Let's dumb-up (journal citation) impact factors

From: Stevan Harnad <harnad_at_ecs.soton.ac.uk>
Date: Sat, 23 Oct 2004 12:50:55 +0100

The following is a commentary on an editorial in the British Medical
Journal entitled:

    Let's dump impact factors
    Kamran Abbasi, acting editor
    BMJ 2004;329 (16 October), doi:10.1136/bmj.329.7471.0-h
    http://bmj.bmjjournals.com/cgi/content/full/329/7471/0-h

I've submitted the following commentary. It should appear Monday
at:

    http://bmj.bmjjournals.com/cgi/eletters/329/7471/0-h

Prior Amsci Topic Thread:

    "Citation and Rejection Statistics for Eprints and Ejournals"
    http://www.ecs.soton.ac.uk/~harnad/Hypermail/Amsci/0138.html
    http://www.ecs.soton.ac.uk/~harnad/Hypermail/Amsci/1112.html

----------------------------------------------------------------------

        Enrich Impact Measures Through Open Access Analysis
              (Or: "Let's Dumb-Up Impact Factors")

                      Stevan Harnad

The "journal impact factor" -- the average number of citations
received by the articles in a journal -- is not an *invalid* instrument,
but a blunt (and obsolescent) one. It does have some meaning and some
predictive value (i.e., it is not merely a circular "definition" of
impact), but we can do far better. Research impact evaluation should
be thought of in multiple-regression terms: The journal impact factor
is just one of many potential predictive factors, each with its own
weight, and each adding a certain amount to the accuracy of the
prediction/evaluation.

The journal impact factor is the first of the regression weights, but
not because it is the biggest or strongest, but just because it came
first in time: Gene Garfield (1955, 1999) and the Institute for
Scientific Information (ISI) started to count citations (and citation
immediacy, and other data) and produced an index of the average
(2-year) citation counts of journals -- as well as the individual
citation counts of articles and authors.

The fact that unenterprising and unreflecting evaluation committees
found it easier to simply weight their researchers' publication counts
with the impact factors of the journals in which they appeared was due
in equal parts to laziness and to the valid observation that journal
impact factors *do* correlate, even if weakly, with journals' rejection
rates, hence with the rigour of their peer review, and hence with the
quality of their contents:

    "High citation rates... and low manuscript acceptance rates...
    appear to be predictive of higher methodological quality scores for
    journal articles" (Lee et al. 2002)

    "The majority of the manuscripts that were rejected... were eventually
    published... in specialty journals with lower impact factor..." (Ray
    et al. 2000)

    "perceived quality ratings of the journals are positively correlated
    with citation impact factors... and negatively correlated with
    acceptance rate." (Donohue & Fox 2000)

    "There was a high correlation between the rejection rate and the
    impact factor" (Yamasaki 1995)

But even then, the article and author exact citation counts could have
been added to the regression equation -- yet only lately are
evaluation committees beginning to do this. Why? Again, laziness and
unenterprisingness, but also effort and cost: An institution needs to
be subscribed to ISI's citation databases and needs to take the
trouble to consult them systematically.

But other measures -- richer and more diverse ones -- are developing,
and with them the possibility of ever more powerful, accurate and
equitable assessment and prediction of research performance and impact
(Harnad et al. 2004). These measures (e.g. citebase
http://citebase.eprints.org/) include: citation counts for article,
author, and journal; download counts for article, author and journal;
co-citation counts (who is jointly cited with whom?); eventually
co-download counts (what is being downloaded with what?); analogs of
google's "page-rank" algorithm (recursively weighting citations by the
weight of the citing work); "hub/authority" analysis (much-cited vs.
much-citing works); co-text "semantic" analysis (what -- and whose --
text patterns resemble the cited work?); early-days download/citation
correlations (http://citebase.eprints.org/analysis/correlation.php)
(downloads today predict citations citations in two years (Harnad &
Brody 2004); time-series analyses; and much more.

So the ISI journal-impact factor is merely a tiny dumbed-down portion
of the rich emerging spectrum of objective impact indicators; it now
needs to be dumbed-up, not dumped! Two things need to be kept in mind
in making pronouncements about the use of such performance indicators:

    (i) Consider the alternative! The reason we resort to objective
    measures at all is that reading and evaluating every single work
    anew each time it needs to be evaluated is not only subjective
    but labour-intensive, and requires at least the level of expertise
    and scrutiny that (one hopes!) the journal peer review itself has
    accorded the work once already, in a world in which qualified
    refereeing time is an increasingly scarce, freely-given resource,
    stolen from researchers' own precious research time. Citations (and
    downloads) indicate that researchers have found the work in question
    useful in their own research.

    (ii) The many new forms of impact analysis can now be done
    automatically, without having to rely on ISI -- if and when
    researchers make all their journal articles Open Access, by
    self-archiving them in OAI compliant Eprint Archives on the
    Web. Remarkable new scientometric engines are just waiting for that
    open database to be provided in order to add the rich new panoply
    of impact measures promised above (Harnad et al. 2003).

Donohue JM, Fox JB (2000) A multi-method evaluation of journals in the
decision and management sciences by US academics. OMEGA-INTERNATIONAL
JOURNAL OF MANAGEMENT SCIENCE 28 (1): 17-36

Garfield, E., (1955) Citation Indexes for Science: A New Dimension in
Documentation through Association of Ideas. SCIENCE 122: 108-111
http://www.garfield.library.upenn.edu/papers/science_v122(3159)p108y1955.htm

Garfield E. (1999) Journal impact factor: a brief review. CMAJ 161(8):
979-80. http://www.cmaj.ca/cgi/content/full/161/8/979

Harnad, S. and Brody, T. (2004) Prior evidence that downloads predict
citations BMJ Rapid Responses, 6 September 2004
http://bmj.bmjjournals.com/cgi/eletters/329/7465/546#73000

Harnad, S., Brody, T., Vallieres, F., Carr, L., Hitchcock, S.,
Gingras, Y, Oppenheim, C., Stamerjohanns, H., & Hilf, E. (2004) The
Access/Impact Problem and the Green and Gold Roads to Open Access.
SERIALS REVIEW 30. http://www.ecs.soton.ac.uk/~harnad/Temp/impact.html

Harnad, S., Carr, L., Brody, T. & Oppenheim, C. (2003) Mandated online
RAE CVs Linked to University Eprint Archives: Improving the UK
Research Assessment Exercise whilst making it cheaper and easier.
ARIADNE 35 (April 2003). http://www.ariadne.ac.uk/issue35/harnad/

Lee KP, Schotland M, Bacchetti P, Bero LA (2002) Association of
journal quality indicators with methodological quality of clinical
research articles. AMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION 287
(21): 2805-2808

Ray J, Berkwits M, Davidoff, F (2000) The fate of manuscripts rejected
by a general medical journal. AMERICAN JOURNAL OF MEDICINE 109 (2):
131-135.

Yamazaki, S (1995) Refereeing System of 29 Life-Science Journals
Preferred by Japanese Scientists SCIENTOMETRICS 33 (1): 123-129
Received on Sat Oct 23 2004 - 12:50:55 BST

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