Understanding public narratives of equity and opportunity in Australia

Understanding drivers of disadvantage as a multi-faceted concept that differentially affects populations is an important precursor to meaningful policy and practice action.

One such driver, how the disadvantaged are represented in public and political discourse, has been under-researched. In part, because of the time required to do so. However new, multidimensional, dynamic measurement approaches open up new opportunities for understanding narratives of disadvantage as a potential driver of disadvantage.

BehaviourWorks Australia, Soda Laboratories (Monash Business School), Data Visualisation and Immersive Analytics Lab (Monash Faculty of Information Technology) and Monash Data Futures Institute undertook to develop a rich understanding of ‘Narratives of Disadvantage’ in Australian discourse.

This page summarises the activities interdisciplinary collaborations, outcomes, and dissemination undertaken as part of Phase 1 of the Narratives of Disadvantage project funded by the Paul Ramsay Foundation.

What did we do?

The main research activities that comprised Phase 1 included:

Evidence mapping from academic literature and practice review to synthesise existing research on narratives of disadvantage
Human-coded content analysis of narratives of disadvantage from open source opinion and editorial documents
We’re now undertaking focus groups to unpack topic specific nuance in understanding how AI enabled tools can be used to address challenges

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What did we find?

Content analysis of over 500 op-eds and editorials published in major Australian newspapers in 2020 was undertaken. Results showed the most commonly-discussed groups were:

First Nations peoples
women
racial minorities.

We also found that the most commonly-discussed issues were:

violence
work
crime
prejudice.

The analysis also showed which groups are largely absent from these discussions, such as single parents, overweight or obese people, aged-care residents, and people with gambling problems. Articles were mostly commonly characterised by a focus on solutions. Disparagement of people experiencing disadvantage was less common, but happened more often in some newspapers.

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What’s next?

We are currently working on phase 2 of the project which involves gaining a deeper contextual understanding of what is needed by different sectors (e.g. youth justice and out-of-home care). Our parts in the Faculty of IT are further developing the suite of AI-enabled capabilities to better support sectors to unpack and understand Narratives of equity and opportunity.

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Phase 2 will be completed by the end of 2023.