Incomplete data: The socio-economic diversity of Singapore’s top schools

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Even though a ST report (Sept. 16) shed some light on the lack of socio-economic diversity among medical and dental undergraduates at the local universities – finding that two-thirds of them come from households earning more than $9,000 a month – a complete picture of socio-economic diversity among medicine and dentistry students remains elusive. We do not know how the income representation of students has changed over time. And in addition to household income, we do not know the socio-economic distribution of these students based on per-capita income, housing type, parental education and employment, as well as their past schools.

Knowing the past schools of medicine and dentistry students, for instance, is likely to highlight the social experience of inequality, given the homogeneity of their relationships and social networks. In the same news report, Associate Professor Jason Tan from the National Institute of Education said: “The root of this imbalance has to be traced way back in the school system, where there is already the phenomenon of students from low-income families being under-represented in the top schools”.

Such incomplete data is less an isolated phenomenon and more of a trend, and the burden seems less on the media than it is on the government. We know a majority of Public Service Commission scholars live in landed property. That about half of current Raffles Institution students live in public housing. That other top secondary schools are widening the pool of primary schools from which their students come, even if socio-economic data was not provided. As informative – and perhaps worrying – as these snapshots may be, they still do not present a complete picture of the socio-economic diversity of Singapore’s top schools.

This is how ST reported the socio-economic make-up of medicine and dentistry undergraduates from the National University of Singapore and the Nanyang Technological University:

“The [Ministry of Education] had said previously that 11 per cent of both medicine and dentistry students come from families in the lowest 30 per cent income bracket, where the gross household income is $4,000 and below a month.

In response to queries from The Straits Times, the ministry said another 20 per cent of students belong to the next 36 per cent of households by income, where gross household income per month is just above $4,000 to $9,000.

This means that about a third of the students come from families with a monthly household income below the median, which was $9,293 last year”.

There are two likely counterarguments to this clamour for more complete data. First, that the university departments and the top schools are probably already cognisant of their demographic and socio-economic representations, which allows them to target those who need the most help. Second, that the ideal target of diversity or representation is hard to ascertain. For instance, by age groups, should the profiles of students in top schools mirror that of the overall Singaporean population?

The first counterargument merits a more straightforward response, that having more complete data made public and providing targeted assistance are not mutually exclusive endeavours. In fact, it might be argued that the provision of individual aid could also be improved by increased public scrutiny and by broader understandings of structural or systemic issues of inequality or poverty.

The second counterargument is convincing at first glance, especially if expedience is prioritised. The same A/P Tan added that it is difficult “to determine an ideal ‘target’ in terms of the proportion of students by income level”. Be that as it may, the argument is less tenable because the public thus far has not been able to make informed judgements – about what it might perceive as ideal – without access to complete data, in terms of how income representation or socio-economic diversity may have changed over time. This limits the public’s ability to draw reasoned comparisons over time or even with other countries, since it has no data upon which to anchor its preferences.

In other words, the lack of data has made it implausible for Singaporeans to have informed discussions on representation. While it may still be true that a fixed “target” is unrealistic, it is not unrealistic to think that the public can tell if there are skews to the extremes, or that the public is collectively capable of deciding upon an acceptable range of diversity.

Calls for more complete data to be made available will continue to intensify, and such data might even influence our perceptions and classifications of these top schools. For example, do these schools produce outstanding academic graduates because of school characteristics or features, or because they attract well-resourced students who are set up to excel regardless? And more broadly, national conversations will only benefit with greater public access to data and information.

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