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Quantitative methods are
the foundation of science. They represent a way of knowing the
answers to very basic questions such as how big, how fast, how many,
etc. The great British scientist Lord Kelvin (William Thomson,
1824-1907) noted, "If you can measure that of which you
speak, and can express it by a number, you know something of your
subject; but if you cannot measure it, your knowledge is meager and
unsatisfactory."
With the introduction of computers after WW II and their rapid
improvements in speed and capacity in the past two decades, large
databases have been created of all sorts of phenomena, both natural
and social. Bibliographic databases, such as ISI's, have been built
up over many years now, and are a vast treasure house of insight
into what happened in the annals of recent scientific history. In
addition to using these databases to find the publications needed
for research work at hand, investigators began turning their
attention and the tools of their profession (quantitative methods)
to science itself. They ask questions such as how big, how fast, how
many, but in this case about scientists, nations, institutions,
journals, etc.
Publication counts became units for measuring output. Citation
counts, as they became available from ISI's Science Citation
Index,
were recognized as units of influence or impact (when total
citations were divided by publications). The sociologist of science,
Robert Merton, has term citations "pellets of peer
recognition." In the vast majority of cases, a citation
recorded in a scientific paper is a positive expression of
importance, influence, or utility. Seen in yet another way, it is a
type of currency by which scientists repay their intellectual debts.
Over the past 30 years a large literature has accumulated on the
validity of using citation counts to measure peer recognition and
esteem. Citation counts correlate to expert opinion on research
excellence to a degree higher than peers agree with each other on
this subject. Thus, it is generally a robust measure of scholarly
achievement, reflected in the referencing patterns of peer
researchers.
It is one thing, simply put, to publish much and to publish in top
quality journals. But it is another thing again, and perhaps even
more impressive, to have your work actually cited, and frequently
cited, by your peers.
Several
rudimentary rules for using publication and citation counts should
always be kept in mind:
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Compare like with
like: scientists or papers in the same field and papers of the
same vintage, since different fields exhibit different average
rates of citations and older papers have more time to collect
citations than younger papers.
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Multiple measures
(number papers, citations, cites/paper, percent cited vs.
uncited) and large datasets are superior to single, thin ones.
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Relative measures
should be used, not merely absolute scores (such as setting
citation counts relative to appropriate baseline, or average,
scores).
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Sometimes the area
of research is not adequately surveyed by the database examined,
in which case the measures will not be robust and could be
misleading.
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And, most important,
that these methods should be used as supplement and not as
replacement for careful consideration by informed peers or experts.
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