Why this matters
The gender pay gap measures the difference in earnings between gender groups (usually women and men). This is different to unequal pay based on gender, which occurs when people of different genders are paid differently for performing the same work or work of equal or comparable value. Unequal pay is unlawful in Australia. While unequal pay can contribute to gender pay gaps, gender pay gaps reveal broader inequalities. They compare the average earnings of women and men across a workforce, reflecting the combined effects of factors such as occupational segregation, workforce participation, seniority, working hours, and in some cases, unequal pay.
Gender pay gaps shape women’s financial security across their working lives and produce a compounding effect into retirement. Women earn less money than men because they often work in women-concentrated occupations and industries that pay less, work fewer hours, and spend more time on unpaid work like housework and childcare (WGEA et al. 2026). Even when women’s part time pay is converted to a full time equivalent (which is how the Commission calculates pay gaps), they still earn less than men on average. At retirement age, Australian women have around 25% less super than men (ASFA 2023). Older women are one of the groups most vulnerable to homelessness in Australia (Peterson and Tilse 2024).
When women have less income and wealth, it affects their freedom to make independent life choices, including to leave abusive relationships (Summers 2022). Wealth inequality also stops women and gender diverse people from making free choices about their health and how they want to live their lives.
As pay gaps are driven by several interacting factors, closing these gaps means looking beyond obvious differences in pay for the same job, to the deeper question of how different types of work and workers are valued and rewarded, and where people of different genders sit within an organisation.
You can read more about gender pay gaps and their drivers in our Insights report: Gender pay gap (2025).
How we define progress
Organisations should aim to move any existing gender pay gaps towards zero. The Commission’s Insights report: Gender pay gap (2025) recommended that organisations keep their mean and median total remuneration pay gaps within a target range of -5% to +5%, mirroring the federal Workplace Gender Equality Agency’s established range (WGEA 2025).
The Commissioner is now setting a higher standard: a target range of -3% to +3%. This tighter target reflects the public sector’s role as a leader in the Victorian community. By holding itself to a higher standard, the public sector can help drive wider progress across the state.
How the Commission reports on pay gaps
The Commission reports pay gaps using four main variables:
- Base salary refers to an employee’s fixed annual pay, excluding bonuses, allowances and other discretionary payments.
- Total remuneration is base salary plus all additional payments, such as allowances and bonuses. Because these are often distributed unequally between genders, total remuneration gives a fuller picture of overall pay equity.
- Mean is the average earnings of a particular group. It is sensitive to very high and very low salaries and typically produces a larger gap figure.
- Median is based on the middle earner in each group. It is less affected by extremes.
The Commission focuses primarily on the mean total remuneration pay gap, because it best reveals structural inequality in earnings. Where the median shows the ‘typical’ difference between women and men, the mean captures the effect of pay being concentrated at the top of organisations. This includes the overrepresentation of men in highly paid senior roles.
Progress between 2021 and 2025
While gender pay gaps have narrowed within many public sector organisations and in most industries, the sector-wide gap has not narrowed. Understanding this dynamic is essential to interpreting progress on this indicator.
Most organisations are closing their gender pay gaps. The proportion of organisations with a small total remuneration pay gap (+/-3%) rose between 2021 and 2025, while the proportion with moderate to large gaps fell. Some of the largest reductions occurred in traditionally men-concentrated industries and occupations. This is consistent with some organisations beginning to address structural drivers of the pay gap such as gendered occupational segregation and access to higher-paid roles.
At the whole-of-sector level, however, the gender pay gap has not narrowed since 2021. Organisations that reported in both 2021 and 2025 improved on average, and gender pay gaps narrowed across many industries. The 2025 sector-level pay gap therefore reflects broader reporting coverage, and where women and men sit across different industries and pay bands, rather than a decline in pay equity. Closing the sector-wide gap depends not only on action within organisations, but also on reducing gendered occupational and industry segregation (see Indicator 7: Gendered segregation) and the value placed on women-concentrated industries and occupations.
Key data measures are presented in Tables 3.1 to 3.4. Findings are discussed in further detail after the tables.
Table 3.1: Gender pay gap progress
| Measure | 2021 | 2023 | 2025 | Percentage point change 2021-2025 | Progress |
|---|---|---|---|---|---|
| All employees mean base salary gap | 13.8% | 14.3% | 13.3% | -0.5pp | Poor (8 – Matrix) |
| All employees mean total remuneration gap | 15.2% | 15.8% | 15.7% | +0.5pp | Poor (8 – Matrix) |
| Senior leader mean total remuneration gap | n/a | 11.2% | 12.5% | +1.3pp | Poor (8 – Matrix) |
Source: Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: Unlike the overall pay gaps, the Commission can only measure changes in senior leader pay gaps from 2023, when the senior leader category was introduced. You can review the definition of senior leader in the audit guidance. To understand how to interpret the different types of progress ratings, see Data measures in Appendix 1. To read more about how the Commission calculates gender gaps, see Appendix 1. Gender gaps are always calculated between men and women. A gap greater than zero is in favour of men, and a gap less than zero is in favour of women. The percentage point change column may not always reflect the exact difference between years due to rounding.
Table 3.2: Gender pay gap progress by industry (mean total remuneration)
| Industry | 2021 | 2023 | 2025 | Percentage point change 2021-2025 | Progress |
|---|---|---|---|---|---|
| Community and cultural services | 1.9% | 4.8% | 3.7% | +1.8pp | Moderate (9 – Matrix) |
| Finance and insurance | 14.2% | 16.6% | 15.1% | +0.9pp | Poor (8 – Matrix) |
| Local government | 5.7% | 3.5% | 2.4% | -3.3pp | Excellent (18 – Matrix) |
| Other | 11.6% | 7.7% | 6.7% | -4.9pp | Moderate (12 – Matrix) |
| Police and emergency services | 18.1% | 10.5% | 12.0% | -6.1pp | Moderate (11 – Matrix) |
| Public health care | 34.0% | 32.3% | 29.0% | -5.0pp | Moderate (10 – Matrix) |
| TAFE and other education | 8.5% | 8.4% | 8.0% | -0.5pp | Moderate (9 – Matrix) |
| Transport | 10.7% | 13.9% | 14.6% | +3.9pp | Poor (8 – Matrix) |
| Universities | 10.3% | 10.8% | 9.1% | -1.2pp | Moderate (9 – Matrix) |
| Victorian Public Service | 12.1% | 10.1% | 12.1% | 0.0pp | Poor (8 – Matrix) |
| Water and land management | 6.7% | 5.2% | 3.8% | -2.9pp | Moderate (9 – Matrix) |
Source: Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: To understand how to interpret the different types of progress ratings, see Data measures in Appendix 1. To read more about how the Commission calculates gender gaps, see Appendix 1. Gender gaps are always calculated between men and women. A gap greater than zero is in favour of men, and a gap less than zero is in favour of women. The percentage point change column may not always reflect the exact difference between years due to rounding.
Table 3.3: Gender pay gap progress by occupation (mean total remuneration)
| Occupation | 2021 | 2023 | 2025 | Percentage point change 2021-2025 | Progress |
|---|---|---|---|---|---|
| Clerical and administrative | 11.3% | 11.6% | 13.2% | +1.9pp | Poor (8 – Matrix) |
| Community and personal service | 20.0% | 21.7% | 24.1% | +4.1pp | Very Poor (4 – Matrix) |
| Labourers | 19.1% | 11.1% | 9.7% | -9.4pp | Moderate (12 – Matrix) |
| Machinery operators and drivers | 13.1% | 7.4% | 9.8% | -3.3pp | Moderate (9 – Matrix) |
| Managers | 9.7% | 10.4% | 9.3% | -0.4pp | Moderate (9 – Matrix) |
| Professionals | 12.3% | 18.6% | 16.5% | +4.2pp | Poor (8 – Matrix) |
| Sales workers | 13.9% | 17.6% | 20.3% | +6.4pp | Very Poor (4 – Matrix) |
| Technicians and trades | 9.0% | 9.5% | 8.2% | -0.8pp | Moderate (9 – Matrix) |
Source: Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: To understand how to interpret the different types of progress ratings, see Data measures in Appendix 1. To read more about how the Commission calculates gender gaps, see Appendix 1. Gender gaps are always calculated between men and women. A gap greater than zero is in favour of men, and a gap less than zero is in favour of women. The percentage point change column may not always reflect the exact difference between years due to rounding. For further information on the occupation codes used in Table 3.3, see Indicator 7: Gendered segregation.
Table 3.4: Indicative mean total remuneration pay gaps for First Nations people
| Comparator groups | Indicative mean pay gap 2021 | Indicative mean pay gap 2023 | Indicative mean pay gap 2025 | Percentage point change 2021-2025 |
|---|---|---|---|---|
| Non-Indigenous women vs non-Indigenous men | 18.7% | 18.0% | 15.0% | -3.7pp |
| First Nations women vs First Nations men | 11.3% | 15.9% | 9.3% | -2.0pp |
| First Nations men vs non-Indigenous men | 16.6% | 12.7% | 17.1% | +0.6pp |
| First Nations women vs non-Indigenous women | 9.0% | 10.5% | 11.5% | +2.6pp |
| Non-Indigenous women vs First Nations men | 2.6% | 6.0% | -2.6% | -5.1pp |
| First Nations women vs non-Indigenous men | 26.0% | 26.5% | 24.8% | -1.2pp |
Source: People matter survey data, 2021, 2023 and 2025. Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: Table 3.4 presents indicative pay gaps. These figures are drawn from People Matter survey data rather than payroll records, and some comparator groups are based on small numbers of respondents. They should be read as indicative of broad patterns rather than precise measures, and they are not directly comparable with the payroll-based industry and occupational figures in Tables 3.1, 3.2 and 3.3. The Commission has not assigned progress ratings to these measures, given the data limitations. The percentage point change column may not always reflect the exact difference between years due to rounding.
Table 3.5: Indicative mean total remuneration pay gaps for people with disability
| Comparator groups | Indicative mean pay gap 2021 | Indicative mean pay gap 2023 | Indicative mean pay gap 2025 | Percentage point change 2021-2025 |
|---|---|---|---|---|
| Women without disability vs men without disability | 18.9% | 18.4% | 15.2% | -3.6pp |
| Women with disability vs men with disability | 11.5% | 10.5% | 8.9% | -2.6pp |
| Men with disability vs men without disability | 13.0% | 12.2% | 10.4% | -2.6pp |
| Women with disability vs women without disability | 5.1% | 3.7% | 3.6% | -1.5pp |
| Women without disability vs men with disability | 6.8% | 7.1% | 5.4% | -1.3pp |
| Women with disability vs men without disability | 23.0% | 21.4% | 18.3% | -4.7pp |
Source: People matter survey data, 2021, 2023 and 2025. Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: Table 3.5 presents indicative pay gaps. These figures are drawn from People Matter survey data rather than payroll records, and some comparator groups are based on small numbers of respondents. They should be read as indicative of broad patterns rather than precise measures, and they are not directly comparable with the payroll-based industry and occupational figures in Tables 3.1, 3.2 and 3.3. The Commission has not assigned progress ratings to these measures, given the data limitations. The percentage point change column may not always reflect the exact difference between years due to rounding.
Table 3.6: Indicative mean total remuneration pay gaps for culturally and racially marginalised (CARM) people
| Comparator groups | Indicative mean pay gap 2021 | Indicative mean pay gap 2023 | Indicative mean pay gap 2025 | Percentage point change 2021-2025 |
|---|---|---|---|---|
| Non-CARM women vs non-CARM men | 19.2% | 18.1% | 15.3% | -3.9pp |
| CARM women vs CARM men | 15.1% | 17.8% | 13.5% | -1.6pp |
| CARM men vs non-CARM men | 6.9% | 4.6% | 7.3% | +0.3pp |
| CARM women vs non-CARM women | 2.1% | 4.3% | 5.3% | +3.1pp |
| Non-CARM women vs CARM men | 13.2% | 14.1% | 8.7% | -4.5pp |
| CARM women vs non-CARM men | 21.0% | 21.6% | 19.8% | -1.2pp |
Source: People matter survey data, 2021, 2023 and 2025. Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: Table 3.6 presents indicative pay gaps. These figures are drawn from People Matter survey data rather than payroll records, and some comparator groups are based on small numbers of respondents. They should be read as indicative of broad patterns rather than precise measures, and they are not directly comparable with the payroll-based industry and occupational figures in Tables 3.1, 3.2 and 3.3. The Commission has not assigned progress ratings to these measures, given the data limitations. The percentage point change column may not always reflect the exact difference between years due to rounding.
Table 3.7: Indicative mean total remuneration pay gaps by sexual orientation
| Comparator groups | Indicative mean pay gap 2021 | Indicative mean pay gap 2023 | Indicative mean pay gap 2025 | Percentage point change 2021-2025 |
|---|---|---|---|---|
| Straight women vs straight men | 19.1% | 18.2% | 14.8% | -4.3pp |
| Lesbian, gay, bisexual, pansexual or asexual women vs gay, bisexual, pansexual or asexual men | 13.3% | 17.5% | 15.9 | +2.6pp |
| Gay, bisexual, pansexual or asexual men vs straight men | 4.0% | 5.3% | 3.3% | -0.7pp |
| Lesbian, gay, bisexual, pansexual or asexual women vs straight women | -2.8% | 4.5% | 4.6% | +7.4pp |
| Straight women vs gay, bisexual, pansexual or asexual men | 15.7% | 13.6% | 11.9% | -3.8pp |
| Lesbian, gay, bisexual, pansexual or asexual women vs straight men | 16.8% | 21.9% | 18.7% | +1.9pp |
Source: People matter survey data, 2021, 2023 and 2025. Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: Table 3.7 presents indicative pay gaps. These figures are drawn from People Matter survey data rather than payroll records, and some comparator groups are based on small numbers of respondents. They should be read as indicative of broad patterns rather than precise measures, and they are not directly comparable with the payroll-based industry and occupational figures in Tables 3.1, 3.2 and 3.3. The Commission has not assigned progress ratings to these measures, given the data limitations. The percentage point change column may not always reflect the exact difference between years due to rounding.
Table 3.8: Indicative mean total remuneration pay gaps by gender identity
| Comparator groups | Indicative mean pay gap 2021 | Indicative mean pay gap 2023 | Indicative mean pay gap 2025 | Percentage point change 2021-2025 |
|---|---|---|---|---|
| Cisgender women vs cisgender men | 18.6% | 18.1% | 14.9% | -3.7pp |
| Trans, non-binary or gender diverse people vs cisgender women | 0.1% | 5.6% | 10.3% | +10.3pp |
| Trans, non-binary or gender diverse people vs cisgender men | 18.6% | 22.6% | 23.7% | +5.1pp |
Source: People matter survey data, 2021, 2023 and 2025. Workplace gender audit workforce data, 2021, 2023 and 2025.
Notes: Table 3.8 presents indicative pay gaps. These figures are drawn from People Matter survey data rather than payroll records, and some comparator groups are based on small numbers of respondents. They should be read as indicative of broad patterns rather than precise measures, and they are not directly comparable with the payroll-based industry and occupational figures in Tables 3.1, 3.2 and 3.3. The Commission has not assigned progress ratings to these measures, given the data limitations. The percentage point change column may not always reflect the exact difference between years due to rounding.
Estimating indicative pay gaps for groups facing intersecting inequalities
The Commission relies on a combination of anonymous People matter survey data and workforce data to analyse pay inequality for groups facing intersecting inequalities. This is because workforce demographic data reporting rates are very low (aside from gender and age). Respondents to the People matter survey select a full-time equivalent annual salary range within $10,000 brackets. To narrow down these ranges and estimate indicative pay gaps using more accurate pay figures, the Commission combined data from diverse People matter survey respondents with more concrete workforce data on pay.
It did this by assigning base salaries in the workforce data – that is, actual salaries recorded in payroll systems – to the People matter survey base salary ranges selected by diverse respondents. First, mean base salaries within each People matter survey salary range were calculated for each duty holder and each industry group. This means they were taken from the workforce data for all employees within an organisation, regardless of gender or other attributes. The mean base salary for each organisation in each $10,000 bracket was then assigned to each respondent in the survey. Mean base salaries assigned to individual respondents in the survey were then used to estimate an overall, indicative mean for each specific group that was reported on (for example, ‘First Nations women’ or ‘men with disability’). The estimated mean for a particular group was then used to determine an indicative pay gap between 2 specific groups.
Because these indicative pay gaps are not calculated using concrete workforce data on pay, they are not as reliable as other pay gaps represented in this report. Estimating pay gaps using this approach is a way of identifying the approximate scale of pay inequality between groups. But the indicative pay gaps in this report should not be considered an accurate representation of the precise difference in pay between those groups. They are also not comparable to other pay gaps that use payroll records. What they can do, is suggest where pay inequality may be greater for those facing intersecting inequalities. This helps organisations and industries target their efforts to address intersectional gender inequality.
Gender is centralised in this report’s analysis of indicative pay gaps for groups facing intersecting inequalities. The Commission was established with a clear remit in relation to intersectional gender inequality. As such, the Commission’s primary focus is the role of gender in shaping public sector workforces, workplaces and careers. By producing indicative pay gaps between various groups of public sector employees of different genders – who do or do not also share an additional demographic attribute – this report helps demonstrate how gender inequality is compounded by other forms of discrimination.
The intent of this analysis is not to rank different groups facing intersecting inequality against one another with regards to pay. Rather, it is to show how both gender and other forms of discrimination combine to different degrees to increase pay inequality in the Victorian public sector. In reality, individuals’ lived experiences of discrimination can’t be siloed in this way. The experience of gendered racism can’t be neatly isolated into the separate parts of gender inequality and racism. However, looking at the data across a range of demographic variables in this way helps to reveal the contributing factors and hopefully, to help begin to identify root causes that can be addressed. Providing indicative pay gaps across a range of variables also shows where the disparities are starkest. By comparing those who experience a form of compounded gender inequality (such as women with disability) with those who face neither gender inequality, nor the additional inequality examined (such as men without disability), the extent of the pay penalty is made visible. Isolating these groups makes it possible to see how inequalities compound to multiply the lost earnings for those facing intersecting inequality – which have potentially profound financial effects over a lifetime.
Producing pay gaps for groups facing intersecting inequalities is an emerging area of data analysis that is not always approached consistently. Jobs and Skills Australia, for example, use ‘all men’ as a constant comparator to consider how a group facing compounded discrimination is faring (JSA 2025). This has the advantage of demonstrating the extent of the gap for each group compared to a stable figure (the average pay of all men in the sample). However, the limitation of this approach is that it does not demonstrate the full extent of the pay penalty generated by the intersection of gender and another attribute. This is because the sample ‘all men’ includes, for example, culturally and racially marginalised (CARM) men. As such, when the average pay of all men is compared to that of CARM women, it is likely to generate a smaller gap than if you isolate men who do not experience discrimination based on their culture and/or race as the comparator. Both methods are valid and have different advantages.
See Intersectionality at work (2023) for further discussion around language the Commission uses to describe groups that experience compounded discrimination.
Signs of progress
Pay gaps narrowed in key men-concentrated industries and occupations
Some of the strongest reductions in gender pay gaps occurred in traditionally men-concentrated industries and occupations, including police and emergency services (6.1 percentage point reduction), water and land management (2.9 percentage point reduction), labouring roles (9.4 percentage point reduction), machinery operators and drivers (3.3 percentage point reduction) and technicians and trade workers (0.8 percentage point reduction). This pattern is consistent with some organisations beginning to address the structural drivers of inequality, including gendered occupational segregation, progression pathways and access to higher-paid roles.
Many organisations and one industry had a pay gap in the +/-3% range in 2025
Many organisations reduced their pay gaps at the workplace level. The proportion of organisations within the target total remuneration pay gap range (+/-3%) rose by 4.3 percentage points since 2021, while the proportion of organisations with moderate to large gaps declined. This organisation-level progress is the clearest sign that the work duty holders are doing is having a positive effect. As set out above, it is also why a lack of movement in the sector-wide pay gap does not tell the full story.
Local government was the only industry within the target pay gap range of +/-3%. Local government reduced their pay gap from 5.7% in 2021 to 2.4% in 2025.
Police and emergency services and public health care made significant reductions to their pay gaps
The police and emergency services industry reduced its pay gap by the largest margin, from 18.1% in 2021 to 12.0% in 2025.
Public health care (which has the highest pay gap of any industry) reduced its gap by 5.0 percentage points, from 34.0% to 29.0%. The gender pay gap in health care remains very high, but a reduction of this size in a very large, highly women-concentrated industry shows that meaningful change is achievable even where gaps are widest.
Indicative pay gaps narrowed for some groups facing intersecting inequalities
Subject to the data caveats noted above, there were modest improvements for some groups experiencing compounded inequality. The indicative pay gaps for First Nations women and CARM women each narrowed by 1.2 percentage points (compared to non-Indigenous men and non-CARM men respectively). The pay gap for women with disability (compared to men without disability) narrowed by 4.7 percentage points – the most of any group experiencing compounded gender inequality (when compared to men without the attribute).
However, pay gaps widened for other groups. The indicative pay gap for lesbian, gay, bisexual, pansexual or asexual women (compared to straight men) widened slightly (up 1.9 percentage points), and for trans, non-binary and gender-diverse people (compared to cisgender men) it widened more (up 5.1 percentage points). While these figures use smaller samples and should be read with care, the direction of change is a concern. It reinforces the importance of an intersectional approach to pay equity and improving data collection to enable more robust intersectional analysis.
Calculated using the same method, the indicative pay gap between all women and all men was 14.8% in 2025.
Areas for attention
The sector-wide gender pay gap remained stubborn
In 2025, the mean base salary pay gap was 13.3%, down 0.5 percentage points since 2021. The mean total remuneration pay gap was 15.7%, up 0.5 percentage points. These sector-wide figures have barely moved despite pay gaps narrowing within many workplaces and industries. Shifting them requires sustained attention to gendered segregation and to how work in traditionally women-concentrated areas is valued. Organisations must also consider how discretionary and non-base remuneration is distributed, how pay is set, and the conditions that shape careers over time. These conditions include shared care, safe workplaces, and the compounding effects of intersecting discrimination.
More women entered senior leadership, but the senior leader pay gap increased
The mean total remuneration gender pay gap among senior leaders widened between 2023 and 2025, from 11.2% to 12.5%. At the same time, women’s representation in senior leadership rose from 53.1% to 57.3%. This means that more women reached senior leadership, but their growing presence did not translate to comparable pay with men.
The Commission’s audit data identifies 3 potential drivers for this discrepancy. Firstly, trends within the Victorian Public Service industry influenced the changes. The VPS employs around 43% of the of the sector’s senior leaders, so changes within the VPS industry can shape trends at the sector level. Between 2023 and 2025, the VPS senior leader pay gap rose from 5.3% to 8.5%. While other industries also increased or decreased their senior leader pay gaps, the size of the VPS senior leader cohort means changes to its pay gap largely drove the sector-wide increase.
Secondly, women’s increased share of senior leader roles mainly grew in more entry-level and lower-paid roles. This suggests that as more women moved into senior leadership, they entered at the lower-paid end of the executive range. More women clustered in lower-paying roles widened the leadership pay gap, despite women’s representation improving.
Importantly, the Commission’s data shows that there is also a widening gender pay gap towards the top of the leadership structure. Among the most senior roles examined, women’s representation rose from around 48% to 53% between 2023 and 2025, yet the pay gap widened from 6.9% to 8.8%. The drivers of this require investigation.
While not visible within the Commission’s data, research also shows that salary negotiation affects senior leader pay. Men continue to benefit more than women in negotiation (WGEA 2018). This was once attributed to women negotiating less, but more recent research finds women negotiate just as often as men. However, their requests are more likely to be refused (Artz et al. 2016). This creates a double bind: women who negotiate assertively are more likely to be judged as violating gender norms and viewed unfavourably (Rudman and Phelan 2008), while not negotiating entrenches the gender pay gap.
Organisations should analyse their gender pay gaps at every workforce level to understand what is driving them.
Traditionally women-concentrated occupations had the highest pay gaps
Analysis of the gender pay gap at an occupational level reveals persistent, and sometimes unexpected, inequalities. The highest occupational pay gaps in 2025 were in:
- community and personal service workers, at 24.1% (up 4.1 percentage points since 2021)
- sales workers, at 20.3% (up 6.4 percentage points since 2021)
- professionals, at 16.5% (up 4.2 percentage points since 2021)
- clerical and administrative workers, at 13.2% (up 1.9 percentage points since 2021).
The fact that some of the largest gaps sit in traditionally women-concentrated occupations, such as community and personal services, and clerical and administrative work, shows how inequality can persist even where women predominate.
Research reveals various reasons for gendered pay disparities among professionals. As with many pay gaps, it is driven by many small, incremental disadvantages such as the gendered distribution of workplace tasks and the lasting effects of returning from parental leave (Burns et al. 2015). Yet, there is also a greater scope for bargaining and managerial discretion that affects pay for this occupational group, especially in health (Vecchio et al. 2013). It is also worth noting the breadth of the ‘professional’ category in the ANZSCO classification, which can produce data that is difficult to interpret (Wibrow 2022). This is particularly true for women-concentrated occupations (Lind and Colquhoun 2021; Risse 2025).4 Finer disaggregation will be needed to understand pay inequality among professional workers more fully.
Commissioner expectations
The Commissioner expects strong, targeted action on gender pay gaps. Pay gaps are the cumulative result of inequalities across recruitment, promotion, workforce composition, gendered occupational segregation, leave and flexibility, sexual harassment and discrimination. In each duty holder organisation they must be investigated, addressed, and eventually eliminated.
Some drivers of the gender pay gap are structural and sit across whole industries. Others can be addressed directly within organisations. To act on these, duty holders should:
- analyse their own data to understand what is driving any gap
- look at pay differences within occupations and by level: are gaps more pronounced in particular areas? Is one gender overrepresented at certain levels or in certain roles?
- review starting salaries by gender, and examine whether bias is affecting recruitment, promotion and pay
- investigate whether discriminatory practices or unconscious bias exist in organisational culture and norms.
Because the senior leader gender pay gap has widened, and because gaps in higher pay bands translate into large dollar amounts, it is especially important to examine how pay is distributed in the top bands. Duty holders should apply an intersectional lens wherever the data allows, to see where and why inequalities show up.
Gendered occupational and industrial segregation are significant and hard-to-shift drivers. Organisations have little control over the fact that work traditionally associated with men is valued more highly. Addressing this at the structural level includes improving pay in publicly funded, women-concentrated workforces. At the organisational level, duty holders should focus on what they can control. For example, building pathways into roles and areas where particular genders are underrepresented.
Rural and regional snapshot
Rural and regional workplaces face distinct challenges in embedding gender equality. Families can struggle to access adequate flexibility and childcare, which often limits women’s workforce participation. Women in rural and regional areas can also be reluctant to move into senior roles as workloads can be considerably higher than in metropolitan areas and flexibility may be limited (Tischler et al. 2023).
In the Victorian public sector, overall pay gaps were lower in rural areas than in metropolitan Melbourne, but senior leader pay gaps were higher.
Regional pay gaps were slightly higher than metropolitan ones. The mean total remuneration gap in regional areas was 17.0%, compared to 15.6% in metropolitan areas.
Women’s access to career development was significantly lower than men’s in rural areas. In 2025, every location had a career-development gap in favour of men. However, the gap was most pronounced in rural areas (13.1%), compared with metropolitan areas (8.4%) and regional centres (7.9%). See Indicator 5: Recruitment and promotion for more detail on career development.
Alongside the structural factors above, this lack of advancement opportunity may help explain the more pronounced senior leader pay gap in rural areas. It could potentially be constraining both women’s pathways into leadership and their pay once there.
Table 3.9: Mean total remuneration pay gaps and senior leaders pay gaps by location
| Location | Measure | 2023 | 2025 | Percentage point change 2023-2025 |
|---|---|---|---|---|
| Metropolitan | All employees mean total remuneration gap | 16.1% | 15.6% | -0.5pp |
| Regional | All employees mean total remuneration gap | 16.6% | 17.0% | +0.4pp |
| Rural | All employees mean total remuneration gap | 10.7% | 10.9% | +0.2pp |
| Metropolitan | Senior leader mean total remuneration gap | 11.5% | 11.9% | +0.4pp |
| Regional | Senior leader mean total remuneration gap | 7.1% | 12.4% | +5.3pp |
| Rural | Senior leader mean total remuneration gap | 15.7% | 14.7% | -1.0pp |
Source: Workplace gender audit workforce data, 2023 and 2025.
Notes: Location classifications are based on employee workplace postcodes and use the Modified Monash Model (MMM). MMM categories were aggregated into three groups: Metropolitan areas (MMM1), Regional centres and large rural towns (MMM2–MMM3, referred to here as ‘regional’), and Small-medium rural towns and remote areas (MMM4–MMM7, referred to here as ‘rural’). Location data was not collected in the 2021 workplace gender audit.
Footnotes
4: As explained further under Indicator 7: Gendered segregation, the Australian Bureau of Statistics’ change from ANZSCO to OSCA is designed to alleviate some of these concerns (ABS 2024).
Updated