In 2009, the short list of five was all male. This event was widely referred to as the “sausage fest.” In response to the perceived gender bias suggested by this result, the female only Stella Awards were created as a response (by editor Aviva Tuffield and author Sophie Cunnigham).

The latest Miles Franklin award short list contains three females and no males. No pejorative “fest” term has described it as yet. And nor should it, unless one believes that there has been some intrinsic bias in the selection process. Is a result of either zero or five males from five (nominally a 1 in32 shot) evidence of gender bias?

Since the Miles Franklin award began, 13 winners out of 55 have been female. No need to test an hypothsis there. However, taking data from 1957 is about as fair as Andrew Bolt taking climate data from the temperature peak of 1998. Nobody denies that the playing field was uneven in 1957. The question is whether it is uneven in recent times.

Below are the data on the short listed authors back to 1993. Why did I choose shortlisted authors? Partly because this was the source of the original controversy. It  also carries more information than just looking at the winners data so any data patterns will be clearer. There is no question that there have been fewer females winners over the full 55 years though this is less the case recently (for instance 4 of the last 10, factoring in a female winner this year!). Why from 1993? No real reason. I got tired and I thought 20 years was enough. If you want to get more data it is all there on Wiki but you have to search some of the author names that are gender neutral. Oh, and by the way. Miles Franklin was a woman.

Miles Franklin short-list record, 1993-2013

1993: 3 males out of 6
1994: 3 males out of 3
1995: 1 male out of 4
1996: 3 males out of 7
1997: 5 males out of 7
1998: 4 males out of 7
1999: 3 males out of 5
2000: 1 male out of 5
2001: 5 males out of 7
2002: 4 males out of 5
2003: 2 males out of 6
2004: 4 males out of 6
2005: 2 males out of 5
2006: 2 males out of 5
2007: 1 male out of 4
2008: 4 males out of 5
2009: 5 males out of 5
2010: 4 males out of 6
2011: 3 males out of 3
2012: 2 males out of 5
2013: 0 males* out of 5

In total, 61 males from 111 total, which is 55%. The P-value for gender bias towards males is around 0.17. What I wonder is whether there is any trend, whether there is extra-binomial variation and whether the ‘sausage fest” year and this year are statistically extreme.

Here are some basic simple minded models. There is a slight decreasing trend in the proportion of males but nowhere near statistically significant (T=-0.15). If you remove the 2013 year the trend is (insignfiicantly) the other way! But keep in mind that the level of overall gender bias (55% on average) over teh entire period.

Was 2013 an anomaly? The change in deviance from including a dummy for 2013 on top of the time trend is 8.84 which implies a P-value of 0.003. Looks like something changed in 2013 but remember that we selected 2013 because it was unusual. Do the extreme 2009 and 2013 results (2 from 21) indicate extra volatility?

Overall, the data are over-dispersed compared to binomial variation assuming a non-parametric time term trend, but not drastically (around 26 on 18 df).

But I wonder whether the short-list data is very useful without knowing the key missing data – how many really good books were written by men and women in a given year?

Indeed, the long list for Miles Franklin this year comprised 2 males and 8 females so that no males making it to the short list is not very unusual (P=22%). The same judges create the long-list though. What was the process that leads to the dominance of females in the long list? It seems to me plausible that the announcement of the new Stella awards as well as the Miles Franking winner being female in 2012 could easily have resulted in more good books being published by women. On the other hand, the long list in the “sausage fest” year was 7 males and three females. Was the male bias at the long list stage, or the short lsit stage or both? The chance of an all male short list (of fixed length 5) from this long-list is about 8%.

Anyway, the data for the long list is on the Wiki link.  It seems to me that you could analyse the long-list data, then analyse the selection of the short-list from the long list. Then lastly analyse the selection of the winner from the short list. But I am too busy! Suggestion. This might be a nice shortish assignment for students learning categorical data analysis.

Overall, when you look at the data, there is aparrently not that much to see. Just goes to show that people will perceive data in what ever way that it suits them. (I include myself in this generalisation!)

* Why is 0 plural? Have always wondered!

Essential research did a poll asking

How much sexism and discrimination against women do you think currently occurs in the ….?

workplace, media, politics, advertising, sport, schools. The allowed responses were none, a little, some or a lot. Few reasonable people could answer none, unless they are in an industry where there is formal or informal affirmative action. Most people would surely say a little or some. I am not even clear what the difference between a little and some is anyway.

To put it simply, you could ask people “how much racism is there..”, “how much anti-Semitism is there..”, “how much religious extremism is there…”, “how much belief in extra-terrestrial life is there….”, and the majority of people would give, in my view, the correct answer of either a little or some.

Seen in this light, the results of the sexism poll (reproduced below) are incredibly bland. Excluding the don’t knows, around 70% of people said a little or some. Tracking changes of this figure over time might conceivably be interesting, but the number itself is not.

So Crickey did not report this number. Instead, the reporter chose to combine the some and a lot categories which came in at about 50% or higher. This was somehow thought to be significantly high, even though this “category” was dominated by the “some” responders.

It gets worse though. The reporter, Cathy Alexander, continued

The poll found those who think sexism is not a factor in women’s lives may be experiencing a utopian fantasy. Less than 15% of those polled thought there was no sexism at work at all in each of our major institutions.

The stated argument is that because the category has the smallest percentage, they must be wrong. Now, I actually think they are wrong, but the reasoning is just oxymoronic.

So the article was a  total beat up of a pointless poll whose results were predictably bland, the reporting of it was biased and the discussion logically flawed.

Crikey!!

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Based on the past 60 years, you might predict a bright future for academics in 2072. However, I would not be surprised if the number of genuine academic positions returns to 1952 levels.

Researching and teaching

Academics create knowledge through largely unfunded research; they generate curriculum; they deliver lectures; they accredit learning. While teaching superficially pays for research, the argument has been that the deep knowledge derived from doing research leads to better curriculum and teaching.

So research is an essential cost input to teaching, and these two activities are bundled rather than one subsidising the other.

Unbundle them and the dynamics become unsustainable with growing student numbers that no longer mean a growing number of academics. The internet has changed everything.

Knowledge middle men

When I started lecturing in 1978, I would take one or two textbooks and write out my own lecture notes. The content would find its way into the students’ notes through a mass lecture.

These days, I design new courses by trawling the web for the latest content, topical examples and exercises. I feel more and more like a dispensable middle man between freely available content and captured students. More worrying, I strongly suspect I am not the world’s best translator of free content into course materials.

I deliver the course to the students in a big hall. Here is another insight. Try as I might to inspire and engage, I am not the world’s best lecturer either.

Surely, 60 years from now, the very best curriculum and audio visual presentations will be collected, digitised and organised. Rather than pay me to produce second best, Universities will purchase premium course materials, perhaps from specialist curriculum generating universities or from private content creators.

Or perhaps they will get the materials entirely free! The Khan Academy has a growing library of freely available lecture style videos and has financial backing from The Bill and Melinda Gates Foundation as well as Google.

Wherever the content comes from, students will consume it at home, and supplement their learning through tutorials. They will watch a macroeconomics lecture by Paul Krugman and discuss any learning blocks with post-docs in tutorial sessions and on-line fora.

They will not need to see the likes of me.

Could it really happen?

Many of my colleagues argue against these predictions. Mostly, I think they confuse what they would like to happen with what is likely to happen.

First, they argue there is no such thing as the “best” curriculum and lecture in a given subject. They may be right, but this is not critical to the argument. There need not be a single best lecture, but there will be concentration towards premium quality.

The point is that there are probably several hundred academics in Australia who lecture on, say, regression analysis, and very few of us could claim to be in the top 1% – actually only 1% of us.

The web allows 100% of the students to access the best 1%. Where is the market for duplication of mediocre course material by research academics?

Second, they argue that students need and thrive on the organic interaction that is possible in a lecture. But do they want it?

I am not sure that there is much interaction in most lectures anyway. Moreover, I think Gen Y and their kids will consider 400 students in a lecture hall an anachronism. I wonder whether they will be able to concentrate for more than five minutes in a row.

Electronic interactions through small groups will be the absolute norm. Students will like it; financial administrators will like it.

Third, some colleagues point out that there is value in allowing diversity in available content; that the process of different universities trying new things ultimately leads to evolution of better content. This may be true but it is an economic externality.

Generating untried and speculative course material is not cost effective for the generator. Students and administrators will migrate towards “the best” and proven content.

So the future I describe may lead to less curriculum evolution, I agree. But that is not to say that it won’t happen.

What about accreditation?

Accreditation is another core function of universities which they currently monopolise. High quality content is worth little unless it comes with a sanctioned university degree.

A degree is a quality guarantee of both content and learning outcome. It is dependent upon a university’s reputation which, in turn, is largely built on research reputation. So universities will always have reason to be involved in research, even unfunded research if it is cutting edge and newsworthy.

I cannot see the private sector usurping this role.

But will Australian universities really need 43,000 researchers for this? Clearly not. They might opt for a small research core in each department, to establish each program’s bona-fides.

The research core may only comprise a couple of elite professors, over-seeing doctoral programs and externally funded research positions and vouching for the quality and currency of the courses delivered.

The prism of history

Many may argue that it is daft to predict what will happen in 60 years. But I find it liberating to see the here-and-now through the prism of historical facts and forces, and to realise that the status quo need not continue.

My academic generation has lived through an unprecedented boom in tertiary studies. Living within history can blind us to a wider historical perspective which reveals the boom as a short-term unsustainable anomaly.

Student numbers exploded and the bundling of academic activities meant that academic numbers also exploded. Decoupled teaching and research could mean academic numbers easily decline.

It does not give me great pleasure to make these predictions, nor though do I think it is necessarily a bad thing. More people might get better educated in the future, without the need for people like me, well-rounded academics who are good at both teaching and research. People like me will find something else useful to do.

In world where teaching and research are not so tightly linked, it is not good enough to be a very good researcher and a very good teacher. Only the outstanding will survive.

I have always found ABS phone staff pretty helpful and there is plenty of free stuff on their site that is reasonably easy to search once you get the hang of it. But, as someone who just paid the ABS $450 for 5 years of data on deaths broken down by exact age and gender, I am not presently disposed to feel kindly towards them. The births are totally free but not the deaths! The good news is gratis, but you have to pay for the bad news!? Moreover, it seems to me that the external spill-overs from open information are great enough that all the data should be provided free. That is not Paul’s main gripe however.

Paul wants to turn the ABS over to private providers. Here is what he says:

Reduce the budget of the Australian Bureau of Statistics by about 90%, reducing it to merely being in charge of running the Census, and instead commission private providers of statistics to generate surveys of Australian businesses and the population. This would involve a quick reduction of around 300 million a year in expenses and would immediately improve the data available for economic decision making.

Why does he think private providers would improve data availability for economic decision making?

The rational for cutting off the ABS is that it is completely secretive about the data it gathers: only ABS officials are trusted with using the full data by the ABS, not other government departments or Australian researchers. We are thus in the fairly ridiculous situation that those who devise the Australian budget in the Treasury do not have access to all the data gathered on the finances of individual industries. The ABS hides behind laws promising confidentiality to prevent anyone else from using its data, but similar laws on secrecy exist in other countries that have not been interpreted as ‘only people in our statistics organisation can be trusted’. Quite simply, the ABS has turned into a secretive rent-seeking organisation that draws huge subsidies but does not feel obliged to share its products with its paymasters. Why then should the Australian public pay for data that is not used to improve our knowledge of Australia? It might as well not exist and if it didn’t exist, the community would be free to buy data from other sources that are more consumer-friendly.

I have an anecdote about my own experience with the ABS and an opinion on why I think privatization is not the answer. About three years ago, I was giving a talk at the ABS in Brisbane. It was actually a talk about statisticians publicly engaging more. Part of the talk involved linking to this modest blog.

I arrive 45 minutes before the talk and managed to get through security. I then passed my USB containing the powerpoint slides to the fellow who had invited me. There was a look of horror followed by embarrassment. “You can’t use that in here” he said gravely. “The IT guys won’t allow it.”

All the PC’s in the building had software installed to prevented the use of USB’s. Apparently, I was supposed to have sent my slides to the IT department who would scan it and upload it to the presentation PC themselves. Their gravest angst was spyware entering their database. This single fear of data security seemed to have supplanted their main mission which is data collection and distribution.

Getting the files to the IT guys was not at all easy either. It was not a matter of walking down to the dungeon. But I will spare your the details.

So the talk did go ahead after a stressful beginning. And you can imagine what happened when I tried to link to Fishing in the Bay during the talk. The PC nearly crashed!

So Paul is absolutely right about the paranoid, obsessive privacy culture of the ABS. It is virtually impossible to get unit record data. The issue though is where that culture comes from and whether privatization would be the solution.

It is not just the ABS that is paranoid about privacy. Try ringing Telstra or Yarra Valley Water to check your bill. If the account happens to be in your partner’s name, you are likely to hit a wall. Imagine what someone could do with the personal information of my water consumption! The really annoying thing about Telstra’s cynical sham of a privacy policy is that they sold all our records to India years ago, which is why marketers can ring you up at dinner time and know your first name. Telstra have not kept up with the hackers, so they  make you think they are a data fortress by refusing to tell your details even to you!

Don’t just blame the companies though. Australian privacy legislation is pretty strict. And I think it has public support. Remember the crazy panic over the Australia Card 25 years ago? There is an unarticulated public fear of information security and privacy. And I think it has recently increased because of the quite real risk of identity theft and credit card fraud. Though people seem to forget that credit card fraud is mainly a problem for the banks, as the customer is not liable for the losses.

So, what about privatizing the ABS? There would be immediate howls of protest about privacy. The government could only outsource this function if they responded by imposing restrictions on data security that would possibly be even more extreme than the Brisbane branch of the ABS. We would end up in a worse situation than we are now, I fear.

In subsequent comments, it appears that Paul has something different in mind - that Government departments and research institutes take responsibility for dissemination, rather than the ABS. He contrasts his experience with obtaining data from the The Longitudinal Study of Australian Children which is not controlled by the ABS, though they collect the data. Virtually all data is made available to someone from a reputable institution who is prepared to sign a confidentiality agreement.

Which seems to imply that

* there is nothing about government provision per se which leads to poor service and obsession with secrecy

* there is nothing in privacy legislation that prevents the ABS from giving out unit record data.

Perhaps he is right about an entrenched culture at the ABS being specific to the ABS. Ho9w about htis for a simpler solution: the responsible minister (the assistant Treasurer) rewrites the ABS privacy policy using the policy of LSAC as a template?

There are a couple of nice discussion of the issues (including comments) by Professor Paul Fritjers  (here and here) which you might like to look at. I thought it might be worth while putting my thoughts down here, in a more complete manner than is possible within a blog comment.

There are three core ideas with the Melbourne model, which often get bundled into one. The first is to force students into a general degree, for the purpose of broadening their education and making them better citizens and more rounded employees. The second is to increase the number of students who extend their degree to 5 years and, let’s be frank, to charge very high fees for the last two years. The third, which is related to but distinct from the first, is to prevent high school students locking in a place in elite courses that lead to closed shop elite careers.

The broadening idea is good in principle. High school students are unlikely to have full information on how well a vocation may suit them and have limited exposure to fields outside their VCE study. So it makes sense to restrict their ability to specialize too early. However, it can and has been argued (for instance by Fritjers) that the idea has been taken too far. Some of the breadth subjects are less rigorous and demanding than would be dlivered to a fully engaged specialist student  – necessarily so, if you want arts students to take a science subject. An alternative and less ambitious model would have been to have retained the rigour of existing courses, while still forcing students to do say 25% of their studies in other faculties. So for instance, Math students would do econometrics in the economics department, psychology students would do statistics in the math department, architecture students would do engineering etc. This would lessen the incentive to dilute the content of courses for a non-specialist audience. While it would admittedly mean less broadening, maximal broadening is not necessarily optimal. A revised system would allow students to move 45 degrees from the subjects that they already have an aptitude for, and are interest in – rather than 180 degrees as is the result of the current Melbourne model.

The second reason for the model is economic. Under the current model, a student finishes with a general arts degree (but with some forced low level broadening subjects) and is not very employable. Their generalist degree is likely to be worth less in the job market than the previous 3-year vocational degrees. So students have a strong reason to move to the two year vocational masters subjects that follow.  The charge for these courses can be very high, and they are not limited in number or fee structures the same way that under-graduate places are.  As one example, the Melbourne Law School charges around k$100 for the law degree (called the JD). Roughly half the students (all local) have to pay this full fee. Students need not pay up front, but will carry a large debt into their first job.

The third reason for the Melbourne model is to prevent high school students choosing their vocation at the age of 17, especially to prevent them locking in a place in an elite program like Law or medicine. They do allow students with extremely high ENTER scores to lock in a place, subject to reasonable performance standards in their under-graduate degree, but they still have to do the general under-graduate degree. There are educational arguments for this which have already been explained above. There is an even stronger ethical and economic argument. 

Under the old model, most students in elite degrees came from incredibly advantaged educational backgrounds. This does huge damage to our society and also to the economy. It is rightly perceived as unequal; it is incredibly expensive for private school parents who hand over about k$100 for their child to essentially jump the queue; it is uneconomic because it is not merit based. Under the Melbourne model, students compete on the level playing field of the university, to gain entry to medicine/law. I cannot understand why the government does not enforce such a system on every G8 university. It should be illegal to allocate governmetn supported law/medicine places to kids who got their good results because of an elite education. The Melbourne model can only lead to fairer and more merit based outcomes.

It has been argued that, under the old Melbourne model and competing systems, there were other non-VCE pathways into medicine and law. That may be true, but the fact that the back door was left ajar does not change the fact that the bouncers on the front door were mainly admitting people in private school uniforms.

** I did in fact apply for a job at Monash in 2011. I was not successful. According to my sources on the ground there, the reason was the Australian article and the rejection of my application came from the highest level.

The October issue of Annals of Statistics had a paper by Weishen Wang about smallest confidence limits. The main Theorem 4 gives a formula for a largest possible lower limit for a scalar parameter in an arbitrary discrete distribution. Unfortunately, this construction was first given by Robert Buehler (JASA,1957). The proof of its optimality was given by Jobe and David (JASA,1992) under a non-trivial restriction. The proof was generalised to remove this restriction by Lloyd & Kabaila (ANZJS,2003).

The paper by Wang includes reference to Bol’shev (1965). That paper refers to Buehler (1957). Indeed it is mainly about Buehler (1957).

The paper by Wang also contained an additional Proposition 2 which, in non-technical terms, says that a more informative statistic can never generate a worse Buehler lower limit than a less-informative statistic. This result was proven in Kabaila & Lloyd (ANZJS,2004) where we also gave conditions under which the lower limit will be strictly better rather than only no worse.

I sent the details of this sorry saga to the editor of Annals, Peter Buhlmann, who responded within two days that that the record could be set straight with a two page paper authored by Paul Kabaila and myself. The publication process was hurried it should appear in the December issue. Well done Peter Buhlmann and Annals of Statistics! My faith is renewed. I am not sure all editors would be prepared to do this.

In fact, I know from personal experience that they don’t.

About 7 years ago Biometrika published a paper, Using logistic regression procedures for estimating receiver operating characteristic curves, by Jing Qin and Biao Zhang. The paper was virtually identical to a paper I had published a year earlier. However, I had submitted this same paper to Biometrika two years earlier and had it rejected.  You join the dots yourself.

The editor of the time, Mike Titterington, told me that Biometrika do not publish letters. Instead, he got the authors themselves to publish an erratum. This was totally inadequate in my view and does not correct the record. If you don’t believe me, try Googling “Using logistic regression procedures for estimating receiver operating characteristic curves” and see what you get. You sure don’t get the erratum or anything with my name in it.

It is hard to know what to do when you have your work plagiarised. If the journal just hunkers down then what avenues are left to you? Do you get up at a conference and denounce the offender and look like a looney? Or do you just blog about it…..

Let’s get to the nuts and bolts then. It is all about grant success rates and some statistical patterns that appear when this measure is broken down by various factors.

Throughout the discussion below, an early career researcher (ECR) is someone less than 5 years post Ph.D. You might not like this definition, but it is the current one (the ARC are actually considering loosening it).

Issue 1: Experience

Success rates are lower for ECR only proposals - around 18.4% for ECR only proposals and around 25.5% for others, in 2009. Remember that the overall success rate is about 23%. This difference has persisted for many years, see HERE.  I do not think that any academic in Australia would be surprised that ECRs have a lower success rate. Is it unfair? Is it a problem that needs fixing?

First, success rates are not the right measure. They do not tell you how much money is going to ECRs. This is pertinent because many of the successful grants of senior researchers will be to support ECR post-docs! The glory may go to the CI, but the money is going to the ECR.

Second, accepting success rate as the key performance measure, imagine an ARC grant that is written by an ECR with no other experienced team members. Such proposals have a lower succss rate. The ARC seem to think that the success rate should be the same as that of a senior researcher.

In what parallel universe do ECR’s emerge from their PhD with the same skill base, research links, and maturity as a 45 year old Professor? In reality, many ECR proposals will be flawed. Moreover, lack of experience makes successful execution of the research program more risky than for an experienced researcher. So even with two equally good proposals, it would be perfectly sensible to fund the more experienced team.

A non-academic might reasonable ask “How do young researchers ever get started then?” We all know the answer. Mentoring. It was made clear to me, early in my career, that the best way to get an ARC grant was to team up with a more senior researcher. This is a good thing. The role of mentor and ECR is a mutually beneficial one, and has been a central pillar of academic culture for generations. Incentivising ECR-only projects is a direct attack on this healthy tradition.

Issue 2: Gender

Success rates have been consistently lower for females (by a modest amount). What could explain this? Well, it turns out that females are over-represented in ECRs and under-represented at higher experience levels. Could the gender gap then just be driven by their having lower experience?

The answer is no. The gender gap is real. If you restrict attention to ECR only proposals then the gap is 16.5% for females compared to 19.9% for males averaged over 2001-2009, see HERE for the graph.

Below is an even more revealing graph. It shows the success rates for males and females broken into 7 groups of experience (the average of the team). As you can see, the gender gap is consistent across 0-15 years - it is not just ECRs. The graph also shows the earlier stated fact that females are over-represented amongst the less experienced applicants - not that this explains the differing success rates because we have controlled for experience in this graph.

But it set the ARC onto quite the wrong track. You see, they got the idea that they could fix the gender problem by discriminating in favour of ECRs. 

The ARC proposal

The ARC consultation document says that

The ARC has hosted a number of discussions about ECR and gender to understand their relationship and thereby propose a means to address disadvantage in success rates….By addressing this issue … the aim is to remove gender difference across ARC schemes as a totality.

Laudible intent. Pity about the execution. What are they planning to do?

The proposal is to have a separate scheme* for ECRs (perhaps around 200 projects) and a new scheme for mid-to-late career researchers(LCR). So we will have three experience groups in mainly different pools - ECRs, LCRs and the rest.

*ECRs and LCRs can still apply in the general pool as well.

The problems

1. How will they control the total allocation to ECRs?

Why are they choosing 200 ECR projects? (This figure was mentioned in the ARC road-show and is not in the document) A fixed number of 200 awarded grants does not guarantee any particular success rate. So perhaps they will target equal success rates for the three groups, otherwise why bother? This raises the really important question:

What will they do if they get 2500 ECR proposals? Fund 500 of them? Which leaves 500 for the rest of the sector? What if only 200 apply?!

2. Gender bias is not actually addressed. 

Have a look at the Figure again, reproduced below. If the ARC carried their idea to its logical conclusion they could create separate pools for each of the 7 experience categories and impose an equal success rate on each. This would get rid of the “experience bias” completely but the gender bias remains completely unaddressed. Females ECRs still do worse than Male ECRs, even if they might do better than Male LCRs.

They could even impose a higher success rate on ECR’s and a decreasing success rate with more experience. This is of course perverse but it could be tuned in such a way that the overall success rates for females could be made to equal that of males. But the bias within experience groups would remain!!! Amongst ECR’s the 4% success rate gap would not change.

This is dangerously ignorant and thoughtless policy. Positive discrimination in favour of ECRs does not remove gender discrimination. It actually tries to hide it.

As a tax payer I expect the ARC to address the real issue. The real issue is that they have identified gender differences in success rates for all programs, but have not addressed the reason at all.

Looking at gender bias

It is possible that the quality of the applications for females was poorer and that this explains the lower success rate. This is not as fanciful as it may sound. Any kind of affirmative action at earlier career levels would result in the pool of female graduates being less capable than male graduates. And low success rates would not then imply bias. On the other hand, it might be that female applications are even better than male applications and the aggregate figures under-estimate the true level of gender bias. We just do not know yet. And we should know.

I believe that the ARC are ethically required to identify the extent of gender bias in their processes. A company with a poor safety record cannot ignore it. They are required to identify the sources of excess risk and eliminate them. In the same way, the ARC must properly assess the level and nature of gender bias, so as to remove it.

This is not impossible to do. For instance, one might take all 2009 applications, strip them of gender identifying information, and then rate the quality of the proposal, and the experience of the applicants. One can then measure the extent of different success rates for genders after accounting for the quality of the proposal and researchers.

The bottom line

So the net effect of the proposed changes will be to

• divert funds from higher quality projects to lower quality and riskier projects of ECRs
• incentivize fresh PhD’s to apply for their own grants rather than apply for post-docs under the supervision of a mentor
• totally ignore the issue of gender bias, in terms of checking whether it is really there, identifying the source or trying to correct it.

What can be done about this?

Perhaps not much. Margaret Shiels writes in her foreward

We are confident in the broad directions of change indicated in this paper, but would especially welcome commentary about details and implementation.

Translation. Save you ink. She has made up her mind. Nevertheless, being the idealist that I am, I will write my (suitably sanitised) comments down and send them to Mr Jonathan Rogers at the address DiscoveryConsultation@arc.gov.au. I really encourage all academics to do the same- whether or not you agree with my analysis. The deadline for submissions is December 1!

Given what Australia’s needs are going into the future…and the fact that the fertility rate is so low, we will just disappear if we don’t have a healthy immigration level.

And the fact that both sides were blathering during the election campaign and trying to hoodwink the Australian people is a disgrace.

The suggestion that the Australian population is about to disappear is fanciful. It is about as wrong as anything can be in politics – it is arithmetically wrong. This is not a matter of opinion. I have run a few calculations and projections to illustrate the point. Other people might get slightly different answers depending on various assumptions, such as the exact age distribution of mothers and how mortality will progress in the future.

TFR is the total fertility rate - meaning the number of children on average a women will have (supposing she does not die before having them). A value slight above 2 (in our case about 2.07) corresponds to replacement i.e. zero population growth. The history of the TFR in Australia is HERE. The TFR in Australia right now is about 1.97. The lowest it ever reached was 1.73 in 2001. In Hong Kong the TFR is about 0.9, see the ladder HERE.

The projections below all assume zero net overseas migration (i.e. about 220,000 migrants to balance the 220,000 permanent departures each year), starting from a population of about 22.1 million at the beginning of 2010.

It doesn’t really look like we are going to “disappear” does it, even under the worst case 1.73 scenario. Under this scenario the population will still be higher than it is now in 2050! I am afraid that it is journalists who are hoodwinking the Australian people on this issue, not the politicians.

Here is another scenario to consider. Suppose that drop the baby bonus and that the TFR falls back to about 1.80 in response. Suppose that we also reduced net overseas migration to 100,000 per year (instead of 200,000 which is now talked about as a compromise figure). Under these two policies - which represent the extreme of what would be politically possible in terms of reducing population pressure -  does the population stagnate? No. It increases to 28.7 million in 2050 and continues to grow into the future.

There are reasons for running an immigration policy, but saving us from a seriously declining total population is not one of them. Neither is it any sort of solution to the ageing population problem, but that is for another post.

You are given a density of the form kx(3-x) on 0<x<3. The task is to Show that k=2/9. The student wrote down the integral and equated it to one. Then he wrote down the indefinite integral and proceeded correctly to the answer. Result: 1 mark from a possible 2. The reason? He did not expand kx(3-x) into 3kx-kx². He is allowed to assume that the indefinite integral of x^k is (k+1)^-1x^k+1 but he is not allowed to assume basic expansion formulas.

You might think this is because of the word “show” in the question – that a high standard of pedantry is required. Not so. Later in the exam, we are asked to find the mean of the same distribution. We are again integrating a polynomial. A mark is again subtracted for not multiplying out the expression in the integrand. You can imagine that a student with a modicum of intelligence would, on receiving his marked script, be pretty angry and demotiviated with the subject of math methods.

But it gets way, way worse. Consider the discrete distribution bellow.

x                0      1      2      4      8      16
Pr(X=x)      0.1  0.1  0.05   0.2   0.4   0.15

You are asked to find the median. The student gives the answer 8. The definition of the median for a discrete distribution is an annoying exercise in pedantry itself, but the answer of 8 here is correct according to the provided definition. Result: 1 mark from a possible 2.  The reason? The question asked that answers should be given to two decimal places. The required answer was 8.00. I kid you not. For those who think students should learn to follow instructions, why not ask the student to write all answers in red, or all even digits in green? We want to test mathematical understanding, not the ability to mindlessly follow instructions. They teach that in the cadet corp.

No wonder some students think that mathematics is a meaningless, mindlesss game that involves the slavish following of algebraic rules for their own sake.

* A SAT is a test adminstered within a school to determine within school rankings. These are combined with inter-school differences from the main exam.

They listed a time series of the number of days during that year where capacity was less than 50%. Not surprisingly, for many wet years there we no days under 50%. So there are lots of zeros. It’s almost as dumb as summarising my growth curve by listing the number of days during each year of my life I was over 5 feet tall.  Bearing in mind how highly correlated the underlying measurement is, why would you ever try to summarise it by looking at the number of consecutive values that are in a range?  If you were going to move away from the mean, the yearly high and low would be much more informative.

But it gets worse. They indicated on the table when new dams were opened, including the humungous Thompson dam.  Now when a dam opens it is surely empty. The state Premier cuts the ribbon when the wall and sluice gates are complete. And then the water flows in over a number of years. So with a huge damn like the Thomspon which accounts for most of Melbourne’s capacity, you would drop below 50% on the day it opens and for a few years after that while it fills. But the table doesn’t show this. In fact, the opening of the Thompson dams does not seem to affect their daft statistic “number of days under 50%” much at all. So they maanged to add a confusing bit of extra information to a meaningless list of numbers. 

*Unfortunately, the graphic I am describing is not on the link. It only appeared in hard copy.