On Tue, 9 Oct 2001, C. Lee Giles wrote:
> Is this just the beginning or an aberration?
There are at least 20,000 refereed journals.
http://www.ulrichsweb.com/ulrichsweb/
All their contents need to be freed online, and as soon as possible.
However, there are reasons to doubt that the fastest, safest, and most
probable way to bring this about is for the 20K editorial boards of the
established journals (who do not agree to restructure themselves and
give away their full-text contents online for free) to resign and start
up new journals!
It is for the authors (and their institutions) of all those articles to
take matters into their own hands now, freeing their own refereed
papers by self-archiving them in their own institutions` OAI-compliant
Eprint Archives
http://www.arl.org/sparc/pubs/enews/aug01.html#6
This will allow for a gradual, stable transition, with neither the risk
of chaotically destabilizing the existing refereed journal literature
by suddenly having 20K editorial boards resign and look for someone
else to take over remaining journal operations, nor the (much more
likely) long-long wait for more journals to give away their contents
voluntarily -- or eventually lose their editorial boards if they do not
(as Machine Learning has just lost its board).
These are radical, risky, slow, and unlikely strategies for freeing the
refereed research literature, whereas the self-archiving solution is
already proved, within reach, and can bring it about stably, and very
quickly.
Harnad, S. (2001) Six Proposals for Freeing the Refereed Literature
Ariadne 28 June 2001.
http://www.ariadne.ac.uk/issue28/minotaur/#1
http://www.ecs.soton.ac.uk/~harnad/Tp/ariadne.htm
The motivation for freeing the refereed research literature is to
maximize the access to, and the impact/uptake of, refereed research.
As researchers (and their institutions) come to realize that
self-archiving is an instant way to maximize access/impact/uptake, more
and more of them will do it, and the positive feedback from
self-archiving`s benefits -- in increased access/impact/uptake for
those papers and authors, as demonstrated by Lee Giles's own group:
http://www.neci.nec.com/~lawrence/papers/online-nature01/ and
forthcoming search-engines that display citation and download impact
factors for papers and authors
http://cite-base.ecs.soton.ac.uk/help/index.php3 -- will induce still
further researchers to self-archive.
Nor will journal cancellations be sudden and immediate (and potentially
catastrophic) with the author/institution self-archiving option -- in
fact, they may never occur at all, if there continues to be a market
for publishers' options even after the basic refereed corpus is
accessible online for free:
http://www.publications.parliament.uk/pa/cm200304/cmselect/cmsctech/399/399we152.htm
So, in my view, these dramatic editorial board resignations
are the exceptions rather than the rule, and researchers
should not sit around waiting and hoping for more of them to
occur. They should self-archive now!
What you can do now to free the refereed literature online
http://www.ecs.soton.ac.uk/~harnad/Tp/resolution.htm#7
Stevan Harnad
--------------------------------------------------------------------
> > Date: Mon, 8 Oct 2001 14:33:25 -0700 (PDT)
> > From: Michael Jordan <jordan_at_CS.Berkeley.EDU>
> > Subject: letter of resignation from Machine Learning journal
> >
> > The forty people whose names appear below have resigned from the
> > Editorial Board of the Machine Learning Journal (MLJ). We would
> > like to make our resignations public, to explain the rationale for
> > our action...
> >
> > Times have changed. Articles now circulate easily via the Internet,
> > but unfortunately MLJ publications are under restricted access.
> > Universities and research centers can pay a yearly fee of $1050 US to
> > obtain unrestricted access to MLJ articles (and individuals can pay
> > $120 US). While these fees provide access for institutions and
> > individuals who can afford them, we feel that they also have the
> > effect of limiting contact between the current machine learning
> > community and the potentially much larger community of researchers
> > worldwide whose participation in our field should be the fruit of
> > the modern Internet.
> >
> > In the spring of 2000, a new journal, the Journal of Machine Learning
> > Research (JMLR), was created...
> > Articles published in JMLR are available freely, without limits and
> > without conditions, at the journal's website, http://www.jmlr.org.
--------------------------------------------------------------------
Stevan Harnad harnad_at_cogsci.soton.ac.uk
Professor of Cognitive Science harnad_at_princeton.edu
Department of Electronics and phone: +44 23-80 592-582
Computer Science fax: +44 23-80 592-865
University of Southampton
http://www.ecs.soton.ac.uk/~harnad/
Highfield, Southampton
http://www.princeton.edu/~harnad/
SO17 1BJ UNITED KINGDOM
NOTE: A complete archive of the ongoing discussion of providing free
access to the refereed journal literature online is available at the
American Scientist September Forum (98 & 99 & 00 & 01):
http://amsci-forum.amsci.org/archives/American-Scientist-Open-Access-Forum.html
or
http://www.ecs.soton.ac.uk/~harnad/Hypermail/Amsci/index.html
You may join the list at the amsci site.
Discussion can be posted to:
american-scientist-open-access-forum_at_amsci.org
Received on Tue Oct 09 2001 - 17:19:29 BST