The OECD Education GPS data set is trove of data, a sea of data. Really this is beyond the ‘monstrous’ amount of data used in school inspections noted by Ozga (2015), and if the data speak themselves, I must be deaf, because I stared for a long time and set up all sorts of visualisations of all sorts of indicators. And it meant very little to me.
This shuffling, sorting and categorising of data reminds me of the data gaze sumarised by Prinsloo (2020) where data supports a political, social and colonial agenda. Looking at the data from a different angle, though, always obscures another side of the overall structure. So whatever truth you choose, you occlude another. Reading Prinsloo (2020), I feel I will look at religious affiliation in Scotland for my week’s data visualisation. This has fascinated me (but it is macabre really) since I first came to Scotland around 30 years ago. When I left the Navy 3 years ago and applied for jobs, many applications had an area for stating religious affiliation. It may seem odd in the 21st Century but some, quite a few had the choice of Protestant or Catholic and nothing else. Sadly, tragically, this division is still important in Scotland and organisations deem it important enough to collect data on. If the form was on paper, and not electronic, I would have been very tempted to scribble in ‘Anglican’ just to throw the algorithm out completely. Unpacking this slightly I noted that this sectarian take on religion falls far short of describing the vast number of divisions in the Christian Church but not as short as for Islam, which is usually just Islam. Or perhaps one might be an ‘other’. An ‘other’, then, is not of interest to those who, for some reason (and I can’t see how it can be a good one) need to know how many Muslims, Protestants or Catholics there are in their organisation. Others are OK. But if we don’t need to know how many Coptic Christians there are, then we don’t need to know anything about the religious practices of our workforce presumably. This struck as a somewhat milder but disconcerting example of the data gaze,
Even in the OECD dataset there is a purpose concealed within the endless tables of data. Whilst the data may be constructed around progressive and laudable objectives, such as the number of women in tertiary education, the data always seem to form some kind of league table. While we may be viewing this as some kind of transparency ‘outing’ the countries which are behind the curve on social mobility, for example, they are still a means of competing with other countries. The OECD probably has no interest in this competition, but it is like we can’t help but compile the data this way. As Ozga (2015) points out school inspection data and governance data such as PISA are constructed this way. Does it really matter if the UK has more women in tertiary education than Mexico? Ozga (2015) points out education is transitioning from a hierarchical elitist structure to more networked and data-driven one. Williamson (2017) also points out the incredible rise of data in supporting vested interests in government and corporate organisations. When I first heard the term ‘data is the new oil’ I thought, when will the first war over data start? But perhaps it is already happening?
Williamson, B. Digital Education Governance: political analytics, performativity and accountability. Chapter 4 in Big Data in Education: The digital future of learning, policy and practice. Sage.
Ozga, J. 2016. Trust in numbers? Digital Education Governance and the inspection process. European Educational Research Journal, 15(1) pp.69-81
Prinsloo, P. 2020. Data frontiers and frontiers of power in (higher) education: a view of/from the Global South. Teaching in Higher Education, 25(4) pp.366-383