A publication suffering from delayed recognition is a publication that received very little attention shortly after publication, but received recognition later. Stephen Cole proposed to use citations as a proxy for recognition (Cole, 1970). Although recognition can be given in many ways—receiving tenure is another important way in which scientists are recognized for their achievements—collecting received citations is the most practiced way to operationalize the notion of delayed recognition. This contribution is not meant as a review of the topic, but we concentrate on a few recent developments. Yet, among the many papers written by colleagues on delayed recognition we single out for mention: (Bornmann et al., 2018; Burrell, 2005; Du & Wu, 2016; El Aichouchi & Gorry, 2018; Garfield, 1980; Glänzel et al., 2003; Ke et al., 2015; Li & Ye, 2012; van Raan, 2004, 2015, 2017).
In this short paper we will discuss three aspects: naming of the phenomenon, recent methods based on a cumulative citation curve and re-interpretation of delayed recognition as a fuzzy concept.
The concept of delayed recognition in relation to persons or articles has also been described as premature discovery, suffering from Mendel’s syndrome, being late bloomers or being ahead of one’s time. Mendel’s work on the rules of heredity is often considered as the prototype case. Yet, Mendel’s work was not totally unknown before the 20th century as mentioned by Garfield (1970), giving reference to Zirkle (1964).
In an article published in 2004, Ton van Raan proposed the name “sleeping beauty” for an article suffering delayed recognition (van Raan, 2004). This catchy term took on immediately: on June 3, 2018 van Raan’s article had already received 176 citations in the Web of Science (WoS). When the value, importance or usefulness of such a “sleeping beauty” is finally recognized in another article, denoted here as P, serving as a wake-up call for the scientific community (leading to general recognition of the “sleeping beauty”), article P is referred to as the Prince, continuing the metaphor of the story of the Sleeping Beauty. The act of “awakening” the sleeping beauty is then sometimes referred to as “the kiss.”
Sugimoto and Mostafa (2018) recalled that, in the context of sleeping beauties, Braun et al. (2010, p. 198) discussed the “ideal couple” and further sexualized the metaphor by discussing male and female dominance and “absolute superiority”: a measurement of the relative citations achieved by the prince and the sleeping beauty. Finally, they introduced the notion of chastity of sleeping beauties, in terms of the number of articles that awoke the dormant article and mentioned the possible unfaithful behavior of princes. Clearly a form of sexualization of citation trajectories has been—and is still—going on.
It is clear that these types of metaphors, continuing with “brave girls” for articles which are immediately recognized (Ye & Bornmann, 2018) have the tendency to become more and more gender-loaded. For this reason Sugimoto & Mostafa (2018) wrote an editorial, decrying this “clear violation of sociocultural norms”. They made a plea to future authors that the use of any such terms, despite connections to historical roots in the literature, should be avoided. As a consequence they stated that JASIST’s author guidelines will be adapted to make this policy explicit and clear.
As a reaction Hu et al. (2018) proposed the metaphor of gender-neutral terms “hibernator” and “awakener” to replace the terms “sleeping beauty” and “prince”. It is, of course, an open question if any metaphor is really useful.
Although being a sleeping beauty sounds like a yes/no situation, it is clear that delayed recognition is not a clear-cut phenomenon and a sleeping beauty in the eyes of one person may not be one in the eyes of a colleague. A similar observation holds in relation to the citation database used for collecting citations. To solve this problem Ke et al. (2015) turned delayed recognition into a time-dependent continuous phenomenon by defining a beauty coefficient at time
The numerator of a term in
If now each term in the sum determining
All else staying the same, All else staying the same,
All else staying the same,
All else staying the same,
In recent papers Du & Wu (2017, 2018) note some disadvantages of the definition proposed by Ke et al. (2015), the most important one being the high importance given to the peak. They claim that the determination of the
For these reasons these authors propose a different approach, not based on the citation curve,
Now we propose a framework to study delayed recognition of an article at a given moment in time, say
Studying this question we consider three aspects: “delayed,” “recognition” and fuzzy membership.
When it comes to the “delayed” part, this implies that one must wait a certain period before one may say that there is a delay. In this study we wait at least ten years (see further for details), but further investigations are needed to study the influence of this starting time. Does it matter if one starts investigations 10 years after publication or is 15 or 20 years better?
Next we come to the “recognition” part. We propose to concentrate on the 1% most cited publications in the same publication year as the publication under investigation. A choice must further be made to include all publication types in this 1% or only normal articles (or normal articles and reviews). We think that here all choices are valid, i.e., have some scientific value, but the choice must be stated clearly.
Finally we come to the most difficult part: constructing a framework to come to a fuzzy membership value. This value, between zero and one, must in a meaningful way express to which extent an article can be said to belong to the fuzzy set of publications with delayed recognition. This membership function, as calculated at time
To the best of our knowledge Ke et al. (2015) were the first to state that suffering delayed recognition is not a yes-no situation. They introduced a parameter-free measure that quantifies the extent to which a specific paper can be considered to suffer delayed recognition. Papers with citations growing linearly with time have
We will calculate a partial membership function, denoted as
The use of the maximum function in formula (3) avoids that the
Now we calculate the sum of the differences in each
The largest possible value of
leading to a value between -1 and +1.
We note that if an article receives its first citation in year 10 and is ‘recognized’ then, based on equation (3), its
If the cumulative citation curve is everywhere concave then
If citations grow linearly in time, then
In this contribution we provide three examples, leaving more investigations to further research.
As a real-world example we begin with Romans’ article (Romans, 1986), an article studied by van Raan (2004). This article got its first citation in 1995 (
Next we consider Leaky et al. (1964). This article has been studied as a sleeping beauty in (Tobias, 1996). The WoS contains 127,018 publications of article type published in 1964. Among these the article ranked 1271 received 242 citations. As Leakey et al. (1964) received 348 citations it belongs to the top 1% most-cited (data collected on June 5 2018). Its
Year Year Year Year 1974 0.014 1985 -0.019 1996 -0.032 2007 -0.007 1975 0.020 1986 -0.055 1997 -0.032 2008 0.027 1976 0.005 1987 -0.053 1998 -0.061 2009 0.061 1977 -0.006 1988 -0.011 1999 -0.059 2010 0.060 1978 -0.013 1989 0.013 2000 -0.057 2011 0.085 1979 -0.035 1990 0.016 2001 -0.055 2012 0.102 1980 -0.036 1991 -0.015 2002 -0.074 2013 0.145 1981 -0.023 1992 -0.026 2003 -0.084 2014 0.151 1982 0.023 1993 0.005 2004 -0.041 2015 0.164 1983 0.003 1994 -0.022 2005 -0.017 2016 0.194 1984 -0.004 1995 -0.023 2006 -0.006 2017 0.225
This leads us to question Tobias’ paper (1996). What did he claim? It is important to know that, actually, Tobias was a co-author of the Leakey et al. (1964) paper. In his paper from 1996 he described how their findings were not accepted by their colleagues, but that step by step the original objections against their findings and corresponding theory fell away and, in his words, by 1984 their findings were accepted. This happened twenty years after their publication and hence, these findings were—rightly—described as a premature discovery. Honesty forces us to include that even today the exact position of
The citation curve does not show any sign of this observation. We think this illustrates the very important fact that using citations is just an operationalization and experts may, rightly, have other opinions. We note that this article and Romans’ are also under-cited influential and hence citation chimeras in the sense of (Hu & Rousseau, 2018). This term refers to the fact that these articles are exceptional in terms of received citations and in terms of second-generation citations.
Finally, we consider one of our own articles, namely (Otte & Rousseau, 2002). Again, we first check if it belongs to the top 1% most-cited articles. The WoS contains 813,472 publications of article type published in 2002. Among these the article ranked 8,135 received 280 citations. As Otte and Rousseau (2002) received 368 citations it belongs to the top 1% most-cited (data collected on June 5, 2018). The
Year K( 2011 0.515 2012 0.480 2013 0.476 2014 0.455 2015 0.464 2016 0.477 2017 0.523
We reviewed recent developments related to the study of delayed recognition, leading to the idea to consider delayed recognition as a fuzzy concept. We proposed a method to obtain fuzzy membership values. One of the requirements for suffering delayed recognition, is that the article must belong to the 1% most-cited ones. This means that at most 1% of the articles under consideration have a non-zero fuzzy membership value, and probably much less than 1%. The value 0.333 for linear growth in citations can be considered a benchmark for comparisons.
Besides proper hibernators (sleeping beauties) who have a long period with no or few citations, articles suffering delayed recognition may have a convex cumulative citation curve, such as in the case of linear growth in citations. Examples of these two types are shown in this contribution: Romans (1986) being a proper hibernator and Leakey et al. (1964) and Otte & Rousseau (2002) being examples of the second type.
We made the important observation that using citations to study delayed recognition is just a—convenient—operationalization of the concept, but that experts may agree on delayed recognition long before this is shown by citations. This is illustrated by the case of Leakey et al. (1964). This leads to the question: How good (adequate) is citation analysis for detecting premature discoveries?
As this contribution is just a feasibility study, many questions are left unanswered, such as:
What are typical values for membership functions? Wouldn’t it be better to use normalized citation scores instead of absolute ones as done here? If so, how to normalize: with respect to the database, with respect to the field, or both (Bornmann et al., 2018)? Can this framework, by focusing on negative values and years immediately after the publication year, also be used for characterizing early recognition (flash-in-the-pan)? If so, how?
What are typical values for membership functions?
Wouldn’t it be better to use normalized citation scores instead of absolute ones as done here? If so, how to normalize: with respect to the database, with respect to the field, or both (Bornmann et al., 2018)?
Can this framework, by focusing on negative values and years immediately after the publication year, also be used for characterizing early recognition (flash-in-the-pan)? If so, how?
These questions are left as topics for further research.
Finally we mention the obvious limitation: as all citation studies also this one is database dependent.
K-values for Otte and Rousseau (2002).
K-values for Leakey et al. (1964).
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