SciBlogs

Archive October 2009

The University co-author network Shaun Hendy Oct 27

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Uni coauthor networkIn an earlier post I looked at the 2008 CRI co-author network. Now let’s turn to the University network. Using the Thomp­son Reuters Web of Sci­ence again, I found 5116 publications in 2008 with authors from New Zealand universities. In total 13930 authors contributed to these papers. The network is shown on the right.

Again, a remarkably large fraction of authors belong to the giant component. In the 2008 CRI co-author network, 2325 of the of the 4496 authors belonged to the largest connected component. Here, 9771 of the 13930 authors belong to the largest component – that’s a remarkable 70%.

We can make some other comparisons between the CRI  and the university networks. In the university network, on average each author has 8.4 collaborators; in the CRI network, each author has 5.1 collaborators. Apparently, university authors are more collaborative.

Degree distribution However, just comparing the average numbers of co-authors is misleading. I’ve graphed the distribution of co-author numbers for the universities and the CRIs on the left i.e. the proportion of authors with certain numbers of co-authors. From the graph it’s apparent that the difference between the university and CRI networks lie in the tails of the distributions. There are a number of university authors that participate in very large collaborations. For instance, there are a dozen or so authors in the network whose only published work in 2008 was one with 343 co-authors. Big science!

It is probably not surprising that university researchers are more likely than those in a CRI to participate in very large overseas collaborations. This skews the average number of co-authors for university researchers relative to CRI researchers, making the mean number of co-authors larger.

New Zealand’s RS&T priorities Shaun Hendy Oct 23

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MoRST have just released a discussion document which introduces a new structure for RS&T investment, aimed at allowing for greater strategic priority setting. Submissions are due by November 18th. Get it here.

What do you think of the feedback document and where would you put our rather modest science dollar?

World bibliometric output

While you are pondering this, here is where the rest of the world puts its intellectual grunt: the pie chart below shows the proportion of papers published by subject area over the last ten years. The physical and medical sciences account for two thirds of the world’s publications.

In contrast, here is where New Zealand puts its efforts:

NZ bibliometric output

Setting priorities is clearly nothing new for New Zealand – as the charts show, our science system strongly emphasises agricultural and environmental sciences at the expense of physical sciences. Have we got the balance right?

The CRI co-author network Shaun Hendy Oct 19

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CRI coauthor network To what extent do scientists at Crown Research Institutes (CRIs) collaborate? Using the Thompson Reuters Web of Science, I have constructed the CRI co-author network for 2008. As best I can determine, the Web of Science database contains 1271 papers from 2008 with CRI authors. In total, 4496 authors contributed to this set of papers – not all these authors are from CRIs of course, but they have all co-authored a paper with someone from a CRI. The network is shown on the left: the green dots are authors, with blue links between pairs of authors indicating co-authorship on at least one paper.

What surprises me is the extent of the largest  set of authors that can be connected to each other by co-authorship. This largest connected component can be seen sitting in the centre of the 2008 network diagram, containing 2325 of the of the 4496 authors (52%). It contains authors from many of the CRIs (including me and a number of my colleagues at IRL) and from a number of Universities, both in New Zealand (including many from the the MacDiarmid Institute) and overseas. The next largest connected component contains only 31 authors.

Connected component If you look at the size of the largest connected component in the CRI co-author networks each year, 2008 is the largest. Just after the CRIs were established, in 1994,  the largest component contained only 195 authors, occupying only 12% of the network. One reason for the growth of the largest component is that since 1994, the average number of co-authors each author has in a given year has risen from two to five. In other words, CRI scientists are collaborating more extensively in 2008 than they were in 1994.

The New Zealand skills deficit Shaun Hendy Oct 16

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NZ PhD In 2006, 640 students  graduated with PhDs at New Zealand universities, compared to only 400 in 1998.

The graph on the right shows how this growth in student numbers has been shared among the disciplines. While the number of graduates in science and applied science has grown modestly, most of the growth has come from outside of the sciences. For instance, in Business and Commerce, the number of PhD graduates has nearly tripled over this period.

Science PhDs If we break down the sciences and applied sciences further, we can see that the number of biological and medical science graduates has grown strongly since 1998. This may be due to the considerable investment in biotechnology research and development made by the New Economy Research Fund (NERF) since 1999. However, the decline in physical sciences PhD graduates since 1998 is alarming. (Although I do know that in the MacDiarmid Institute, our numbers are growing:  we currently have more than 140 PhD students enrolled.) The relatively static numbers in engineering and the agricultural sciences should also be a concern.

Nokia human capital demandHow important are graduates to an economy? In an earlier post, I discussed the network of inventors that can be identified through the patent portfolio of Finnish mobile phone giant Nokia. The plot on the right shows the number of new inventors that appeared in Nokia’s patent record each year. In 2002, more than 300 new inventors appear in Nokia’s patent record. For comparison I’ve included the number of engineering PhDs graduating per year from Finnish universities. These started growing in the early 90s in advance of the strong demand by Nokia. It seems that these graduates must have played a key role in Nokia’s success. In 2006, the Finns graduated more than 300 PhDs in engineering compared to New Zealand’s 51.

Although the increasing numbers of New Zealand PhD graduates in the biological sciences is encouraging, a scan of the 2008 TIN100 report shows that few of the top 100 technology companies in New Zealand are based on biotechnology. In fact New Zealand’s manufacturing industry today is based heavily on engineering and ICT. Is this industry being held back by New Zealand’s skills deficit in physical sciences and engineering, or does this simply reflect a lack of appetite for research and development in our manufacturing sector?

How many Aucklanders does it take to file a patent? Shaun Hendy Oct 12

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New Zealand’s patent output is horrible by OECD standards. On a per person basis, the OECD produces four times as many triadic patents (inventions that are patented in the big three economies: the US, Japan and Europe) as New Zealand. Finland produces nearly ten times as many. Our poor performance in patenting is one of the reasons we are near the bottom of our class in the World Economic Forum’s innovation rankings.

So what’s the problem? One explanation lies in economic geography, the study of how economics depends on location. In fact, economic geography suggests that the comparisons I’ve just made are not very meaningful. As economist Paul Krugman says “… countries are not points and some pairs of countries are much closer than others … London and Paris are much closer to each other than New York and Chicago, or for that matter that Canada is essentially closer to the United States than it is to itself.” To an economic geographer, the natural unit of economics is the city, not the country.

Many economic measures, including productivity, savings rates, and even the number of petrol stations per person, appear to be correlated with city size. Dave Maré, a Wellington economist, has found that in New Zealand, the productivity of a company is correlated with the regional density of companies. In the US, the per capita patenting rate of a region also seems to be related to its population, with larger population centres having more patents per person.

NZ Patents by Region with mean How are New Zealand’s patents distributed? Using an OECD patent database (previously discussed here), I have plotted New Zealand’s PCT patents from 1978-2008 for each region against its population in 2008. The Auckland region has the most patents, the most people and the most patents per person. The dashed red line is a fit that assumes the number of patents per capita is uniform across the country. From the plot you can see that on average, New Zealanders produced one patent per 1000 people over this period, while Aucklanders produced one for every 750 people.

Are Aucklanders just smarter, or is economic geography at work here too? We’ll explore this in later posts.

Marsden 2009: A substantial increase in funding but success rate remains low Shaun Hendy Oct 08

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At $66m, this year’s allocation of Marsden funding is the largest since the fund was created. However the success rate remains low – how much new science does this funding increase actually buy?

Total marsden fundingThe Marsden fund supports much of New Zealand’s blue skies research, so it is a vital part of our innovation system. In this year’s budget the Government increased the Marsden fund by $9m. The relative magnitude of this increase in funding is shown in the figure on the left, where the funding allocated each year since 1998 is shown (CPI-adjusted to 2009 dollars). Between 1998 and 2007, growth in the fund shadowed inflation, but in the last few years it has grown substantially. In real terms, this year’s allocation is more than 50% larger than that in 1998, resulting in 109 new applications being funded in 2009, compared to 100 in 1998.

Fast start proportionAnother pleasing development is the level of funding for emerging researchers. This ‘fast-start’ category, created in 2001, is open to those who obtained their PhDs within the previous 7 years. A fast-start grant allows a new researcher to develop an independent research programme at the forefront of their discipline. Successful proposals build confidence, and attract good PhD students and collaborators. Since the scheme was created, the proportion of money allocated to ‘fast-start’ grants has nearly doubled to 13%.

Marsden success rateHowever, the overall success rate of the fund remains low (right) and selecting the successful proposals is a very difficult job for the Marsden panels. Historically, only 80-90 out of 800 applications have been selected for funding each year – an 11% success rate. As is shown on the right, this year’s 12% success rate is quite close to the historical rate. Australian scientists have been complaining this year about a 20% success rate, although the ARC only funds the marginal costs of research (e.g. the salaries of research assistants, but not the salaries of the principal investigators). Unlike its Aussie counterpart, the Marsden fund bears the costs of the salaries and institutional overheads associated with the principal investigators (known as full-cost recovery).

Funding per proposal The figure on the right shows the average funding per proposal in real terms, now just under $600k (roughly $200k per annum). This steady growth in the size of grants explains why, despite the large increase in total funding, the overall success rate remains low. It has occurred despite the introduction of fast-start grants in 2001, which are roughly half the size of the average full grant. While the Government has funded more proposals this year, much of the increase in funding over the last two years has gone into increased proposal size.

The data show that this year has been a very good year for the Marsden fund. However, if trends continue, the fund will need regular increases of this size to keep the success rate at 12%. 

(Disclosure: I am a principal investigator on two current Marsden grants, but did not submit a proposal this year.)

New Zealand’s recent bibliometric productivity Shaun Hendy Oct 02

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As discussed in an earlier post, there are a number of sources for bibliometric data. Scimago Journal and Country Rank is a freely accessible bibliometric analysis site developed by a Spanish research group using Elsevier’s Scopus bibliometric database, which holds country and journal summary information. For example, there is a New Zealand summary statistic page that has data on publications each year since 1996.

NZ total pubsThe first thing that leaps out at you on the NZ summary page is the large increase in publications per year evident from 2003, as I have replotted on the right. This increase is substantial: NZ has gone from publishing 5000 scientific articles per year to more than 8000.

Actually, 2003 was the year in which the first performance-based research fund (pbrf) assessment round was held. This was part of a change in the way university funding was allocated, from a system where funding levels were set largely by full-time student numbers, to a system where levels are partially determined by research performance. The performance measures used were based on the quantity and quality of research performed by individual researchers, with assessments taking place in 2003 and 2006.

NZ-FTE-ProductivityIt is tempting to attribute the growth in annual publication to the pbrf exercise, with researchers responding to this assessment by increasing their output. However I mentioned in an earlier post that Statistics NZ provides an estimate of the number of full-time equivalent (FTE) researchers in the university, government and business sectors every two years. This allows us to calculate the number of papers per FTE researcher, which is a measure of researcher productivity. On the left I’ve plotted the number of university and government FTE researchers (including post-grads), and the productivity in papers per FTE researcher from 1996-2006.

This shows that while total publication output has increased significantly, so has the number of FTE researchers, leaving productivity in papers per FTE surprisingly static. Most of this increase in FTE researchers comes from a large expansion in post-graduate student numbers. In many disciplines, we are now training more post-graduate students than ever before. This is good news (especially given the discussion here), but as I’ll discuss in a later post, this growth in post-grad numbers is not uniform across the disciplines.

Thus on the face of it, the introduction of the performance-based research fund has not led to an increase in bibliometric productivity. However there are claims that the pbrf has led to an increase in research quality, as measured by citations. One way to test this is to compare university citations with those from the CRIs – this will be the subject of a later post.