Goodhart's law: "when a measure becomes a target, it ceases to be a good
measure".


http://plus.maths.org/content/how-good-your-maths


<http://plus.maths.org/content/how-good-your-maths>
 Submitted by mf344 on September 9, 2010

Bad statistics can mislead, and who'd know this better than mathematicians?
It's ironic, then, that mathematics itself has fallen victim to the
seductive lure of crude numbers. Mathematicians' work is being measured,
ranked and judged on the basis of a single statistic: the number of times
research papers are being cited by others. And mathematicians are not happy
about it.

Is this good maths?

Like any other area in receipt of public money, mathematical research needs
to be accountable. A reasonable way to judge the quality of research is the
impact it has on future research: ground-breaking work will be heavily
discussed and built upon, and mediocre work largely ignored. Traditionally,
the reputations of individual researchers, institutions, or research
journals have hinged on the opinions of experts in the field. The rationale
behind using citation statistics is that bare numbers can overcome the
inherent subjectivity of these judgments. In a competitive world it's the
bottom line that should do the talking.

Bottom lines are crude, however, and summary statistics open to misuse. A
whiff of scandal floated through this year's International Congress of
Mathematicians <http://plus.maths.org/content/latest-news-icm-2010>, when
the mathematician Douglas N. Arnold (president of the Society for Industrial
and Applied Mathematics) exposed what appears like a blatant example of
citation fraud. It involves the *International Journal of Nonlinear Science
and Numerical Simulations* (IJNSNS) and a summary statistic called the *impact
factor*.

The impact factor of a journal measures the average number of citations per
article in the journal, but only taking into account citations from the *
current* year to articles that have appeared in the previous *two* years. So
old citations don't count and neither do citations to articles that are
older than three years.

IJNSNS has topped the impact factor chart for applied maths journals for the
last four years by a massive margin. In 2009 its impact factor was more than
double that of the second in line, the esteemed*Communications on Pure and
Applied Mathematics* (CPAM). A panel of experts, however, had rated IJNSNS
in its second-to-last category: as having a "solid, though not outstanding
reputation". In the experts' opinion IJNSNS comes at best 75th in the
applied maths journal rankings, nowhere near the top.

There are some easy explanations for this mis-match between the impact
factor chart and expert opinion. A closer look at citation statistics shows
that 29% of the citations to IJNSNS (in 2008) came from the editor-in-chief
of the journal and two colleagues who sit on its editorial board. A massive
70% of citations to IJNSNS that contributed to its impact factor came from
other publications over which editors of IJNSNS had editorial influence. An
example is the proceedings of a conference that had been organised by
IJNSNS's editor-in-chief Ji-Huan He. He controlled the peer review process
that srcutinised papers submitted to the proceedings.

Another striking statistic is that 71.5% of citations to IJNSNS just
happened to cite articles that appeared in the two-year window which counts
towards the impact factor (the 71.5% is out of citations from 2008 to
articles that have appeared since 2000). That's compared to 16% for CPAM. If
you use a five-year citation window (from 2000 to 2005) to calculate the
impact factor, IJNSNS's factor drops dramatically, from 8.91 to 1.27.

The conclusions from this are obvious: cite your own journal as often as
possible (with citations falling in the two-year window) and make sure that
authors who fall under your editorial influence do the same, and you can
propel your journal to the top of the rankings.

Libraries use impact factors to make purchasing decisions,
but mathematicians are judged by them too.

What's worrying is that impact factors are not just being used to rank
journals, but also to assess the calibre of the researchers who publish in
them and the institutions that employ these researchers. "I've received
letters from [mathematicians] saying that their monthly salaries will depend
on the impact factors of the journals they publish in. Departments and
universities are being judged by impact factors," says Martin Grötschel,
Secretary of the International Mathematical Union, which published a highly
critical report on citation statistics in 2008.

Grötschel dismisses the blind use of impact factors as "nonsense" and not
just because they are open to manipulation. For mathematics in particular,
the two-year window that counts towards the impact factor is simply too
short. There are examples of seminal maths papers that didn't get cited for
decades. In fact, scouring 3 million recent citations in maths journals, the
IMU found that roughly 90% of all citations fall outside the two-year window
and therefore don't count towards the impact factor. This is in stark
contrast to faster moving sciences, for example biomedicine, so using impact
factors to compare disciplines presents mathematics in a truly terrible
light.

Another confounding factor is that papers may get cited for all the wrong
reasons. As Malcolm MacCallum, director of the Heilbronn Institute for
Mathematical 
Research<http://www.maths.bris.ac.uk/research/heilbronn_institute/>,
pointed out at a round table discussion at the ICM, one way of bumping up
your citation rates is to publish a result that's subtly wrong, so others
expose the holes in your proof, citing your paper every time. Malicious
intent aside, someone might cite a paper not because it contains a
ground-breaking result, but because it gives a nice survey of existing
results. If on the other hand your result is so amazing that it becomes
universally known, you might lose out on citations altogether — few people
bother to cite Einstein's original paper containing the equation *E=mc2* as
the result and its originator are now part of common knowledge.

The list of impact factor misgivings goes on (you can read more in the IMU
report on citation
statistics<http://www.mathunion.org/fileadmin/IMU/Report/CitationStatistics.pdf>).
The fact is that a single number cannot reflect a complex picture. With
respect to manipulation, Arnold points to Goodhart's law: "when a measure
becomes a target, it ceases to be a good measure". What's more, no one knows
exactly what the impact factor is supposed to measure — what exactly does a
citation *mean*? As a statistical quantity the impact factor is not
sufficiently robust to chance variation. As the IMU report points out,
there's no sound statistical model linking citation statistics to quality.

How, then, should mathematical quality be measured? Mathematicians
themselves aren't entirely in agreement on how big a role, if any, citation
statistics should play, or even whether things should be ranked at all.
Everyone agrees, however, that human judgment is essential. "Impact factors
— we cannot ignore them, but we have to interpret them with great care,"
says Grötschel, the IMU Secretary. The IMU, together with the International
Council of Industrial and Applied Mathematics, has set up a joint committee
to come up with a way of ranking journals that might involve human judgment
*and* statistics.

With their fight against the mindless use of statistics mathematicians will
do a service not just to themselves. "Some of [our work on this] has very
broad applications in other sciences," says Grötschel. "It's very important
that mathematicians are at the forefront of this issue."

-- 
==================================================================
Adolfo Neto
Assistant Professor - Federal University of Technology, Paraná
Web: http://www.dainf.ct.utfpr.edu.br/~adolfo
Twitter: http://twitter.com/adolfont
Mestrado em Computação Aplicada: http://www.ppgca.ct.utfpr.edu.br
==================================================================




-- 
==================================================================
Adolfo Neto
Assistant Professor - Federal University of Technology, Paraná
Web: http://www.dainf.ct.utfpr.edu.br/~adolfo
Twitter: http://twitter.com/adolfont
Mestrado em Computação Aplicada: http://www.ppgca.ct.utfpr.edu.br
==================================================================
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