Jack¡¯s school is sprawled across a postcard enclave in a leafy south London suburb. Jill¡¯s college is an old polytechnic on the outskirts of Stockton-on-Tees. It is the sort with too many corrugated roofs, and not enough light. Their time is already pinched. Jack debates, plays tennis and volunteers with Age UK every week. Jill balances studying with caring for her three rowdy siblings, as her single mum, a ward nurse, works nights at the James Cook hospital.

Jack and Jill opened their A-level results at the same time. Inspired by the intricacies of the cosmos (and the aura of Brian Cox), they had both applied to study physics at the University of Manchester. They did exceptionally. Jack scored A*AA; Jill, A*AB. Jack¡¯s grades turned out to be about average in his school that year. Jill¡¯s were the best. Ever.

Jack made it in. Jill didn¡¯t.

Most will accept the sentiment of this story: how, and where, we grow up has an effect on what we might be able to achieve. Too often, though, the Jills of our story ¨C from rural and coastal peripheries, to the hearts of our cities ¨C are personally blamed for not fulfilling their potential: "You can make it, kid; it doesn¡¯t matter where you come from." Sadly, however, it does. This is the unhelpful paradox inside the seemingly positive idea of "admitting students regardless of background". It¡¯s in disregarding where someone has come from, and how they have managed to achieve despite the obstacles, that we risk missing some of the most impressive and resilient young people of our time.

As the recent Times Higher Education article on the subject points out, universities have understood this for a while. Using information collected through Ucas, they pioneered the process of. In short, because the social playing field is uneven, grades are more effectively understood in their (school, home, and personal) context. In the past 10 years, some have gone further by offering informed adjustments to account for this inequality. The examples are numerous: from bespoke , to grade flexibility at admission. For our story, Jill¡¯s A*AB, in context, may mean that both she and Jack are accepted on to the same A*AA physics course at Manchester.

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This is happening as we speak. In 2013, 37 per cent were systematically contextualising (57 per cent intended to). But, even for those actively contextualising, the process can often suffer from such inconsistency that it is rendered inert. The data may remain unused as it¡¯s too hard to match to individual applications or, even when it arrives, tutors are unclear as to how to interpret and apply it accurately. Sometimes, pointlessly, ¡°context¡± can obscure more than it reveals.

So, why is this happening?

It¡¯s hard. The supply of background data, alone, is not enough. We need systems and standards. How can individual university systems be made to speak positively to Ucas? And, how can knowledge of what to do with this information be distributed appropriately throughout the admissions architecture?

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An answer can be found in the emergent field of . Recruiters, originally inspired by the work of universities, have standardised the contextual information's form by adopting a single system. The result is that a growing list of 22 of the UK¡¯s elite employers, including Deloitte, Police Now and the ¡°magic circle¡± of law firms are doing what the higher education sector has been unable to do: collaborate. Knowledge transfer processes, through bespoke training, supplement this single system. This ensures that, top to bottom, a firm line is established outlining how, when, where, and to what effect the information is to be used.

Don¡¯t get me wrong, advocating in favour of more information, intelligent technical systems and informed users is not blind adoration of the ¡°big data/open data¡± Bieberism. This idea is about the precise connection between relevant information and processes that need it. The outcomes? Decisions being made using all the information they deserve; decisions that will consistently be based on achievement and potential; and the ability to measure. From measurement emerges reflection, iteration, improvement and progress.

This is not about Jack or Jill, but about Jack and Jill. They both went up the hill, yes, but they took vastly different paths, and we ought to at least know how.?

Joshua Oware is research manager at .

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