For various reasons, we keep an eye on what comes out of the Workplace Gender Equality Agency which is the Australian Government statutory agency responsible for promoting and improving gender equality in Australian workplaces.*
Of most interest is the WGEA’s publicly accessible and very search-friendly archive of the required annual reports by relevant Australian employers (non-public sector employers with 100 or more employees in Australia) that detail, among other things, the number (by ‘headcount’) of employees within a specific workplace according to gender and to employment status. Australia’s universities are counted here.
Regarding employment status, the public reports are particularly useful in providing a clear breakdown of the actual number of people employed as or on:
- Full-time permanent staff
- Full-time contract staff
- Part-time permanents
- Part-time contracts
- Casual staff
The reports also give useful information on numbers of people employed in manager and non-manager occupational categories. The latter category is broken down further into professional, technical, community and personal service, clerical and administrative, sales and machinery operators. For our purpose – actual numbers of casual employees in teaching, research and related services – the categories of ‘Professionals’ (ie ‘Academics’) and ‘Clerical and administrative’ (ie ‘General / Professional staff’) seem to be most applicable.**
We need these raw numbers, if only to have a base from which to work towards change. We’ve started some important conversations but without the data (‘What casualisation?’ ‘Where’s the evidence that this is an issue?’) those conversations will stall.
Working in Australian higher education, we’ve also found it frustrating to have the Full-Time Equivalency (FTE) rate applied to everything under the sun, regardless of whether it is actually useful in that particular context. The FTE rate is a very incomplete response to the practical question that’s being asked of our sector: how much casualisation is there? and how much would be too much? How much is too much?
There are three entirely separate ways to approach this question. FTE measures things from the institution’s point of view. What proportion of the budget spent on salaries is directed to insecure employment? Institutions find it fairly easy to round down to a measure around 20% for this, and this kind of figure is often used to rebut claims that Australian higher education has a casualisation problem.
The NTEU and other researchers, particularly including CASA contributor Robyn May, have provided powerful corrective evidence that what matters from a staffing perspective is headcount. Headcount measures the numbers of individuals affected by insecure staffing, and here the proportion rises sharply to near or over 50%. That is, more than half the individual humans employed in higher education don’t know if they’ll have a job next semester, next year, or even next month. Most of these have no leave provisions, very limited capacity to borrow for house financing etc, and they are vanishingly unlikely to be taken into account when universities set their course for the future—even those who have worked for over a decade at the same institution.
And we suspect that there’s a third, underestimated measure that really makes a difference to students: proportion of teaching. This information would be exceptionally easy for institutions to collect, so there’s probably an equally easy-to-understand reason why they don’t. But planning and contractual data exist that would help us understand what proportion of contact hours in any given subject, course, discipline area, Faculty or whole institution is delivered by someone casually hired—someone who doesn’t get invited to curriculum meetings, isn’t supported in their research career, doesn’t have an office or isn’t paid at all to meet with students, doesn’t have the benefit of paid professional development, can’t access teaching grants, has to work when sick, and so on. What is the cumulative impact on a student in a particular degree of repeatedly being taught by those to whom the institution has made the least commitment, and supplied the most meagre resources to support what they do with their students?
So we’re interested in beginning to collect this and other kinds of data, partly as a base from which to contribute to evidence-based change, and partly as a counterweight to the use and abuse of FTE in Australian higher education. To kick off, we’ve put together a very basic spreadsheet that includes the data from the WGEA reports filed by Australian universities for the time period 2013-2014 for all employees counted within the Professional and Clerical and administrative categories*, and all signed off as accurate by each university’s vice-chancellor. And once the reports for 2014-2015 are made public, they will be added. [see Quick Update below]
And please note that we’re both qualitative researchers. We think about how people tell stories of their experience. So if you see something glaring in our interpretation of anything, just holler at us, and tell us why things don’t really work this way. Our purpose in turning to data isn’t to turn ourselves into data experts, but to point out that there are some confronting obfuscations in the use of FTE as the measure of proportion. It’s our view that we all have a shared interest in coming to a better formula for how much—without which no one has means of determining the number that tips the scales as too much.
*The NTEU has also been watching the WGEA figures and have provided a detailed analysis in the latest Advocate (November 2015) here.
**The WGEA reports reveal that Australian universities employ casuals in all the Non-manager occupational categories. However, the two categories with the highest numbers of casual employees in terms of headcount are the Professional and Clerical and Administrative categories.
Since we published this we’ve been asked some helpful questions about consistencies and interpretations in the WGEA data, particularly in relation to whether all institutions interpret the workplace categories in the same way. Thanks to these questions we’ve uncovered some gaps in our own thinking that change the weighting a bit, but not the actual numbers of casuals employed. We also agree that it seems likely that is variance in how institutional reporting interacts with the given categories. All submissions to the WGEA collection are signed off at the highest level within each institution, so the one thing you can be sure of is that each set of figures was prepared and endorsed by the institution that submitted it. So if you work at an Australian university and you want to see how they report the numbers of people casually employed in any category, head to the WGEA site and have a look.
For the moment, we’ve removed the link to the spreadsheet while we update it with a couple of corrections and clarifications. #workinprogress
These are sobering figures. There are 11,000 people at Monash on casual ‘contracts’ and another 10,000 at UNSW. Terrifying!
I find it interesting that some universities are reporting 0 casuals. Did you know that, reportedly, there are no casual staff at all at the University of Adelaide. Isn’t that amazing!
If you scroll across to see the last column ‘Other’, you’ll find those missing casuals. We think this is may be an example of what we said in our update: that reporting across the WGEA’s non-manager occupational categories that don’t directly translate to the occupational categories found at universities, may be quite inconsistent across institutions.
But yes, indeed, they are sobering. I still find myself going back several times to some reports to check because I can’t quite get my head around some of those numbers.
We’re also looking at the extraordinary mismatch between these reported numbers and the numbers used in Annual Reports. Both are institutionally generated, both tell different stories. Annual Report data is typically aggregated (i.e. FTE) but there’s still an astonishing difference. Instinctively I feel that the WGEA data needs better understanding, which is why we’ve begun this process in public, as we work out our own thoughts. WGEA is public data, so technically it should be easier than we are finding it to understand why these different data sources tell such different stories.
We began this process because we wanted to know where something other than FTE was reported, because FTE is such a card trick in terms of human lives. To the layperson it seems very much as though the card trick is played on a revolving table inside a hall of mirrors.
We’ll report any further clarifications we find.