Posts from June 2018 (16)

Last week, Microsoft (who you’ve probably heard of) bought GitHub (who you may well not have heard of) with $7.5 billion in Microsoft stock.  Github is a site that cross-bred version-control software (‘track changes’ for programmers) with social media, providing a place to share and promote code.

Stuff and the Herald quoted the same number

More than 28 million developers around the world use GitHub, with Microsoft ranking as the most active organisation on GitHub.

You might wonder what proportion of developers use GitHub. If you search a bit on Google, you’ll find that the total number of developers is estimated at about 21 million, so roughly 130% of them use GitHub.

Obviously there’s something wrong there.  The problem is how to define ‘developers’.

In the US, the Bureau of Labor Statistics reports how many people do each job. They say, currently,  that there are 1,617,400 “Software Developers and Programmers”.  The figure of 28 million worldwide is actually based on a subset of those, the 1.2 million “Software Developers, Applications” and “Software Developers, Systems”.  This sort of official classification has to be narrow, because the goal is for  every job to end up in exactly one category.

Lots of people in the US who are developers in the GitHub sense aren’t developers in the Bureau of Labor Statistics sense. Some of them write software only in their spare time. Others write software as part of their jobs, but their jobs are classified somewhere else in the BLS system. The same is true in New Zealand. Stats NZ reports 31,860 jobs in ANZSIC06 category 7000 “Computer Systems Design and Related Services”, which is a bit broader than the US category.  Even though I’m a developer in the GitHub sense, I’m not one of them. I’m in 8102, “Higher Education”.

Other people who probably in the 21 million count include statisticians, data scientists, computational biologists, ornithologists, journalists, linguists, and many more.

Official statistics are usually pretty accurate, but they are only accurate for what they are trying to measure, which might not be what you are looking for.

The new QS university rankings are out, and there’s a story in the Herald.  It starts

Staff cuts despite growing student numbers have dragged most New Zealand universities down in the latest world rankings.

The biggest six of the country’s eight universities have all tumbled in the London-based QS rankings, which are regarded as the most important for attracting international students.

“Tumbled” is an exaggeration — for example, the University of Auckland has ‘tumbled’ from 82nd to 85th in the rankings. But the message that it’s staff numbers does seem to be backed up with a quote from QS

“The increase in enrolments – and the decrease in faculty numbers – reported by the country’s universities sees all eight receive a lower score for faculty/student ratio,”

QS don’t make it easy to find older numbers, but an archive of their webpage in March last year said there were 29,930 students and 2025 academic staff, and a ranking of 81. The current figures are  29,641  students (ie, fewer) and 2,047 academic staff (ie, more), for an improvement in staff:student ratio from 14.8 to 14.5. 

That’s over a two year period, but last year, the story at Stuff said

New Zealand universities performed well in research outputs – Waikato ranked 133rd, Otago 174th and Canterbury 178th – but showed “uniformly deteriorating” faculty to student ratios. The exception was Lincoln University, which featured among the top 200 universities globally in that measure.

So, cumulatively over this two year period the staff:student ratio at UoA (as measured by QS) improved, but the reporting said it worsened in both years.

My guess as to what’s going on is that these rankings are rankings. What they mean by “lower score for faculty/student ratio” isn’t that the ratio got worse here, but that it got better here by less than it did at some competing universities.

The other strange thing in the Herald story is this:

The worsening staff/student ratio in NZ universities was entirely due to cuts of 203 academics at Massey and 74 at Lincoln.

It could be true that these are the only NZ universities with a worsening staff/student ratio — the other universities could be seeing the same sort of change that UoA did — but if it is, the apparent contradiction with the lead should have been noticed.

Team Ratings for Round 17

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 99 matches played, 69 of which were correctly predicted, a success rate of 69.7%.
Here are the predictions for last week’s games.

Predictions for Round 17

Here are the predictions for Round 17. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

• • According to the Daily Mail “Brisk ten-minute walk, around 1,000 steps, can increase mortality by 15 per cent.”  They mean decrease.
  • Wikipedia thinks Amanda Cox, the data visualisation expert from the New York Times, isn’t “notable”. They are wrong and they should feel bad. But also, published evidence that she is notable would be useful.
  • The FDA has issued guidance on how to include pregnant women in clinical trials.
  • A monthly collection of the best data visualisation from around the web
  • Black cats are less popular

Debuting new survival analysis example in class today (from Austin TX’s animal control data available online). pic.twitter.com/9qDmFMKvbM

— Jeremy Freese (@jeremyfreese) May 30, 2018

The report from Dr Anne Bardsley and Dr Felicia Low for the Office of the Chief Science Adviser makes clear that testing of houses for methamphetamine has been a complete failure for the sort of evidence-based risk-benefit analysis the NZ governments are claiming to care about.

It’s not just that Housing NZ used an Australian guideline for how clean a former meth lab should be after you’ve cleaned it as a screening threshold. Or that there’s an explicit 300-fold safety factor underlying that threshold even for the most susceptible people (toddlers crawling around and putting things in their mouths). Or that they not only evicted people but sometimes took away their personal belongings as too unclean to touch.  

In a situation where Housing NZ now claims they knew their standard was not very well founded, they didn’t try to do any better.  Faced with a huge testing and remediation bill, whose necessity was — at the most generous evaluation — unclear, they didn’t spend the relatively small amounts that would be needed to find out whether they were wasting public money. They didn’t even ask for help from, say,  the Chief Science Adviser, or the Royal Society Te Apārangi.

More importantly, though, they ignored the harm done by evicting vulnerable people.  The fundamental assumption of any cost-benefit or risk-benefit analysis is that you’ve got the costs and risks and benefits right, or at least that you’ve made an honest effort to get them right and been explicit about your uncertainty.  There are difficult second-order questions of whose costs and benefits you include, and how you account for hard-to-quantify factors like cultural preferences and reputational costs. But if you don’t even put in some of the major costs of a policy, you’re admitting up front that you don’t care about the right answer.

There currently seems pretty broad consensus among people who don’t work there that Housing NZ needs to be remediated. But the ability of the meth screening policies to last that long will — and should — raise doubts about evidence-based decision-making across the NZ public sector. Which is a pity.

Team Ratings for Round 14

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 100 matches played, 59 of which were correctly predicted, a success rate of 59%.
Here are the predictions for last week’s games.

Predictions for Round 14

Here are the predictions for Round 14. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.