A few weeks ago I had a meeting with my PhD supervisors. Gave them draft chapters, chapter outlines and results enough for a couple more. I asked them, in their experience, if they thought it could be submitted by mid next year and what advice they’d give me if I went for it. Straight off the bat, one of them remarked: “Don’t get pregnant.”
It’s kind of hard for me to do that. I’m a dude with an unappealing mo’ for a start. But it did get me thinking about why they’d say that. I don’t have the numbers on what starting a family does to PhD progress but a brilliant friend of mine could probably tell you. He’s just had his first child, with some complications and he’s temporarily suspended his PhD. His suspension is not the only one within our school due to marriages, babies, cancer or other major life or family events. I started having a poke around some of the stats out there for probability of life events and came across the latest HILDA survey.
I’m no statistician but I’ve tried to pull out some meaningful numbers that might be used with caution. On the matter of caution, caveats.
The HILDA survey is nationally representative for Australia and is intended to describe the average Austray-yan. The HILDA survey is not intended to be representative of Australian PhDs nor of residents of major cities, where universities are generally located. There are many international students among us, we’re mobile and at the high end of the education spectrum, so our rates of life event experience may differ to population average.
Second caveat, where described as ‘in any given year’ I’ve used the most recent year from the HILDA survey (2009-2010), which was a bit of a shakedown year, due to the GFC, in which many people made major life adjustments (me included). Third caveat, many probabilities are quoted on an annual basis and caution should be taken extrapolating to estimates of cumulative probability over a longer time period.
Considering caveats let us agree the numbers are rubbery and incomplete, based on observation of a broader population in a time and place we no longer inhabit. The statistical quibblers may cheerily point out that this data set is not perfect. But then again, quibblers gonna quibble. No dataset is perfect. These numbers are available and we may use them as general indicators with a certain degree of caution.
Selected statistics on marriage, income and ‘getting pregnant’ in Australia:
I’ve kept the focus on a few select events and not included a lot of other major life events such as death, serious injury, moving country or discovering Eddie Izzard clips on youtube.Here’s a brief selection of probabilities for major life events:
Source: Eighth statistical report from HILDA
The arrival of children affects household income. Couples with children already will generally find their family income reduces in the short term (one year) but increases in the long term (four or five years). Couples without children will find their income drastically reduces when they start to have children, which is seen as a long term effect.
APA Scholarships for PhDs are approximately $22,500 per year tax free. The ABS recognises relative poverty as income less than 50% of the median for the household-equivalent individual income, which was about $19,990 in 2010. Without additional sources of income or a supporting partner, your average PhD is slightly above what the ABS calls relative poverty.
We know a little bit about happiness and can make estimates for the effect of major life events.
One of the biggest effects seems to be a major worsening of financial situation, which is comparable in its effect on happiness to being a victim of violent crime or separating from a spouse with whom you have young children. A major worsening of the financial situation gives us around about a seven percentage point reduction in probability of becoming a home owner, all other things considered. That’s pretty big reduction when we consider the base rate for buying a home is 10 percentage points over the long term (eight year study period, 2002-2010). We note that the arrival of children, getting a bachelor degree or the being the victim of property crime gives us a greater propensity to become a home owner.
What does this mean for an average PhD student?
The average first year PhD in Australia is about 34 years old at the moment. Let’s say Jill is 34, currently single and has come from a well paying job prior to starting the PhD. If she doesn’t have alternative sources of income while studying then six months into her PhD she is decidedly unhappy. It’s an unhappiness effect that measures somewhere between separating from a partner with whom you have young children and the death of a spouse or child. So she’s pretty down about her life.
In her first year of the PhD she will have an 8.8% probability of getting married, but after she turns 35 it reduces to a 4.7% annual probability of marriage in any given year. Over the three year PhD this cumulative probability of marriage might be somewhere between 10 and 20%. If she stays single, she’ll have up to a cumulative probability of having a child somewhere between 5 and 13%. If she gets married then the probability increases a few percentage points. Having a child and being in a couple will offset the effect on home ownership propensity, but the mere act of taking the pay cut to do a PhD is going to significantly reduce her probability of buying a house in the next eight years.
What about a bloke, Jack, who’s married without kids at the start of his PhD and it takes him five years? In that time he’s got a 6% probability of getting a divorce and a 15.4% probability of having kids. If his partner doesn’t have maternity leave, then they’ll be in relative poverty.
What does this mean for universities?
Supervisors are always surprised when non-university issues confound the progress of students. Students are dumfounded when supervisors are unavailable while they deal with their own life and family events. Yet the baseline probabilities indicate that these events are highly prevalent. Over the course of a PhD they are likely to affect a good proportion of PhDs and their supervisors.
The numbers are rubbery but if we consider marriages and births alone, for every five married PhDs we might expect at least one to have a child or get a divorce at some point during the four years it takes to complete a PhD (about the Australian average for a full time PhD). The numbers for unmarried PhDs getting hitched and having babies might be closer one in four PhDs. These tend to be serious events that can cause deferment or exit from the PhD program, not to mention the potential to give PhDs the real sads (not all events to be sure, I hear marriages and births are fun). We note the different impacts between men and women of marriages and births.
Some of these life events can be planned, but many are surprises. Looking at baseline probabilities, your average PhD runs a good risk of getting pregnant, married, divorced or just plain sad while they’re working away. The probabilities are heightened by age group and life choices that mark the demographic. Most PhD scholarships contain a variety of leave and temporary support mechanisms but they’re not always clear or consistent between scholarship types.
I expect the leading universities and colleges have their programs, policies and counselling services at ready for dealing with these issues too. However, I’ve not seen much of these responses formalised or resourced and I’m not sure if they’re commensurate with the occurrence of these events within a large student body. I’ve heard senior academics describe the resources available for these events as ‘what we can find down the down the back of the couch.’ With 100 PhDs enrolled in my school and 2,400 in the university, there is might be a student every fortnight in my school and ten students a week across the university who go rummaging down the back of the metaphorical couch.
A university policy of “Don’t get pregnant” is laughable in this sense.
Author Bio: Walter is a PhD student at ANU’s Fenner school where he is investigating demand management policy for residential water and electricity use. Walter is now at the pointy end of his degree, but he took time out to play with the stats and tell you what the likelihood is of you encountering a major life event during your PhD.