-  Welcome, everybody, to the Australian Disability Clearinghouse on Education and Training, and National Centre for Student Equity and Higher Education webinar.  It's wonderful that we're able to present this webinar in partnership with the National Centre.  The webinar, called Beyond Graduation, a long-term social economic outcome amongst equity students presentation around the research that was recently undertaken.  Before we start, I would like to acknowledge with deep respects the traditional custodians of the land, the Palawa people, and pay my respects to Elders, past, present and emerging.  I’d also like to acknowledge the Tasmanian Aboriginal community who continue to maintain their identity, culture and Aboriginal rights here in Lutruwita. 

Thank you for joining us today.  We're really excited to bring you this webinar in partnership with the National Centre.  Sue Trinidad will be providing the introduction to the webinar and our presenter, but before Sue does that, I wanted to talk about housekeeping for the webinar if people haven’t joined us before.  We are having this webinar captioned by Bradley Reporting.  If you need to access the captions, you can click on the "CC" button on the tool bar which is either at the top or bottom of your screen.  You can increase the number of lines in the caption box by clicking on the small arrow in the top right-hand side.  If you have any technical difficulties throughout, you can email us at admin@adcet.edu.au.  

Wojtek will present for 40 or 50 minutes and then we will have time for questions.  If you want to ask questions, you can do that throughout the webinar in the chat pod.  If you mark the chat pod, you select it with all panelists and attendees.  Everybody can see the questions and it is a great way to keep the engagement going, because sometimes people have the answer to your questions before I have to ask the presenter.  It is another way to engage and keep the conversation going.  I encourage you to participate in the chat pod as well, so playing along at home.  

I think that is all the housekeeping.  So, now I will put it over to you, Sue.  

-  Thank you, Darlene.  We wanted to sincerely thank ADCET, you, Darlene, and Jane, for your ongoing support for us in our wider dissemination and promotion of important national equity research.  As director of the National Centre for Student Equity in Higher Education, it gives us great pleasure to be in partnership with ADCET and to bring you this webinar, Beyond Graduation: long-term socioeconomic outcomes amongst equity students.  Wojtek has undertaken some very important research.  In his webinar, he will present these results from recent research that addresses the knowledge gaps by investigating short and long-term socio-economic trajectories of Australian university graduates from equity groups and compares them with outcomes from non-equity students across multiple domains.  

A little bit about Wojtek.  He is a the Research Group Leader at the Institute for Social Science Research at the University of Queensland and a Senior Research Fellow in the ARC Centre of Excellence on families and children over the last course — or the life course centre.  He is an accomplished international scholar with expertise in quantitative research methods and advanced statistical analysis.  His research interests include education, employment and transitions from school to work.  He has a wealth of knowledge and we're very pleased to be able to present this information to you today.  I will hand this over to you now, Wojtek, and thank you again.  

-  Thank you for your kind introduction and thank you for the opportunity to present this webinar to everybody.  I'm very thrilled to be here and to be able to share the results from this research with people.  This is a recent project that was undertaken by a team of researchers here at the Institute for Social Science Research at the University of Queensland and I want to acknowledge my co-authors, Francisco Perales, Matthias Kubler and Ning Xiang, some of whom might be listening in, so, I just want to say hello.  I really want to acknowledge NCSEHE and support from people in the centre, including Sue.  This piece of research was funded through 2017, the research grant scheme.  We're grateful for the support from the centre.  

I also want to acknowledge support from the ARC Centre of Excellence for children and families, which I am a part of, and the centre has supported this project too by kind of sponsoring, co-contributing some of our time into this project.  

Finally, before I begin, I just want to say that more information or the full results of this research are now available online and so, what I'm going to be presenting has been published in the form of two different outputs.  One is the report for the National Centre for Student Equity and Higher Education and that's available at the NCSEHE website and there is another output that we had just published recently, a month or two ago, a journal article published in the Research in Higher Education and there's links to those outputs.  They're kind of similar, but the original article focuses on low SES students.  The report talks about other equity groups and we focus on slightly different outcomes in the paper and in the report, but I will try to capture all of this as I talk to you.  If you need more information for anything, anything is not clear, feel free to ask questions and I will try and answer at the end, but feel free to grab that paper or that report and just read for more information.  

In terms of motivation for the study, we just started by recognising that there is a wealth of research in terms of documenting benefits of higher education and that's across a range of market and other outcomes.  So, there has been a lot of research showing the higher kind of employment probability for university graduates compared to non-university graduates, occupational status and wages, better physical and mental health, subjective well-being and outcomes.  This research really focuses on the kind of returns to higher education by comparing people who acquire a higher education degree with those who never go to university or don't acquire such a degree.  So, this is a group comparison between those with university degrees and those without university degrees.  

Much less research has been done around investigating outcomes within the group of university graduates and this is something that we wanted to do in this project.  So, we were really interested in answering this question as to whether graduates from different equity backgrounds, from advantaged to disadvantaged backgrounds, benefit from a university degree to the same extent as non-graduates.  So, if you look within the group of university graduates, whether the outcomes are the same for those from more advantaged and more disadvantaged backgrounds.  

We started with reviewing some theories across a number of fields, particularly looking at literature in sociology and economics and we found a lot of theories that were relevant to this issue, but we also found that some different theories predict different outcomes.  We grouped them.  Particularly in the paper, we talk a little bit more about this.  We call them the first set of theories that would predict equal benefits for graduates from advantaged and non-advantaged backgrounds, we call them levelling forces, and we review a number of those theories.  So, why certain theories would predict equal benefits or equal outcomes for equity and non-equity graduates in our case and I need to say that most of this literature has focused on low SES as a particular equity group of interest.  

So, for example, the human capital theories would essentially predict equal benefits because those theories say that university, as any other education, is fundamentally about acquiring certain skills, whether it’s cognitive or non-cognitive skills, but so long as different people acquire the same set of skills, there shouldn't be any differences between them.  So, for example, we have a person from a low SES and non-low SES background who is trained to be a good doctor and lawyer and they acquire the same skills.  You know, they should have equal returns in terms of employment probability or chance of employment or salaries and so on.  

Another set of theories mostly coming from economics, screening theories, signalling theories or credentialism theories and they are slightly different, but they basically give a similar set of arguments around employers using university credentials, university degrees, qualifications, as a signal from employees about their skills.  So, if an employee assists a graduate from the same university with the same degree, the theory says that they have no straightforward ways to gauge their productivity apart through those credentials that they’re presented with.  So, in that sense, again, they should be, in principle, blind to the graduates' background.  

Additionally, there’s a set of sociological theories pointing out that there is a selection into higher education and the decision of whether to go into study at university is not the same sort of decision, it carries a different risk for people from advantaged and disadvantaged backgrounds.  So, disadvantaged families would weigh the relative costs and benefits of participating in higher education, in this example, more carefully and would essentially support children and individuals — would self-select into higher education if they have a high chance of success.  For example, they perform better at school, they have academic ability, they're motivated and so on.  Because of this positive selection, we would actually assume that any potential disadvantages due to, say, low socio-economic status may be overcome or compensated by the positive selection.  

Similarly, a lot of these theories focus on labour market outcomes, but there is also other theories that could be applied to predict equal benefits for disadvantaged and non-disadvantaged graduates beyond labour market outcomes.  So, when we look at health and wellbeing, for example, there’s research and theories pointing at increased cognitive and non-cognitive endowments according to higher education and, again, that would predict that a low SES and high SES, for example, graduates would have similar health and wellbeing outcomes.  There’s also the indirect effects through better jobs, improved wealth and income that I've already mentioned.  All this would essentially assume that so long as students from a more disadvantaged or more advantaged background can complete university, they should be expecting similar outcomes.  

However, there is also another set of theories to which, in the paper, we refer to as stratifying forces and those theories predict unequal benefits.  A lot of those theories come from sociology.  So, there’s theories like social capital theories or culture capital theories that would underline the role of information, social networks, cultural know-how.  So, the kind of people's ability to navigate the selection process, for example, in terms of employment, post-graduation, social networks, professional networks, that which enable people from all backgrounds to get an edge or get a job more quickly than someone from a disadvantaged background.  

Another theory is, for example, the effectively maintaining equality theory would predict that as higher education becomes more common, as has been the case in Australia, more advantaged families would find ways to differentiate themselves from more disadvantaged families within the group of people who acquire higher education credentials, and this is done, for example, by enrolling into better, more prestigious universities or degrees.  So, this theory would predict that even though on the surface you might say that a lot of people from, say, low and high socio-economic backgrounds acquire a university degree, when you look more closely, you will see that the people from more advantaged backgrounds are more likely to graduate from universities and obtain degrees that will lead to a better outcome post-graduation, prestigious degrees like law or medicine, for example.  

Finally, when we look to life-course perspective, this perspective recognises that advantage and disadvantage accumulates over time and it is interrelated across different life domains.  This perspective would predict that people from disadvantaged backgrounds, like low SES families, would not only be less likely to, for example, enrol into university, but they're more likely to have other problems that are not directly related to education.  For example, they might be more likely to have family members that are dependent on them financially or they might have health issues or family members with health issues.  All of this complex disadvantage will eventually impact on their chances, even if they graduate from university.  

So, we recognise that all of those mechanisms and in particular, the stratifying and levelling forces operate at the same time, it's not just one thing that’s operating at a particular time, it’s multiple things at the same time.  You would predict, and this is a prediction we make in the paper, that the stratifying forces, even though people might be acquiring skills that they learn during the course of university studies at the same pace, for example, even if you assume that low SES and high SES people do that, then all of those things that we just talked about in terms of social capital and cultural capital, for example, would give an edge to graduates from more advantaged backgrounds.  

We have also reviewed empirical evidence, both international and Australian literature, and most studies focus on labour market outcomes and low SES as a particular category, and they provide a somewhat mixed picture.  Initially, there was a series of research papers by Mike Hout and others in the United States back in the 90s showing an association between socioeconomic backgrounds and occupational status among US graduates and that was taken as a sign of meritocratic function of the university initially.  The university was seen as this great equaliser that once you've obtained your university degree, it doesn't matter where you came from in terms of your social origins, but subsequent studies found the fact of socioeconomic backgrounds that when you look into particular subgroups like graduate students or postgraduate students, or certain fields of study, and negative effects of disadvantaged backgrounds on labour market outcomes have also been found in a number of countries outside of the US.  So, for example, such effects have been found in several European countries.  

Very few studies explored … of the time, although those few that do indicate that any differences, any initial differences between advantaged and disadvantaged graduates will decrease over time and this again might also explain some of those early findings about the lack of association between SES backgrounds and occupational status in the US.  

The last thing that I want to say on this is that most studies focus on the absolute difference in outcomes between advantaged and non-disadvantaged graduates, rather than on the relative gain.  So, studies would look at, say, for example, the difference in salaries or earnings between low SES and high SES graduates, in terms of the dollar value.  Very few studies have looked at the kind of relative gain, so, compared to how much actually different groups of graduates gain in terms of, say, increased or improved earnings compared to the baseline that was the situation before graduation, so, where they came from.  We think it's an interesting thing to look at and might give you a slightly different perspective on things as well.  

The final comment on this is there's very little evidence on non-labour market related outcomes, so a lot of research has focused on labour market outcomes.  

In the Australian context, a lot of this would be very familiar to you, but there's been a huge growth in the higher education sector since the early 90s.  There has been a dedicated focus on higher education equity, and since the early 90s, six groups have been officially disconnected equity groups in higher education in Australia, Aboriginal and Torres Strait Islander people, people from low socio-economic backgrounds, non-English speaking backgrounds, regional and remote areas, people with disability and women in nontraditional subject areas.  In this study, we focus on the first five.  We don't look at women in nontraditional subject areas, but we do look at all the other five groups.  

However, despite equity being really high on the policy agenda, there is surprisingly little research looking at graduates from equity groups.  A lot of research focuses on the issues around access and completion, success in higher education, but few studies look beyond graduation.  

We reviewed those that do and this table here in slide summarises the study that we looked at.  The common feature here is that the time of the graduation is relatively short, up to three/five years, but typically it’s about four to six months and they use dedicated graduate surveys that come with certain limitations and problems.  

We reviewed this literature and I won't go into a great deal of detail about this here, but you can read more in the report, but in summary, the empirical evidence for Australia shows a mixed picture.  For the labour market outcomes, there's very, very few studies, hardly anybody look at non-labour market outcomes.  So, in terms of labour market outcomes, what we see in the previous studies is that graduates from low SES, remote and regional areas and non-English speaking backgrounds, some studies found those groups to have had poorer labour market outcomes.  For example, lower employment rate and lower salaries.  However, there are other studies that report similar outcomes for those groups, and I think there is a bit of a pattern where studies that look at outcomes further, several years after graduation, that see less of a difference compared to those that look at shortly after graduation, the first four to six months, there seems to a difference.  So, that's for low SES and remote and regional students and NESB.  Evidence is more consistent for graduates with disability and those from Indigenous backgrounds where evidence suggests that the graduates with disability have worse labour market outcomes, while the Indigenous — graduates with Indigenous backgrounds have, on average, according to previous studies, better labour market outcomes than the rest of the graduate population.  I need to say that this particular finding around Indigenous graduates has a lot to do with selection into the subpopulation of graduates from universities, so we know that people from Indigenous backgrounds face a number of areas and there are a huge selection in terms of accessing university and then, also the completion rates are lower for Indigenous students.  Those who survive to graduation are a quite select group of graduates compared to the Indigenous population as a whole.  

Those studies have generally been affected by data limitations, definitional issues and, as already noted, have a short time horizon and predominantly focus on labour market outcomes.  

In summary, the research gaps and contributions related to them are the following that previous studies have mostly focused on the labour market outcomes.  They looked at outcomes beyond labour market related outcomes.  Typically, studies have only a short time horizon and focus on short-term outcomes.  Few studies look at longer term outcomes.  It is typically focused on absolute outcomes as opposed to relative comparisons, comparing before and after outcomes for graduates from different groups.  Much of the evidence is limited to the low SES group comparing low SES and high SES graduates and other equity groups with less study.  

Moving on to the research questions building on those gaps, the first research question that we ask is, do equity graduates have post university outcomes comparable to non-equity graduates and whether this changes over the short and long-term.  We explore a range of outcomes and we also investigate five groups, as I already mentioned, and we’ll tell you a little bit more about it in a second.

The second research question is around patterns over time, is there a convergence of outcomes between equity and non-equity graduates over time?  And the third question is about the absolute and relative benefits of higher education, whether absolute and relative perspectives tell us a different story or the same sort of story.

In terms of data, we used two data sets for this research project, both large scale and robust data sets.  The first one is the Australian Longitudinal Census Data, or the ALCD, or in short, I’ll be calling it the census data.  This covers a 5 per cent sample of the Australian population who provided information from 2011 and 2016.  We’ve got a 5-year gap between the two census waves.  The census data largely focused on labour market outcomes.  For this project, we focused on the subset of people aged 15 to 17 in 2011 and we observed the outcomes in 2016.  So, when those people are aged 20 to 22.  The outcomes are captured up to two years after graduation.  On average, it will be about a year after graduation for this.  The reason we selected this sample is that due to the nature of the census data, we need to draw on the information about students and graduates' families and so, for example, if you want to know their parental occupation status or where they live, their place of residence, for that, we might need an indicator of low SES or regional and remote indicator.  We need to know at the time they were — they still lived with their parents, that's why we focused on 15 to 17 year cohort and we know five years down the track, we know that within this time window, they graduated from university.  We know that.  We can't really pinpoint exactly a time of graduation, for example, but we know it is reasonable to assume that they have been living with parents, so we can find out about their parents, so we can see what happens to them five years down the track.  

The second dataset we used is the Household Income and Labour Dynamics in Australia survey, or the HILDA survey.  It is a large nationally-representative survey, very comprehensive.  It collects data annually between 2001-16.  We used all different waves of data that’s available to date.  The survey captures both labour and non-labour market outcomes.  We really focused with HILDA on those non-labour market outcomes because the labour market outcomes are also captured in the census data.  With this data, we are able to explore how outcomes evolve for up to 15 years after the attainment of a bachelor's degree up to 15 years after graduation.  With the HILDA data, we can pinpoint the year of graduation and we can start tracking people from that point onwards.  We have up to 15 years worth of data beyond graduation.  

The example is about 900 people for the HILDA survey, about 2,500-3,000 cases for the census data. 

In terms of the key variables, we focused on five population-based equity groups, low SES, Aboriginal and Torres Strait Islander graduates, regional and remote graduates, non-English speaking graduates and graduates with a disability at the time of graduation.  I need to say that the definitions — the operational definitions vary across the two datasets due to the nature of the data and data limitations.  

We also used a combined equity group indicator in the HILDA analysis.  I will show you some of the results for that indicator.  

In terms of the outcome variables, Census enabled us to capture employment-related variables, we looked at employment status, full-time employment and some other variables related to employment.  With HILDA, we can also look at some indicators of jobs related to jobs and finances, like hourly wages which we only do for low SES for the paper.  In the report, we show results for perceived job security, job satisfaction and financial prosperity, but the key advantage of the HILDA data is we can look at health and wellbeing outcomes, things like general health, mental health, life satisfaction, social support, and we've got a number of control variables that we also include in our models.  

I won't go into the detail of this, but we used quite advanced statistical modelling.  With census data, we apply logistical regression and outcomes are captured up to two years, typically about a year after graduation.  With HILDA analysis, we do two things.  We use growth models, two-model trajectory outcomes post-graduation, so, for up to 15 years after the people graduate, so, from that point of graduation, and we also run a fixed model where we essentially compare outcomes before and after graduation and this is for this last research question about relative gains.  So, for that purpose, we are really interested in what's a relative gain for different groups on certain outcomes.  

I'm going to move straight into the results.  The first set of results is from the census data.  So, it's comparing outcomes up to two years after graduation.  In this table, we don't need to look at the curvations.  In terms of the key findings, this is consistent with previous studies, we find that low SES and NESB graduates are less likely to be in employment, employed in a managerial or professional occupation, and less likely to have a high personal income if they are in full-time employment.  These are the coefficients here and also marked with a star, which means they are significant.  

Graduates with disability were less likely to be employed and also less likely to be employed full-time.  If you're curious about the colours, that just highlights things, the coefficients have changed when we added the field of study, which is also controlled in this result, so these are the effects that I explain by the field of study.  This is the final model with all the variables included.  

We do see some initial… in this short period after graduation, up to two years.  There is some evidence for disadvantaged that carries over to labour market outcomes beyond graduation for certain groups.  

Moving on to the results from the HILDA data, comparing trajectories up to 15 years after graduation, this first set of results is looking at the combined indicators, so whether somebody was a member of any of the five equity groups we looked at versus no equity status.  In terms of the job and financial-related indicators, there appear to be some initial differences and then we observe a convergence between equity and non-equity students, so in this slide, for example, we look at financial prosperity or job security.  We see this initial gap as indicated by the lines that are separated and the confidence intervals don't overlap, but we see there is a degree of convergence.  

This next slide shows, again, for the same group, same comparison, so a member of any equity group, any of the five versus other students, shows outcomes for health and wellbeing.  The picture is less clear here.  There are differences in terms of health and support.  In general, we would say that the trajectories are similar for this overall group comparison.  

I’ll now move on to looking at the results from some specific groups.  When we look at the low SES versus high SES students, these graphs comes from the paper.  It uses slightly different models, specifications, … term which is why you see those curves rather than straight lines, and uses a set of slightly different outcome variables.  It includes … outcomes.  Again, the story is that we concluded, we see initial dysfunction on some of the outcomes, specifically job security and financial prosperity for low SES graduates, but then we observed this catch-up at about four to five years after graduation where the difference between low and high SES graduates disappears, so there is this sort of catch-up.  

Now, I just want to talk about another example which is just a — there's lots of results in the report, particularly if you look…  I mean, if you go to the report, you will find full sets of results mostly in the appendix summarised in the report, but for every equity group and every outcome, you will find the figures and results for that.  I'm just focusing on selected examples here.  This is an interesting example.  The caveat is with HILDA, in this particular analysis, we only have a small number of people in this group of Indigenous graduates.  So, we have got potentially a small sample issue, but, nevertheless, I think this set of results is very interesting and the results are significant.  They show persistent differences across health and wellbeing indicators that don’t go away in time, so there is no catch-up.  There’s differences on general health, mental health, life satisfaction, social support, those differences between Indigenous and non-Indigenous graduates persist over time.  

I think this is the final example from this analysis.  This is for graduates with disability versus solid graduates.  A little bit similar to the Indigenous group, but certainly in terms of the initial situation, there are significant differences across all the indicators, all the outcomes in the health and wellbeing domain, but apart from the general health, there seems to be a catch-up on things like mental health, life satisfaction, social support and it's not something that we could explain with our data or we could not really provide an explanation, but much like with the Indigenous, we see it as a potentially interesting pattern that could be followed up in future research.  

Just very briefly, I want to talk about the last set of results that compared before and after graduation outcomes.  We're also interested not only in looking at the kind of absolute differences between equity and non-equity graduates, which we've done in all of those I showed you just now, just before, but we also were interested in looking at the kind of relative gain.  If we compare general health and mental health before people obtained a degree, and that includes the period of time before university, if we compare the mental health or life satisfaction in that period before graduation and then we compare that to life satisfaction averaged across the time after graduation, what do we see and what's that kind of relative gain or relative loss.  So, the results were kind of interesting and a bit surprising.  So, for the low SES group that we focus on in the journal article, and it is not shown in this slide, we got results that are kind of consistent with the limited previous research done on this, so those results suggested that low SES graduates benefit — in terms of certain outcomes at least, benefit more in relative terms on some of the indicators, compared with high SES graduates.  Even though the absolute outcomes might be lower, the relative gain is potentially higher on some of those indicators because of the essentially lower starting level in terms of, say, financial prosperity.  So, even if they earn similar or slightly lower salaries than high SES graduates because of where they come from, the relative gain is potentially higher.  

A bit surprisingly, we found very interesting patterns for the Aboriginal and Torres Strait Islander graduates that essentially suggests that those graduates recorded a decline across the board pretty much in terms of health and wellbeing indicators, so, general health, mental health and life satisfaction appears to be lower for those graduates compared to what it was before graduation.  Again, we don't really have an explanation for this and I need to repeat the caveat around small sample size, that the results are significant and it is potentially pointing out something that's there that can be followed by future research.  

In summary, what we’ve done in this study, we leveraged robust large-scale data from the Census and HILDA.  We focused on five population-based equity groups, low SES, ATSI, NESB, regional/rural areas and graduates with disability.  

We explored both short-term outcomes, up to two years after graduation, and also long-term trajectories over time, up to 15 years beyond graduation, and we investigated both labour market and non-labour market outcomes, including health and wellbeing.  

In terms of the key findings, just to repeat, there are some initial disadvantages for equity students and this is constant with previous literature in that, for example, low SES graduates are less likely to be employed and have lower income/salaries; graduates with disability are less likely to be employed and in full time.  NESB graduates are less likely to be in employment and have lower salary.  It is consistent with the previous literature, but also it is a bit inconsistent with what you find in studies that look at access and completion, for example, when non-English speaking students are typically not disadvantaged in Australian higher education.  This is an interesting finding to that.  There seems to be going on in terms of employment beyond graduation that's different from the pattern that we observe up to the point of university completion. 

The second finding was there's differences for the outcomes we could capture - generally disappears over time.  … related to subjective assessment of financial prosperity and job security, but also for social support.  However, the pattern is different for graduates of an Aboriginal or Torres Strait Islander background and to some extent, for students with disabilities.  These graduates report significantly poorer outcomes that persist over time and particularly in terms of physical and mental health outcomes compared to the non-equity counterparts.  

Evidence is a bit mixed in terms of the relative gains and research questions and it depends on the equity group.  For low SES graduates, as I just said, we find that they appear to benefit potentially more in the relative terms, despite not better absolute outcomes.  However, for Indigenous students we, again, find that decline on the number of indicators related to health and wellbeing when we compare the before and after graduation outcomes.  

-  Wojtek, just to let you know, we’re actually at the 50-minute mark.  I know you’ve only got two slides to go, but if anyone’s got any questions, please add it to the question pod and hopefully, we might get to a couple just as you end.

-  This is my last slide, just to conclude.  In the case of most equity groups, the trajectories of equity graduates and non-equity graduates appear to converge despite initial differences.  So, those disappear after several years, but arguably more could be done to prevent this relatively long catch-up.  Sometimes, it's four/five, sometimes, up to seven years depending on the outcome, and to give an equal start to all university graduates.  We think that universities may play a role here by focusing on boosting employability, but also thinking about the health and wellbeing of the students and graduates because there seems to be some gaps too.  

The sort of findings, particularly for Indigenous graduates, but also graduates with disability, is particularly striking.  Again, you need to make the caveat about small sample sizes in our study.  We think that something that could be followed up and I will just — this is what I said in materials of the limitations, we have been limited by small sample sizes, despite the fact that we used robust data because of the way we had to select our sample, focusing on graduates and graduates from those equity groups, some of which are relatively small.  We end up with relatively few graduates in our analytic dataset.  So, we think using large-scale administrative data is one avenue, but also, perhaps more importantly, we think that there's certainly room for qualitative research and mixed-method research to explain some of those findings.  

Thank you.  

-  Wonderful.  Thank you very much for that.  We have received a couple of questions.  I didn't check before we caught up.  Are you happy to answer questions afterwards if we don't get to them all?  

-  Sure.  

-  We will put them up on the website afterwards, if there’s any that needed to be answered.  

One question that was asked was, were you able to account for any variables or difference if disability or was it just one identifying category type - was it just disability in general or was it disability types?  

-  It was just one in general.  I've received a few questions before the seminar and typically, the answer would be similar.  The answer is that unfortunately, due to the data limitations, because of the way we set up the samples, we really wanted to capture when people graduate or kind of at least approximately, and so that kind of — that basically restricts your sample to the people that you're able to observe as graduating rather than people who actually hold a university degree already.  That limits the sample size.  Then, when you overlap the kind of equity groups onto that, you end up with relatively small samples, so no, we're not… there could be ways with some of the data, not with HILDA, but with some of the data at the Australian Bureau of Statistics holds that could be ways to delve more deeply into subcategories within the disability category, also within the non-English speaking background.  For example, we could potentially look at people with certain visa types, for example, humanitarian migrants.  This wasn't possible in this project.  There is a new project funded by the NCSEHE that we're doing, looking at refugees.  If people are interested in this particular group, we use different data, but that should be coming up in several months.  

-  Did the institution play a role?  Was there better outcomes for equity graduates from particular institutional groupings, such as the G8s?  

-  This is a major limitation of this study that I skimmed through.  The only thing that we were able to do, particularly with HILDA, with HILDA, the only thing we were able to do was to have a control, not really look within the categories, but we had a control for study level, whether it was post-graduate degree or graduate degree.  With census data, we included the field of study, a detailed variable, but we didn't include university type and we weren't able to look within or compare across specific categories comparing across the kind of categories of disadvantaged and non-disadvantaged.  Again, something for the future.  You could look more, delve more deeply, stratified this by — even by gender, but by field of study, look for differences across different university groups, some of those theories I mentioned would predict things that would kind of — that would be interesting to look at, where people from more advantaged backgrounds are more likely to enrol in more prestigious fields of study.  Whether that translates into better outcomes, we weren’t able to do that in this study.

-  Another thing that may not have come up in this study was around enabling programs because more and more people are accessing university through those.  Did you look at students who had come through that tertiary education?  

-  No.  What I showed you — I only showed you a kind of selected results, but more results are in the report, but the results in the report are really of the same kind.  This is just really the extent of what we could do with this data.  So, similarly, it wasn't part of this project to look at the kind of practice within universities in terms of, you know, was there … for different people from different backgrounds to go through university and graduate, we couldn’t look at university practices in terms of employability skills, what they actually do to help graduates in that transition.  We couldn't do that.  This is a follow-up research project.  

-  I think that is that call to arms.  Someone has written that around how can we make the changes to improve the outcomes.  I think having the National Centre join us today, there are equity groups such as students with disabilities and students from Aboriginal backgrounds who have poorer outcomes, what can we do to improve that?  Can we use research to inform our practice in the university sectors?  

We're coming to the end now.  For the questions that we didn't answer, we will answer those and put them up online.  

Just a little plug before everybody goes is that our next webinar will be on 20 November, which will be with the Royal Institute of Deaf and Blind Children.  It will be around accessible assessments for students with vision impairment.  This has come from the round table, they’ve developed the guidelines on how to do an accessible assessment.  So, it will be useful for many of us in the tertiary sector to ensure that students who are blind or have a vision impairment can access their assessments.  

Thank you, Wojtek, for joining us.  I'm not good with data, but I was excited by some of the data you shared today.  It has started a really important conversation for a lot of equity groups.  

-  That's right.  I want to say, I see this piece of research as something — as a starting point.  We documented some interesting kind of gaps and findings that will probably lend itself to interesting further research.  So, we are very open to collaborate with other people, so if somebody is interested and wants to do a follow-up research with us, please get in touch.  We're keen to collaborate with other people.  

-  Thank you to Sue and Nina from the National Centre to help us to bring this together and to Jane and also, the captioner.  

Thank you, everyone, for joining us.  Have a great day.  Thank you once again, Wojtek, for presenting your knowledge to us.  

-  Thank you for the opportunity.  

-  Bye.  

-  Bye.