This module is going to look at step two of conducting a GIA, understanding your context.
In many ways this is the biggest and most time-consuming step. The aim here is to use data, research and consultation to build an understanding of how gender shapes the context. So, all of that thinking you did in step one, all that brainstorming, asking the questions and challenging your assumptions, here we take all of that and really solidify it by collecting evidence to understand the context even further.
We want to think about how you might use internal data, desktop research and stakeholder engagement to investigate this further. Template two supports this step, you might like to download that from the Commission's website now and have that side by side as we go through this.
It's also important to think that given this is quite an involved step sometimes, if you are short on resources or time, thinking about how you can best get the evidence that you need to support this step is going to be really crucial.
So first we want to pose some questions. What do we want to find out and how can we find out from data, research and stakeholder engagement? So, asking ourselves some questions around who is likely to be affected? So, thinking about your target population for this policy, program or service, and the other diverse groups who are likely to be affected? How many what proportions of the affected population are likely to be women, men, or different gender identities, gender diverse people?
What various cultural backgrounds, or different age brackets or different socio-economic backgrounds or those living with disabilities and are there any gaps in your knowledge on who is likely to be impacted? How can these be filled in to better build understanding of the context of this proposed policy program or service?
You also want to think about what the lived experiences of diverse groups. So, do women, men, gender diverse people and other diverse communities who are going to be affected by this policy, do they attain the same rates of things like employment, assets, access to decision making, education, wages health care and so forth?
Are there different social expectations and responsibilities for different genders in the community that you are working with? And are there gaps again in your knowledge on the social factors, social expectations and perspectives from different groups, such as people of various ages, cultural and social or socio-economic backgrounds?
Then you also want to think about what different impacts may be likely for different people. So how are diverse communities likely to be impacted? Think about how gender roles, expectations or responsibilities may shape how, when, and why they access or use your service. What barriers might inhibit different genders or diverse community groups from accessing and using a service?
If you go to your toolkit and have a look at pages 22 and 23, it'll talk you through some of this, there’s a really great guiding questions and template for you to work through.
The second part is really thinking about how you can use data and research to get the information you need, and you want to think about what you might already have on hand, so that internal data first up is going to be really important. So, thinking about where you could perhaps access previous commissioned reports, project and program evaluation reports, complaints handling data, customer and end user data, perhaps, including social media data and consultation and policy submissions.
You might also want to conduct some desktop research, a desktop research is a review of existing research for information relevant to a project's needs.
If you have a look at page 25 of your toolkit, you'll see some really great resources for conducting desktop analysis.
It's also important to think about consultation and meaningful stakeholder engagement.
You want to take the time to seek out the knowledge, perspectives and experiences of women, men and gender diverse groups on all of your policies, programs and services, and not just those that target them.
You want to think also about this as a process of creating a more empowering space for all members of the Victorian community to take part in planning and building policies, programs and services, particularly those that engage with on a regular basis.
You also want to consider how you engage with, so not just who you engage with, but how you engage with them.
So, you want to think about have you engaged users of your policy, program or service, have you engaged non-users as well? Have you spoken with local women's organisations or peak bodies that represent diverse groups? This might help you identify barriers and impacts for who would not have who you would not have thought about previously.
And do the stakeholders that you're engaging represent the level of diversity seen in the population that is going to be affected. If not, you might be missing some valuable insights, also thinking about how to engage with people is really important. So, is your stakeholder engagement accessible, do you need to consider time of day for different people's, you know timetables and different needs? Do you need to think about venue accessibility, do you need to think about interpretation services? It's also important to think about whether there are existing mechanisms already in place to seek stakeholder views that would be used for you know further engagement. So rather than overburdening community groups that perhaps are over-consulted. You can think about those existing mechanisms as well.
Have out how you will share the learnings the process of decision making and the outcomes with participating stakeholders? So, all of those things are available for you on page 27 [of the toolkit]. There's a really great checklist to support meaningful and inclusive stakeholder engagement in the toolkit.
There’s also a really great tool that is not mandatory for you to use in your Gender Impact Assessments but might be really useful for you. It's a Quantitative Analysis Tool. I'll show you very, very briefly. The quantitative analysis tool uses a selection of quantitative gender indicators and data so that being population level, ABS data, to help you understand the impacts of your proposed policy, program or service. It can be used at these earliest stages to help understand a policy problem more fully, but you can also use it in your options analysis [Step 3] to maybe help you weigh up options and outcomes possible outcomes. It can also be used to help justify or rationalise a recommendation in step four as well.
So, there's a number of factors that should be considered when using the quantitative tool.
These are known indicators that are impacted, you need to know what needs to be impacted. So, this tool assumes that you can identify the indicators that are likely to be impacted by a policy, let's say the number of jobs created, or the change in skill level or education attained.
It's also one of the limitations about it is that it's a data set that is static, so it's currently using information from 2018-2019 data, but it can be easily updated and if you had the ability or quantitative analytics team who are able to do this, it's absolutely fine for you to adapt this to your needs.
Another limitation that we'd just like to highlight is that the data is incredibly binary, so it looks at, male and female sex disaggregated data there's very little data available at a population base level on gender diverse communities and people, so unfortunately that is one limitation that you'll find working with this tool.
I'm just going to take a moment to show you the functionality of this.
So, we can see here, we've jumped straight into page 26 of the Gender Impact Assessment toolkit. We know it's in step two, because it's the purple colour associated with step two. And on page 26 we have our friendly icon here about ‘taking the next step’.
So, the quantitative analysis, if you have the scope to extend your research even further, you could undertake your own quantitative analysis. This has been developed to support this process, including identifying indicators and estimating policy impacts so it's really about an estimation of policy impacts, based on the data that we have at hand at a population level. Again, I want to stress that this is not mandatory, you don't, you're not required to do this, but it might be really useful in certain contexts. So, we'll just take you through it now really quickly. As you can see here, there's a hyperlink in this pull-out box. If you click on that, then it will take you to an Excel spreadsheet which I'll open now.
So hopefully, appearing on your screen is this Excel spreadsheet which is the quantitative analysis tool. And you can see here that there is a number of different indicators for different areas. So, employment economic resources, education, health care, Safety and Justice and government. So, if any of these areas where you find that this will be useful information for you, then you'll be able to click on these. So, a very simple user-friendly example that I can show you is one of employment. So, if I click on employment here, it'll take me to all of that population level data that we have available in Australia, around the different sectors, different employment level statistics and so forth.
So, a very simple example that I can think of and perhaps salient example for the COVID context is if a policy we’re enacting is, you know, looking to create 3000 jobs for people in let's say the construction industry here we can see that we've got a very gendered workforce. Okay so, 88%, of the workforce in construction is made up of men, and only 12% is made up of women.
Now we might be putting forward a policy that is looking to create say, 3000 jobs, I'll put in 3000 there to the change of employment.
When I press Enter, it will spit out a sort of estimate or presumption based on the data that we have that this particular policy of creating jobs in the construction industry for 3000 people would change employment for women by only 351 people, but it would change male employment considerably, so over two and a half thousand [jobs]. It also gives us the wage data for that. So, looking at the change in wage data, effecting great change for men's wages but not so great for women.
So, we can see that on the surface that an example of that particular policy seems really great of course, it's great to generate jobs for people, particularly in a time of crisis, but it's actually entrenching gender inequality because we know that that particular sector is very gendered. It's not to say that you wouldn't actually take forward that policy, but you might want to think about mitigating factors or you know a particular recruitment drive perhaps to drive female employment and really ‘up’ that [female recruitment], reduce that gender inequality that we would say, as an outcome of that policy.
So that's a very basic example of the functionality, again, reiterating that it is not mandatory for you to take that forward, or for you to, to include in your Gender Impact Assessment but it might be useful for you.
So just moving on now from our quantitative analysis tool and back into step two, and thinking about how we might apply step two, to this hypothetical or to think about it as a process in your own contexts. So, if it's useful to you we can think about this, with this public transport safety policy example that we've been using across some of the other steps, or you can think about how you might adapt this to your context as well.
But really thinking about what it means to apply a gender impact lens and a gender lens, or not to apply one, to step two. So, if we're thinking about not applying this Gender Impact Assessment or to sort of apply the gender lens, in this particular hypothetical example, we might ask ourselves some very general questions, so we might think about what can user data that isn't gender disaggregated from public transport users, tell us about safety? We might think about what our consultations committee community consultation processes, tell us about public transport usage and experienced trends, and we might think about consulting with a very small subset of the community. In this instance maybe public transport staff members.
Now you can see that it's quite narrow, and it's not really applying that gender lens, it's not using gender disaggregated data, it's not widening the scope of consultation and so on.
Now what we want to do is apply a gender lens, so you might want to take a moment to sort of think about with this particular example or another example of your choosing. What types of information would you gather? What type of research would you conduct? and how would you conduct inclusive stakeholder engagement?
I'm just going to pull up a template to, to sort of show you really what the step looks like in practice. So, here we can see template two, understanding that policy context. It's very straightforward, it's actually a PDF that you can type straight into, if that's useful to you or you can adapt it to your own needs, but it really just takes you through some very clear guiding questions around the types of consultation and types of information you might gather. So, what information is already available to understand who is likely to be affected by the policy, program or service, and you can list those that are available. It asks if you've already got this information, or where you will find further information, so it's really good for sort of documenting where you already have this and directing you where you're going to go next.
And then it asks you to record what the research and evidence told you. It also asks if you consulted affected stakeholders on this aspect, it might be yes or no. If yes, give details on what they told you, if no explain why not. And it might be just because you've already consulted them before, it's not appropriate, or you're doing a light touch GIA.
In any case, you can just document the reasons here.
Question two moves on to the information, what information is available to understand the lived experiences of the diverse groups who will be affected, and it takes you through very much the same process. So, the information, if you already have it or where you will go next, what the research or evidence tells you, and have you consulted with affected stakeholders. It asks, ‘How is this policy program or service likely have different impacts on different people?’, and again it takes you through the same process. So that's step two.
You might want to take a moment now to work through that and think about, or even just think about in general terms, what types of information you'd gather for this particular context. Would it be complaints processes to public transport Victoria, would it be Myki data, would you, you know, consult with different groups or would you look at doing some desktop-based research that might look at other jurisdictions in, you know, other either LGAs or other areas around Australia or even internationally if there's any learnings that could be gathered there and applied to this context. So just take a moment now to think about what it is that you would engage with.
So hopefully you've had a think and the outcomes, these are just very general ideas it's not limited to these ideas, but really just to sort of give you some guidance in how you might develop a solution that that benefits the greatest number of people and think about this collecting evidence in order to do that. So, you might be making sure that you specifically investigate those gender issues. So, you might be collecting existing user data that you already have on hand, population data of the region. What do current public transport, you know use, you know, data sets, tell us? What public transport user experience data do you have? Myki data, or, you know, surveys or things like that. Stakeholder consultation and Consultative Committee data, making sure that the any data we have is disaggregated by gender and additional demographic cohorts where possible. This will help to better identify any gender differences in how people experience safety on public transport, that you might need to take into account. You might also complete desktop research on other regions to gather evidence of existing gender impact analysis, public transport usage so how is Transport Safety likely to have different impacts on public transport usage for women, men and gender diverse people, what can wider evidence tell you, and what evidence exists that could be transferred to the Victorian or local context. You might also then want to think about what stakeholders, you might be, you know, engaging with. So, you know, is it women's groups or, you know, particular parenting groups or particular LGBTQI+ groups, any sort of cohorts that you can think possible where you might want to sort of gather their insights and think best about how to do that.
So that's really step two. Step two is really about gathering that evidence and making sure you're going through meaningful consultation with your stakeholders to better understand the context. This is a really important step. It's a very detailed step, and it's really important that you record that detail, because it's really going to help you when you move on to step three, which is your options analysis. You're going to be in the next step developing options based on this data, so making sure it's really rich and meaningful, and specifically investigates those gender issues. We'll move on to step three now, Options Analysis.
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