National Museum of Emerging Science and Innovation (Miraikan), University of Tokyo