Introduction

When we picture a bullied child, many of us imagine someone like Maya, a girl from a migrant family, teased for the way she speaks. Her experience is real. But when Australian students were asked how often they are bullied, the answers pointed somewhere else. The five interactive charts below follow that thread from the world, to Australia, to Victoria’s 79 councils.

How to use the charts: hover over any point for exact values and sample sizes, drag to zoom, and double-click to reset. Charts 4 and 5 are linked: click a council in chart 5, or type its name in the search box, and it lights up on the map.

1 · Australian teens report more bullying than students in 22 of 23 comparison countries

Only Latvia scores higher on PISA’s exposure-to-bullying index, and Australia sits well above the OECD average.

2 · The twist: students born overseas report less bullying

Australian-born 15-year-olds report the highest rate for every one of the six bullying acts. For example, 18% are made fun of a few times a month or more, against 14% of students born overseas. PISA measures how often students are bullied, not why, so this does not mean racist bullying is rare.

3 · So who is bullied most?

The widest gaps are about where students go to school and First Nations background. Where students were born is linked to less bullying, not more.

4 · Victoria has the lowest bullying of any state or territory, but not in every town

Across Victoria, 17% of Years 4–9 students said they had been bullied this term in 2023. In Central Goldfields it was 33%. The darkest councils are mostly regional.

5 · Outside Melbourne, more disadvantaged councils report more bullying

Among regional councils, disadvantage and bullying rise together (r = 0.42). In Melbourne the link almost disappears (r = 0.16): Brimbank and Greater Dandenong are among its most disadvantaged and most multicultural councils, yet they are not bullying hotspots.

What the data tells us

The story

We tend to imagine bullying as something that happens to children who look or sound “different”. This report tests that picture with three public datasets. Australian students report more bullying than almost every comparable country (chart 1). Yet students born overseas report less bullying than Australian-born students (chart 2). The biggest gaps are about where students live and First Nations background (chart 3). Inside Victoria, the state with the least bullying, rates have fallen from 22% in 2017 to 17% in 2023, but they vary sharply between councils (chart 4), and outside Melbourne they rise with disadvantage (chart 5). A child’s postcode tells us more about their school experience than their family’s birthplace.

How to read and use it

  • Read the charts in order, 1 to 5. Each heading states that chart’s finding.
  • Hover over any point or council for exact values, sample sizes and confidence intervals.
  • Click a legend item in chart 5 to show or hide Melbourne or regional councils.
  • Charts 4 and 5 are linked. Click a council’s bubble in chart 5, or type its name into the search box, and it is highlighted on the map as well. Double-click to reset.

Data and preprocessing

  • PISA 2022 (ACER): Figures 6.1, 6.2 and 6.4 and Table 6.2 are read from fixed cell ranges in the Chapter 6 workbook. Asterisks marking countries that missed sampling standards are removed and kept as a flag shown in the hover text. 95% confidence intervals are calculated as ±1.96 × SE.
  • VCAMS 3.2a (Attitudes to School Survey): both sheets (Years 4–6 and Years 7–9) are read in full, keeping only rows that start with a year. “NDP” cells (five or fewer students, hidden for privacy) become missing values. Two rows labelled “2109” are corrected to 2019. Council rates for 2023 pool Years 4–6 and 7–9 by summing students, which gives small councils more stable rates. Only 2017–2023 is used, because the survey question changed in 2017. There is no 2020 survey, because of COVID-19.
  • ABS SEIFA 2021 and ASGS 2021 boundaries: Victorian councils are joined to VCAMS by name after removing suffixes such as “(C)” and “(Vic.)”. Two renamed councils are matched manually: Moreland → Merri-bek, and Colac Otway → Colac-Otway. The code stops if any council fails to match. Boundaries are joined to SEIFA by LGA code and simplified for web display.
  • Metropolitan Melbourne means the 31 metropolitan councils as defined by the Victorian Government. All other councils are “regional”.
  • r in chart 5 is the Pearson correlation between disadvantage (the SEIFA IRSD score reversed) and the % of students bullied, calculated across councils. A positive r means more disadvantaged councils report more bullying.

Limitations and care

  • PISA and VCAMS measure different things. PISA asks 15-year-olds about six bullying acts. VCAMS asks Years 4–9 students in government schools whether they were bullied “this term”. They are not combined; each chart’s source is shown under it.
  • PISA measures how often students are bullied, not why. The lower rates for overseas-born students do not mean racist bullying is rare or unimportant.
  • Correlation is not causation. Disadvantage and bullying go together in regional Victoria, but these data cannot show that one causes the other.
  • Small councils with fewer than 300 students surveyed are flagged in the hover text, because their rates can swing from year to year.

If this topic affects you, Kids Helpline (1800 55 1800) is free and available 24/7. eSafety (esafety.gov.au) helps with online bullying.

Text descriptions of each chart

  1. Dot plot of the PISA bullying index for 24 countries and the OECD average. Australia is second highest, behind only Latvia.
  2. Dot plot of six bullying acts by immigrant background. Australian-born students report the highest rate for every act.
  3. Dumbbell chart of the bullying index by demographic group. School location and First Nations background show the largest gaps.
  4. Map of Victorian councils shaded by the 2023 share of students bullied. The darkest councils are mostly regional.
  5. Bubble scatter of council disadvantage against bullying. There is a clear upward trend for regional councils and a weak one for Melbourne.

Acknowledgements

PISA data © OECD (2024), published by ACER. VCAMS data © State of Victoria (Department of Education), licensed under CC BY 4.0. ABS data © Commonwealth of Australia, licensed under CC BY 4.0.

Maya is a fictional character created to frame the issue explored in this analysis. Claude (Anthropic) was used only for grammar correction. All analysis, interpretations and final decisions are the author’s own responsibility.

References

Data sources (APA 7th)

Australian Bureau of Statistics. (2021). Australian Statistical Geography Standard (ASGS) Edition 3: Local Government Areas 2021 digital boundary files [Data set]. https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files

Australian Bureau of Statistics. (2023). Socio-Economic Indexes for Areas (SEIFA), Australia, 2021: Local Government Area indexes [Data set]. https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/latest-release

De Bortoli, L., & Underwood, C. (2024). PISA 2022: Reporting Australia’s results. Volume II student and school characteristics: Data tables [Data set]. Australian Council for Educational Research. https://research.acer.edu.au/ozpisa/63

Victorian Child and Adolescent Monitoring System. (2024). VCAMS – 3.2a Proportion of children who are bullied [Data set]. Victorian Department of Education; DataVic. https://discover.data.vic.gov.au/dataset/vcams-the-child-children-and-young-people-are-mentally-and-emotionally-healthy

Software

R Core Team. (2025). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/

Sievert, C. (2020). Interactive web-based data visualization with R, plotly, and shiny. Chapman and Hall/CRC. https://plotly-r.com

Cheng, J., Sievert, C., & Schloerke, B. (2023). crosstalk: Inter-widget interactivity for HTML widgets [R package]. https://CRAN.R-project.org/package=crosstalk

Pebesma, E. (2018). Simple features for R: Standardized support for spatial vector data. The R Journal, 10(1), 439–446. https://doi.org/10.32614/RJ-2018-009

Aden-Buie, G., Sievert, C., Iannone, R., Allaire, J. J., & Borges, B. (2023). flexdashboard: R Markdown format for flexible dashboards [R package]. https://CRAN.R-project.org/package=flexdashboard

Wickham, H., & Bryan, J. (2023). readxl: Read Excel files [R package]. https://CRAN.R-project.org/package=readxl