The key objective of gender analysis is to determine whether a policy has a gendered impact and what that impact is. Gender analysis requires policy makers to reflect on the direct and indirect impacts of the proposed policy based on its impact on gender equality.
Gender analysis should be a standard part of effective policy design. Gender analysis is most impactful when incorporated from the beginning of policy design, as it helps inform the policy design from the outset. When undertaken later in the process, gender analysis will still help surface impacts and possible unintended consequences that can be addressed in the design and implementation. Overall, the earlier analysis is undertaken, the easier – and more effective – it will be to design policy that has gender equality benefits.
What is a gendered impact?
A policy may have a gendered impact if it has different or disproportionate impacts based on gender. A gendered impact may occur because of gender norms or biological differences. For instance, Australia’s superannuation system helps people accrue retirement income based on the amount of time they spend in paid employment. Men and women are paid superannuation at the same rate, but on average, women accrue less superannuation. This is the result of multiple factors such as how women on average earn less than men and are more likely to be primary carers. The combination of these factors means they typically spend less time in paid employment which reduces their opportunity to accrue superannuation.
A disproportionate gendered impact may occur because of existing inequalities or patterns of behaviour. For instance, 79.9 per cent of single parents in Australia are women (ABS Labour Force Status of Families). This means that while women and men receive the same rate of Parenting Payment, a change in the rate or eligibility will have a disproportionate impact on women.
Where a policy maker identifies that a policy has a gendered impact, consider whether this is a positive or negative impact on gender equality. To do this, consider current circumstances of inequality, both broadly and specifically to the policy area.
The significance of a gendered impact is a judgment call based on data and evidence, as well a proposal’s policy context and objectives.
A gender impact is likely to be significant if it increases or limits:
- access to resources for one gender compared with others (through income, payments, taxation, superannuation), and/or
- access to opportunities for one gender compared with others (including workforce participation, education, training, health programs, leadership, public office).
The proposal may have a significant impact on gender equality if it relates to:
- family and domestic violence and wellbeing, including online safety, and/or
- unpaid care or household work, and/or
- attitudes or stereotypes about gender and/or
- addressing gender discrimination or advancing gender equality.
The need for gender-disaggregated data
Finding high-quality gender disaggregated data and evidence is a good starting point to identify a proposal’s gendered components. Using gender disaggregated data will strengthen analysis and provide evidence for the impacts of policies. Basing policy in evidence is fundamental to good policy development, and will ensure that your gender analysis has been well considered. Appendix B contains links to a range of useful data sources.
Where gender disaggregated data is not available, policy makers can infer the likely gendered impact using other data. Policy makers can also use qualitative data including research, expert analysis, stakeholder feedback or consultation to understand the gendered impacts of a policy. It is also worth considering whether material relating to states and territories might be appropriate to use where nation-wide information is not available.
The first step to conducting any analysis is to identify whether any gender disaggregated data or other forms of evidence, as outlined above, is available. This research should be used to inform the gender analysis and should be referenced in the Gender Analysis Summary.
Step-by-step process for using evidence and data to inform gender analysis
Note the steps outlined are an iterative process.
Step 1: Define the policy problem and data needed
Articulate the issue that the policy intends to address.
Identify credible data, particularly gender disaggregated data, available on the policy problem. Data may be from government and non-government sources.
- Ensure data is relevant, timely and accurate. Refer to the ABS Data Quality Framework for guidance on good quality data.
Identify any data gaps. Gaps may be due to lack of gender/sex disaggregated data, or more broadly unavailable and incomplete data, including lack of timeliness, accuracy, quality or granularity of the data.
- Acknowledge any limitations associated with the data being referenced. Where quality disaggregated data does not exist, consider how this data can be collected in the future.
What if there are limited data sources?
Lack of data does not suggest the lack of a policy problem, especially where stakeholders or subject matter experts have highlighted one. While quantitative data is important to quantify the impacts of policy, policy makers should look for other ways to understand the full extent of the issue.
Qualitative data such as feedback or other observations from stakeholders, subject matter experts or service providers is important evidence and should be considered alongside quantitative data where available. For example, a service-delivery program that does not collect gender disaggregated data can rely on feedback from service recipients and providers to show the experiences of the people the program targets. This feedback could highlight gendered impacts where different people have different experiences with the services. Policy makers should also consider how data (both qualitative and quantitative) can be collected as part of policy implementation and evaluation, and how this will enrich and expand the evidence base in future.
Step 2: Access the data
Data can be accessed through a variety of means, including through open data, customisable data and non-published data. Policy makers can contact specific data teams across departments/agencies to identify and access relevant non-published data.
- Ensure the data is well organised, accessible to review, and comes from reputable sources. Include the source of data and format the reference to align with the Australian Government Style Manual.
- Include a mix of qualitative and quantitative data where possible. See Appendix B for examples.
Step 3: Analyse the data
Use data disaggregated by gender, sex and other intersectional factors. Observe patterns or relationships in the data and provide logical and plausible explanations for observations.
- Consider any potential biases or limitations associated with the way the data is analysed, collected or presented.
- If needed, seek feedback from peers or experts in the field to review and validate draft analysis. Refer to the ABS Standard for Sex and Gender for further guidance.
Step 4: Assess the policy impact on gender equality
Consider what the data and evidence shows about the current state of gender equality in the policy area.
Consider if the policy proposed includes, or should include, any initiatives that would improve gender equality or address any gender-data gaps within that policy area.
Targeted and proportional analysis
Gender analysis should be targeted and proportional to the scope, value and impact of the proposal. For instance, if a significant gender impact is not clearly emerging in the initial exploration of the data, and this can be demonstrated, then it may be appropriate to end the analysis at this point. This will focus the analysis and direct policy development to where there is likely to be a significant impact, without placing undue burden on policy makers. Using gender disaggregated data helps to uncover these impacts. It is important that departments’ efforts are targeted to proposals with the greatest potential to improve gender equality in response to either existing inequalities or likely exacerbation of inequalities arising from proposals.