Remoteness standard 1.0

Requirements 

When collecting, releasing, analysing and reporting data related to RRR education, all directorates across the department must use the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS) Remoteness Standard (Standard).  

Using the Standard enables the department to consistently identify the impact of geographical isolation on educational performance and outcomes. The Standard identifies locations according to five regions: Major Cities, Inner Regional, Outer Regional, Remote and Very Remote. Regions outside of Major Cities are identified as RRR.  

It is important to note that ASGS boundaries do not neatly align with boundaries for Statistical Area Level 4, which have previously been a measure of geographical areas as they are the largest sub-State regions within the ASGS. For example, Central West NSW, as defined by SA4 covers Inner Regional, Outer Regional and Remote areas, as defined by Remoteness Areas.   

Data.NSW provides a complete list of NSW Public Schools, with the possibility of disaggregation by ASGS Remoteness Areas, as well as other useful data points such as SA4 and Principal Network.  

In practice, use of the standard may look like: 

Collecting Data - All data should be collected in a way that allows for analysis using the Standard. To do this, teams should collect data against an address or school identifier as a minimum (note that incomplete addresses such as postcode does not fully align with remoteness categories). Use of the CESE Master dataset will then allow data to be aligned to ASGS Remoteness. 

Analysing Data - Data analysis focussed on geographical isolation allows teams to identify performance by remoteness, and provide additional, contextual support to areas that, the evidence shows, are having difficulties achieving desired outcomes.  

When preparing remoteness data: 
 

• Cells (particularly for Remote and Very Remote locations) may need to be combined to protect school, student or staff anonymity while maximising the amount of reportable data. 

• Use agreed groupings when collapsing remoteness categories. In general, do not use a mix across remote and regional categories (e.g., it is appropriate to collapse inner and outer regional, but not appropriate to collapse outer regional and remote). Reporting RRR as a single group that excludes major cities may be appropriate, depending on sample size. 

• Remoteness categories do not always align with “common sense” expectations – e.g., Tweed, Central Coast, Newcastle, Wollongong and Queanbeyan are all “Major Cities” and much of “Inner Regional” is the northern eastern seaboard. Remoteness categories may vary within a postcode or suburb.  

• Additional analysis by SA4 may provide further granularity, but analysts should focus on remoteness in their analysis and reporting.  

• Ensure that you use the most recent version of the categories, noting that the Standard uses census data but is generally released several years after the census. 

• When analysing a time series, it is preferred that the current categories should be applied to the full dataset, however there may be some cases where using the contemporaneous categories would strengthen the analysis. Explicitly identifying the approach in any publication allows the reader to know exactly what they are looking at.   

• When reporting against ASGS categories, it is important to explicitly show how the unit of analysis (e.g. students / students in schools) has been mapped to the ASGS categories.  

Reporting Data - Data reporting should include analysis by remoteness. This can be achieved in several ways including a discussion of RRR throughout the report, a dedicated subsection within an overarching report, and/or a standalone factsheet.   

From 2024 Our Plan for Public Education will commence reporting on RRR equity by the Standard. Additionally, the Post School Destination Survey has provided a remoteness factsheet in which a discussion of the data analysis is published.  

Rationale 

The use of the Standard will support a consistent, enterprise-level representation of RRR performance. Implementation of a Standard is critical to ensuring the department has a consistent understanding of how to measure and report on performance. Developed by the ABS the data Standard has been adopted by state and federal government departments. Such broad use of the Standard provides comparability between research and outcomes as well as capacity for interdepartmental collaboration.  

In August 2023, the Audit Office of NSW completed the Regional, Rural and Remote Education Performance Audit, with a recommendation for the department to improve data collection by using a standard remoteness classification. Adopting the RRR data Standard across the department will address this recommendation by:  
 

• ensuring public-facing performance measures for RRR are reported consistently with reference to a common standard 

• addressing inconsistent interpretations of RRR across the department when collecting and analysing data that may be used as part of internally or externally commissioned research.  

Prior to the release of the Audit and associated recommendations, the data Standard had been endorsed by the DoE Rural Assurance Steering Committee (RASC). RASC was formed in 2022 as the governance mechanism for the Regional, Rural and Remote Implementation Unit. Implementing a data Standard has been identified as significant to: 
 

• improved decision-making that uses a current evidence-base, noting the ASGS is updated every 5 years to account for growth and change in Australia's population, economy and infrastructure. 

• the tailoring of policies, programs and processes across the department to ensure they better address the complex social and educational challenges and needs of RRR communities. 

• developing an increased capacity to undertake data analysis on complex issues involving multiple data sets with a greater level of confidence in the analysis outcomes.  

• enabling discussions on RRR priorities with external agencies based on common definitions of rurality within data. 

Supporting documentation and policy  

Eagle Eye is a map-based platform for analysing and developing insights from multiple data sets across School Infrastructure NSW (SINSW), DoE and external to the department. The platform can analyse results based on remoteness and provides insight into enrolment and housing trends, housing supply and housing characteristics. 

The Post School Destinations Survey (PSDS) adopted the standard for reporting remoteness in factsheets for 2022 onwards. This factsheet was a standalone document that provides a high-level overview of findings from the survey with a comparison to Major Cities students. This was a development from previous publications which referred to Greater Sydney and ‘Rest of NSW’.  

In 2024, the Regional Rural and Remote Implementation (RRRI) Unit are delivering on commitments within the RRR Implementation Plan. A central element to this plan is the consideration of RRR contexts from a whole-of-systems perspective.  

The RRRI Unit have developed and tested the RRR Lenses; a resource to prompt thinking regarding contextualising program design, delivery and evaluation for varied regional nuances that may impact successful outcomes. The Lenses encourages the reader to consider regions in line with the Standard. 

Get Back in the Game – During an evaluation and following use of the RRR Lenses document, the Get Back in the Game team amended their approach for developing a regional loading in their standardised funding model, to better cater for rural and remote regions. Seeking advice from the Rural, Regional and Remote Education Policy team, a model based on the Australian Statistical Geographical Standard (ASGS) was used to more accurately calculate the loading across NSW.  

The OECD has published an article title ‘Yes Minister, Yes Evidence’ on the improvement of evidence use in education policy (OECD, 2024). The policy paper highlights that policy officers often can come up against too little research, or too much research which is not available in relevant formats to allow for use. This challenge extends to RRR data, as current practices to analyse data often results in an aggregation of data across multiple remoteness contexts. As a result, difficulties arise to achieving evidence-informed and effective decision-making practices. [LINK to paper]  

The Department of Education Research Statement 2024-2025 is using the standard as a method of defining equity based on geographical isolation. The Statement will be an executive approved document that will provide clear guidance on the use of ASGS Remoteness Structure in future research. 

Below is an excerpt of the presentation taken to the Rural Assurance Steering Committee (RASC) on 15 December 2022 in which the need for a consistent data definition for RRR was discussed.