Racism in Australia: filling data gaps
March 2021
Jehonathan Ben, Amanuel Elias, Mandy Truong, Fethi Mansouri, Nida Denson and Yin Paradies
This is a CRIS Issues Paper. CRIS Issues Papers identify what an issue is about; why it’s of strategic importance; who or what has the power and resources to act on an issue; where current policy can be improved; concrete proposals for action; potential impacts of proposed policy changes, and related areas that need further research and exploration.
Executive Summary
Racism is a social force that continues to shape Australian society. Data on racism in Australia have grown considerably over the last two decades, but several gaps remain that relate to their collection, analysis, and overall utility. This Issues Paper is informed by an ongoing stocktake review of racism data in Australia, and specifically in Victoria, focused on self-reported data collected through survey-based research and routine initiatives by government, community and other organisations¹. We point to a number of areas where racism data remain under-collected, including gaps that should be filled as a matter of urgency in the context of COVID-19.
Identified data gaps include:
Particular demographic cohorts, such as children;
Vicarious and structural forms of racism;
Settings and institutions such as domestic and online spaces, sports, finance and healthcare settings;
Responses to racist incidents by those who are targeted;
The relationship between racism and different areas of everyday life, including social, economic and health circumstances;
Demographics of perpetrators of racism.
We also consider limits to analysing data specifically from Victoria. We discuss the consequences of data gaps for research and policymaking, and make recommendations for augmenting data collection processes, and enhancing the availability and utility of collected data.
Three recommendations to address identified data gaps in racism research:
Conduct further analysis of existing data
Collect new data that addresses identified data gaps
Enhance data availability and integration
Why is this an issue of strategic importance?
Racism has detrimental consequences across many levels and areas of human life – structurally, institutionally, interpersonally and when psychologically internalised. These harmful consequences span domains including mental and physical health, the economy, education, justice and many more (e.g., Elias & Paradies, 2016; Paradies et al., 2015).
Racism’s ill effects have been partially acknowledged in Australian law and policymaking, from the Racial Discrimination Act to ongoing initiatives by the Australian Human Rights Commission. In Victoria, resources and programs have been devoted to addressing racism over the years, for example through the Victorian Government’s Anti-Racism Action Plan. While high-quality data are critical to informed decision-making on this topic, racism data collection, availability and analysis are limited in important respects. Most recently, under COVID-19, the terrain of racism has been shifting (Elias et al., 2021), resulting in new questions, priorities, and a need for additional data reflecting this changing landscape to help guide effective policy and anti-racism action.
2. What is the issue about?
Data collection on racism in Australia has increased substantially over the last two decades, aided by the establishment of several large-scale surveys, datasets and projects, with many that have been ongoing. These data sources have greatly enhanced our understanding of different facets of racism, for example, by providing population estimates of the prevalence of racism (e.g., Kamp et al., 2017; Markus, 2019), and by shedding light on the experiences of different racial, ethnic, and national groups (e.g., Correa-Velez et al., 2015; Shepherd et al., 2017).
However, racism research in Australia faces important challenges because key data remain insufficiently collected and analysed, and largely under-utilised. We are currently completing a stocktake review of racism data in Australia, and specifically in Victoria, focused on self-reported data collected through survey-based research and routine initiatives by government, community and other organisations.
Based on our review, we identify major data gaps in:
1. Children and racism
Despite the considerable effects and long-term consequences of racism on health among children and young people (Mansouri et al., 2009), and children’s heightened vulnerability to racism compared with adults, Australian research on racism and health among young people has been quite limited (Cave et al., 2019; Priest et al., 2020; Shepherd et al., 2017). Similarly, our own stocktake review points to just a handful of studies that have focused on racism among children (e.g., LSAC, LSIC, SOAR), with LSIC and LSAC as presently ongoing (see Appendix A).
2. Different forms of racism
There are also data gaps that relate to different forms of racism.
For example, new forms of racism under COVID-19, as linked with intense nationalism and ideas of contagion (Elias et al., 2021), are under-studied in Australia. Less recent, but still evolving and inadequately studied, are forms of racism associated with enhanced policing, securitisation and a focus on counter-terrorism, and their effects of criminalising particular groups, such as Muslims and humanitarian migrants.
Our stocktake review also shows minimal engagement with forms of ‘cultural racism’, such as ideas about socio-cultural ‘fit’ in work environments. We found that data collection centres on direct, interpersonal racism, and far less on racism as experienced vicariously (i.e., as witnessed or known of) or structurally (i.e., as operating more broadly in society).
Vicarious racism is the least studied form, with several exceptions (e.g., CRaCR, GSS, LEAD, LSIC, SOAR, Nelson et al., 2018). This is despite the high prevalence of vicarious experiences and our increasing understanding of their adverse effects. Vicarious racism may have serious effects, for example, at work (Dahanani & LaPalme, 2019), and among children (Heard-Garris et al., 2017).
Structural racism, captured, for instance, in questions about the prevalence of racism in Australia at large, is relatively under-studied too, despite its pervasiveness according to national surveys (e.g., 86% of respondents in Geographies of Racism, Habtegiorgis et al., 2014; and 79% in Facing Up to Racism, Sharples & Blair, 2020).
3. Racism in domestic and online environments
Data on several critical settings where racism occurs are also missing. With COVID-19, racism has increasingly moved into and transformed within certain spaces, such as domestically and online. Yet domestic spaces like home environments and neighbourhoods see surprisingly little data collection. Only a few of the studies we identified examined racism at home (or at a relative’s or friend’s home), or in the neighbourhood or by neighbours (e.g., BNLA, LEAD, NATSISS, Face Up to Racism).
This is also true of qualitative research on intercultural connections, where meagre attention is given to private spaces and intimate circles of friends and family (e.g., Valentine et al., 2015; for Australia, see Nelson, 2020). Online and social media spheres are becoming increasingly central to social life, and crucial to our understanding of racism and actions to contest it, but have been scarcely studied. Several studies have measured racism in online settings (e.g., Face Up to Racism, LSIC, NATSISS), although they have typically done so using only a single item about experiences of racism online (rather than a multi-item scale). Routine data collection by media and social media organisations, and by organisations that monitor the internet (e.g., of incident reports) is fairly limited too.
An exception in this area is Cyber Racism and Community Resilience (CRaCR), which used a large representative sample to examine cyber racism in more depth, including its manifestations, specific platforms, and responses it induced (Jakubowicz et al., 2017). Still, some dimensions of online activity remain understudied, including, for example, pervasive ‘sexual racism’ in online dating sites and apps towards gay and bisexual men (Callander et al., 2015) and towards gay Indigenous men and women (Carlson, 2020), as well as in online gaming, which is popular in Australia, but under-explored for its links with racism (see Passmore et al., 2018, for a US-based discussion).
Moreover, media outlets such as newspapers and TV shows have rarely been studied with regard to racism, but recent research shows that at least some key actors in this arena, such as NewsCorp publications, consistently represent some groups negatively (e.g., Muslim, Chinese and Indigenous people) through racist opinion pieces (ATN, 2020; see www.alltogethernow.org.au/media-monitoring/).
4. Racism in healthcare settings
Healthcare-related racism is significant for various reasons, including the existence of racial/ethnic disparities in access to health services. Experiences of racism are associated with lower levels of healthcare-related trust, satisfaction and communication (Ben et al., 2017), and may help maintain culturally unsafe healthcare environments (for a recent Australian case, see Malatzky et al., 2020). In the context of COVID-19, while healthcare settings and services play a significant role in combatting the pandemic (for example, through treatment and vaccination), racism in such settings may work against equitable access and result in further disparities. Racism in healthcare settings has only been measured in six of the studies we identified (e.g., BNLA, Face Up to Racism, Geographies of Racism, LEAD, Mayi Kuwayu, NATSISS), with the last two the only ones that remain ongoing.
5. Racism in financial settings
There is urgent need for data collection on financial settings and institutions in Australia, since very few studies have considered this area. The few studies that have measured racism in financial settings typically focus on experiences of racism in receiving financial assistance or services, for example, in financial institutions like banks (e.g., BNLA, Geographies of Racism, LEAD, NATSISS). One key area where research is missing is the sharing economy, a growing industry with substantial levels of intergroup contact – negative and positive – which potentially can create, heighten or counter racism (Piracha et al., 2019).
6. Racism in sport settings
The under-exploration of racism in sport may seem somewhat surprising, given the attention it receives in some media reports and anti-racism initiatives, with a notable recent example being coverage of structural racism at the Collingwood Football Club (e.g., The Guardian, 2021). However, survey-based studies that measure racism in sport typically address it, again, via limited measures, and while discrimination may be reported internally at different levels (e.g., clubs, governing bodies) we were unable to find initiatives focused on routine racism data collection and reporting.
7. Responses to racism
Few of the studies we have identified measure immediate responses to racist situations. Typically, these are behavioural (e.g., avoidance) or via health responses (e.g., stress, worry, feeling angry or upset), whereas little data have been gathered on other responses.
8. The relationship between racism and different areas of everyday life
Publications that use racism data are limited in reporting the association between racism and areas such as employment and health behaviours, including substance abuse and conduct problems, and, to a lesser extent, physical and general health, and education. We also found limited reporting on perpetrators’ ethnic and racial backgrounds, both in studies that examined participants’ racism towards other people and groups, and in those where study participants have been targeted.
9. State and local government
Data about the state where study participants reside and racism occurs are often collected, but state-level analyses are uncommon, which limits our ability to understand and challenge racism in particular states, such as Victoria. Finally, data on the area where study participants reside are sometimes collected, and may be used to compare racism between urban and regional environments or Local Government Areas, but such analyses are rarely reported.
3. Where can current policy be improved?
Currently, there are several policies that relate to data collection:
The Australian Bureau of Statistics (ABS) devotes extensive resources to data integration across different surveys, and maintains several integrated ‘data assets’ for research deemed to be in the public’s interest (ABS, 2020). These resources may be further expanded to include additional ABS surveys that measure racism.
There are policy-oriented initiatives that focus on discrimination data, such as routine data collection and reporting by human rights commissions. The Australian Human Rights Commission collects data on complaints made in Australia under the Racial Discrimination Act and is charged with investigating, conciliating and reporting on such complaints; while the Victorian Equal Opportunities and Human Rights Commission (VEOHRC) collects further data on complaints of discrimination, and can facilitate dispute resolution. Other state- and territory-based anti-discrimination commissions also receive and resolve complaints in accordance with each jurisdiction’s own Anti-Discrimination Act. These initiatives may be more strongly integrated with other routine data collection mechanisms that focus on related data at the national level (e.g., eSafety, Fair Work Commission), state level (e.g., Victoria Police, Victorian Government Department of Education and Training), and locally.
In relation to COVID-19, early data suggest increased reports of racism in Victoria (VEOHRC, n.d.), and hundreds of COVID-19-related incidents against Asian Australians nationally (Asian Australian Alliance, 2020). The government’s approach to collecting data on racial disparities has been haphazard and data on COVID-related racism and on racial disparities relating to tests, infections, hospitalisations and deaths, are missing, as well as on the relationship between racial/ethnic backgrounds and COVID-related challenges to housing, income and employment (Ben & Paradies, 2020; SBS, 2020).
4. Proposals: what further action is needed and by whom?
We make three proposals for how racism data gaps may be filled. We discuss further analysis of existing data, collecting additional data, and enhancing data availability and integration.
a) Further analyse existing data
To enhance the utility of existing data, we propose to further analyse the following:
i) Perpetrators’ backgrounds – analyse how racism may vary according to perpetrators’ demographics (e.g., racial/ethnic background, age, gender);
ii) Association data – use available data to conduct bivariate analyses (e.g., correlations) and multivariate statistical models to understand racism’s interaction with and affect on areas such as health, employment, justice, income and education;
iii) State-based (Victorian) analysis – existing data often include ‘state’ as a demographic, although further analyses by state are uncommon. Victorian-focused analysis should be feasible and useful to local policymakers, as well as analysis of geographical and government areas;
iv) Systematic review and meta-analyses – the existing body of evidence on racism should be synthesised qualitatively and quantitatively to determine how racism fluctuates over time, across localities and forms, and between groups.
b) Collect additional data
We propose to extend data collection on racism through:
i) Academic, survey-based research;
ii) Reporting mechanisms and initiatives by organisations.
These may be combined in some ways, possibly through data linkage and integration projects. As noted earlier, priority should be given to increasing data collection on the following: study participants – young people and children, especially in early childhood; forms – vicarious and structural racism; settings and institutions – domestic, online, sports, finance, healthcare and media; responses to experiences of racism – immediate and longer term, both cognitive and behavioural; perpetrators’ racial/ethnic, age and gender backgrounds – in addition to examining links between racism and study participants’ demographics, as noted earlier, the demographics of those who perpetrate racism towards study participants should be examined.
Priority should be given to adding measures to existing studies that repeatedly measure racism, such as MSC, GSS, AVS, and NATSISS. Adding racism measures to HILDA, and possibly extending the study by recruiting a cohort of migrant respondents could generate excellent data for analysing racism and related factors that are already captured by the survey. Given the absence of current data collection on migrant groups, reviving datasets or aspects of projects that focus on migrants (e.g., BNLA, LSIA) would also be very useful. We propose that researchers additionally collaborate with organisations working in spaces that have the capacity to collect further data.
Further initiatives that may be able to fill these gaps include projects that are currently ongoing, such as our work on cyber racism and on everyday responses to racism (www.crisconsortium.org/stream-1-overview).
c) Enhance data availability and links
To enhance the utility and relevance of data, existing studies and reporting mechanisms should be made more widely available, and better integrated and interlinked. This can be furthered through linkage initiatives and integrating corpuses of data from multiple agencies. It will require building on similar current initiatives, closely liaising with government and other organisations that keep and use data, to better understand shifting priorities, and to clearly communicate possibilities and likely benefits of augmentations to data collection and analysis.
Key actors to potentially liaise with in seeking to increase the utility of collected data are those already involved in data linkage and integration initiatives, and projects that seek to make data more accessible. Several surveys (e.g., GSS, NATSISS), are conducted by the ABS, which fosters such linkages, including to other agencies, while key longitudinal studies that include racism measures are run through the National Centre for Longitudinal Data (NCLD; i.e., BNLA, HILDA, LSAC, LSIC). Research programs that focus on racism (e.g., www.westernsydney.edu.au/challengingracism/) and initiatives to create central repositories (e.g., www.tacklinghate.org) may align with our discussion as well. Other actors to collaborate with to establish new linkages include researchers and government organisations with experience in cross-agency partnerships.
We recommend consulting end-users who plan to utilise new data to catalyse social change, for example, through implementing anti-racism programs, to ensure that data can indeed inform adequate responses to ongoing and emerging issues. One way forward is to bring together various stakeholders (e.g., organisations, researchers) working on racism within the same areas and settings (e.g., online, healthcare, media). Based on our stocktake, we will identify such stakeholders and explore new collaborations in data sharing and use. We will make our stocktake and ensuing publications widely available, promote them among researchers, practitioners and policymakers, and collaborate with others who seek to make such data more accessible and useable.
5. What are the impacts of a change in policy?
By filling racism data gaps, we will expand knowledge about racism, and will be better placed to inform initiatives that respond to it. For example, collecting data on online racism may inform anti-racism campaigns focused on specific audiences (e.g., parents/children, people from different racial/ethnic backgrounds), and help identify particular platforms and areas in need of improved regulation. Given the sophisticated data analysis methods now available, it may also be possible to examine the characteristics of both perpetrators and targets of cyber-racism. Expanding data linkages will reduce gaps and overlaps in data collection and thus save resources. It will expand the evidence base on racism, and enhance the quality of its analyses, while advancing multi-agency collaboration. On a broader societal level, research and action to counter racism will ultimately have positive consequences for people who experience racism, and for Australian society at large.