There’s a saying out there, that if you’re female, you have to work twice as hard as a man, and that you have to be perfect, just to be able to receive the same level of recognition as our male peers. Recent events highlighted in the media have proven that true, but wonderfully, something else is happening – something that has been a long time coming.
Conversations are being sparked by women brave enough to say “no more”. Predators like Harvey Weinstein, Don Burke and Craig McLachlan, are no longer able to hide behind the systems that give them their power and enable their crimes. High profile women in media and entertainment like Michelle Williams and Lisa Wilkinson have become poster women and the gender pay gap.
Victims always find that they themselves bear the burden of proof, that the onus is on them to prove inequality and injustice, even though they are being beat down and intimidated. And so much of it is unprovable, having happened in private or within an environment where the behaviour is systematic. Then after counting the huge personal cost, many choose to not fight it and to move on.
Even though so many things cannot be quantified, there is still plenty of data for the things that can.
So what else does the available data tell us?
I’ve created the following three visualisations based off available ABS Census in 2016 data:\
Legend: Teal – Male. Coral – Female.
The gender pay gap is alive and well in Australia. It is quite telling that more women than men are earning under the minimum wage, but men earn more once you cross the minimum wage threshold. In fact, the higher the earnings, the higher the probability the income earner is male, and the increase in quite stark.
More women than men also report earning no income at all.
It can be theorised (and there probably is plenty of data and analysis out there to back this up) that women work more part-time hours in order to care for the family.
The following visualisation on childcare certainly seems to support this theory.
On top of that, women also appear to be the primary group providing unpaid care to persons with a disability.
All data has “not stated” and “not applicable” counts removed.
The full visualisation can be accessed on Tableau Public here: Gender Disparity in Income, Childcare and Unpaid Assistance to a Person with Disability in Australia
Australian Bureau of Statistics – Dataset: 2016 Census – Cultural Diversity (Generated 15 January 2018)
SEXP Sex and AGE10P – Age in Ten Year Groups by INCP Total Personal Income (weekly), SEXP Sex and AGE10P – Age in Ten Year Groups by CHCAREP Unpaid Child Care, SEXP Sex and AGE10P – Age in Ten Year Groups by UNCAREP Unpaid Assistance to a Person with a Disability, TableBuilder. Findings based on use of ABS TableBuilder data.