Spam: It's Not Just for Inboxes and Search Engines! Making Hirsch h-index Robust to Scientospam

What is the ‘level of excellence’ of a scientist and the real impact of his/her work upon the scientific thinking and practising? How can we design a fair, an unbiased metric – and most importantly – a metric robust to manipulation? Quantifying an individual’s scientific merit The evaluation of the scientific work of a scientist has long attracted significant interest, due to the benefits by obtaining an unbiased and fair criterion. A few years ago such metrics were yet another topic of investigation for the scientometric community with only theoretical importance, without any practical extensions. Very recently though the situation has dramatically changed; an increasing number of academic institutions are using such scientometric indicators to decide faculty promotions. Automated methodologies have been developed to calculate such indicators [6]. Also, funding agencies use them to allocate funds, and recently some governments are considering the consistent use of such metrics for funding distribution. For instance, the Australian government has established the Research Quality Framework (RQF) as an important feature in the fabric of research in Australia; the UK government has established the Research Assessment Exercise (RAE) to produce quality profiles for each submission of research activity made by institution. The use of such indicators to characterize a scientist’s merit is controversial, and a plethora of arguments can be stated against their use. In his recent article, David Parnas [5] described the negative consequences to the scientific progress caused by the “publish or perish” marathon run by all scientists. Following the reasoning of the phrase attributed to A. Einstein that “Not everything that can be counted counts, and not everything that counts can be counted.”, we stress that the assessment of a scientist is a complex social and scientific process that is difficult to narrow it into a single scientometric indicator. Most of the times, the verbal descriptions of a scholar’s quality is probably the best indicator. Though, the expressive and descriptive power of numbers (i.e., scientometric indicators) can not unthinkingly be ignored; instead of devaluing them, we should strive to develop the “correct set” of indicators and, most importantly, to use them in the right way. No matter how skeptical is someone against the use of such indicators, the impact of a scholar can quite safely be described in terms of the acceptance of his/her ideas by the wider scientific community that s/he belongs to. Traditionally, this acceptance is measured by the number of authored papers and/or the number of citations. The early metrics are based on http://www.uts.edu.au/research/policies/resdata/RQF.html http://www.rae.ac.uk