During the 2011 World Conference on Social Determinants of Health, the Rio Political Declaration on Social Determinants of Health was adopted. The declaration expressed a global political commitment for the implementation of a social determinants of health (SDH) approach to reduce health inequities. Social determinants of health are defined by the World Health Organisation (WHO) as the conditions in which people are born, grow up, live, work and age. These conditions influence a person’s opportunity to be healthy, risk of illness and life expectancy. Social inequities in health – the unfair and avoidable differences in health status across groups in society – are those that result from the uneven distribution of social determinants. All of these drive health inequity – systematic disparities in health between social groups who have different levels of underlying social advantage or disadvantage such as food, shelter, clean water, sanitation, proper clothing and have limited access to medical care, education and finance.
Video: Dr Hans Rosling’s 200 Countries, 200 Years, 4 Minutes – use of data to visualize social determinants of health across the globe.
What does ‘development’ mean to data scientists, and how does that determine what data science can achieve within the field of international development? This essential question has been raised, in relation to certain D4D (Data for Development) projects, by some experts who further state:
Data science conducted with the aim of informing development policy must, by definition, involve an understanding of the policy area in question, and importantly the analysis must be combined with understanding of the local context. Without these characteristics, research only informs the field of data science rather than development policy.
(Taylor & Schroeder, 2015, pp. 508 & 514)
‘Data science must involve an understanding of the policy area and the local context’. Here is an interesting statement to begin with. So, let’s start with a video from the Geospatial Revolution Project.
Whistleblowers are individuals or a group of people who bring to public knowledge any information or activity that is regarded as illegal or unethical. These activities could be in several forms such as breaching company policies, corruption or threat to national security. Whistleblowing has much to do with a person’s ethics, and as a result, numerous debates arise as to whether it is allowable or not. Those in support of it maintain that it aims at protecting the public from government misconduct. Those in the opposite camp, however, argue that it breaches confidentiality (Brown et al., 2014).
Jürgen Habermas. Photograph: Martin Gerten/EPA/Corbis
The combination of big data and social media, may both empower development in many ways as well as harm human rights and privacy. Nevertheless, those two diametrically opposed practices will be further analyzed in following posts. In this post, it is briefly discussed how both those perspectives fit into the theory of the Public Sphere.
According to the classic theory of public sphere introduced in 1962 by the German philosopher Jürgen Habermas (1989), public sphere is the discursive space that floats between the private sphere and public authority. Living in the age of internet, many theorists offered diverse perspectives on how the Internet may include public spheres or how it can constitute a public sphere on its own (Dahlgren, 2005; Bohman, 2004). Indeed, it is a huge advantage what modern communication channels offer to us.
The Sustainable Development Goals (SDGs) aim to address inequalities with an objective of “reaching the unreachable”. As mobile technology becomes more affordable, more powerful, and more accessible in low-income regions, it presents even more opportunity for governments to achieve these goals, even more so in public health.