Distance disadvantage needs a new measure

Current remoteness rating not working writes Mex Butler. Youth Allowance eligibility for regional students is causing much debate, but the discussion seems to be missing one important fact – that there is considerable scope for obtaining a more equitable result without any legislative change. Developing an education specific tool for determining distance disadvantage could provide much better focused policy outcomes. Currently, a student’s remoteness category is determined by an ABS document called the Australian Standard Geographical Classification (ASGC), which is mentioned by name in the legislation. However the same legislation also states that a different document could be used, providing that it is one published by the ABS. This is fortunate, since the ASGC will be replaced in mid-2011. The new document is designed to be more flexible, especially when it comes to ‘plugging in’ non-ABS structures such as local government areas, catchment management areas and the like. The relevance of this fact will become clear later, when we explore the possible development of an education sector tool for determining distance disadvantage. Meanwhile, let’s look at the existing situation more closely, and understand why there is so much interest in including ‘inner regional’ students in the eligibility criteria. To understand the strong feelings of inequity in relation to the current situation, one need only examine a map which colour-codes the five main remoteness categories. Zoom in on south west Victoria, for example, and you will see that right in the middle of a large brown ‘outer regional’ area, the town of Hamilton and several outlying villages are classified as ‘inner regional’ pink. This means that people living in Hamilton can’t gain access to Youth Allowance under the special conditions introduced to help regional and rural students, whereas people living all around them can. Look around the map and you will find a number of such pink islands of ineligibility – Mount Gambier, Tamworth, Dubbo, Deniliquin and Mackay, to name a few. Zoom in closely to any of these places and you will find that along the boundaries, there are houses opposite each other in the same street where on one side they are eligible and on the other side they are not. Wherever there is an eligibility boundary, there will be people on one side who are not happy. However if we look a little closer, the situation becomes harder to defend in the case of Youth Allowance. The ASGC – that ABS document which defines remoteness categories – draws its underlying data from a source called the Accessibility/Remoteness Index for Australia (ARIA+). ARIA+ can give a score to any location in Australia, based on its distance by road from the nearest ‘service centre’ in each of five different population size categories. It is described by its developers as ‘a purely geographic measure of remoteness’. So how can this purely geographical measure, based on distance by road from other centres, result in people being treated differently when they live directly opposite each other in the same street, and who are therefore by definition equidistant from everywhere by road? The problem arises when the ARIA+ scores are averaged over an area, then aggregated up to ABS Collection Districts. Collection Districts (CDs) typically encompass around 400 households each, and are often bounded by roads. North of the road is one CD, south of the road is a different CD. So when ARIA+ scores are averaged and aggregated up to CDs, much precision is lost. As to why one town of around 10,000 people gets a different remoteness rating from another town of about 10,000 people, both at around the same distance from the state’s capital city, that seems to be an artefact of the methodology. The underlying data is all there, detailed down to the level of individual properties. ARIA+ scores according to the specific formula outlined above – distance by road to centres in five population sizes. But it could easily provide a score according to different sets of criteria. And that is exactly what it has been doing for doctors, pharmacists and cardiac services. Right now, a three-year ARC research program to develop CardiacARIA is in its closing stages. CardiacARIA provides a means of determining the closest and best suited cardiac service for any given location in Australia. It was developed by the ARIA team at the National Centre for Social Applications of GIS (GISCA), with an expert panel from within the health industry and a team of researchers headed up by Dr Robyn Clark from the University of South Australia. In the process, they have been able to identify with great precision the areas of inequity in the provision of cardiac services. Not surprisingly, these are in regional and remote Australia. Similar tools have previously been developed to assist with remoteness incentive schemes for general practitioners (GPARIA) and pharmacists (PHARIA). So, if it is possible to modify ARIA with information relevant to the health industry, what about doing the same thing for the education industry? What about developing EduARIA? Consider the outcomes if EduARIA measured the distance by road to the nearest higher education providers at five levels of service, ranging from an unstaffed computer access centre through to a large complex multi-disciplinary university campus. Preliminary exploration of this idea renders a somewhat different map. The pink islands of ineligibility disappear. The possible inputs could go well beyond this one simple example. It could be cross referenced with a range of other socio-economic, cultural, demographic or technological factors. Or perhaps simplicity would obtain the best result. This is not a decision for one person. An expert panel of education specialists, working with the ARIA team from GISCA and a university based research team seems like an appropriate and already tested model for developing such a tool. Its applications would be far wider than simply Youth Allowance eligibility. By mapping educational distance disadvantage, greater policy precision would be possible across the entire education sector. The few years since the Bradley Review have resulted in a plethora of reports on distance disadvantage in educational provision. EduARIA would be a good place to start in mapping the disadvantage clearly and accurately. It could provide an informed and appropriate basis for targeting policy where it is most needed. Mex Butler is a project officer with the Potter Rural Community Research Network at RMIT University’s Hamilton campus.