Javier Ruiz-Castillo

The skewness of science in 219 sub-fields and a number of aggregates

This paper studies evidence from Thomson Scientific (TS) about the citation process of 3.7 million articles published in the period 1998–2002 in 219 Web of Science (WoS) categories, or sub-fields. Reference and citation distributions have very different characteristics across sub-fields. However, when analyzed with the Characteristic Scores and Scales (CSS) technique, which is replication and scale invariant, the shape of these distributions over three broad categories of articles appears strikingly similar. Reference distributions are mildly skewed, but citation distributions with a 5-year citation window are highly skewed: the mean is 20 points above the median, while 9–10% of all articles in the upper tail account for about 44% of all citations. The aggregation of sub-fields into disciplines and fields according to several aggregation schemes preserve this feature of citation distributions. It should be noted that when we look into subsets of articles within the lower and upper tails of citation distributions the universality partially breaks down. On the other hand, for 140 of the 219 sub-fields the existence of a power law cannot be rejected. However, contrary to what is generally believed, at the sub-field level the scaling parameter is above 3.5 most of the time, and power laws are relatively small: on average, they represent 2% of all articles and account for 13.5% of all citations. The results of the aggregation into disciplines and fields reveal that power law algebra is a subtle phenomenon.

The decisions of Spanish youth: A cross-section study

Abstract. This paper presents a simultaneous model for the joint decisions of working, studying and leaving the parental household by young people in Spain. Using cross-section data from the 1990–1991 Encuesta de Presupuestos Familiares, the model is estimated by a two stage estimation method. Endogeneity of the three decisions proves to be important in order to understand the dynamics of household formation. Our results also confirm a number of plausible intuitions about the effect of individual characteristics and economic variables on these decisions, and provide some new insights into the reasons for young people in Spain remaining in large numbers in the parental home. Most of the results are gender independent.

References made and citations received by scientific articles

This article studies massive evidence about references made and citations received after a 5‐year citation window by 3.7 million articles published in 1998 to 2002 in 22 scientific fields. We find that the distributions of references made and citations received share a number of basic features across sciences. Reference distributions are rather skewed to the right while citation distributions are even more highly skewed: The mean is about 20 percentage points to the right of the median, and articles with a remarkable or an outstanding number of citations represent about 9% of the total. Moreover, the existence of a power law representing the upper tail of citation distributions cannot be rejected in 17 fields whose articles represent 74.7% of the total. Contrary to the evidence in other contexts, the value of the scale parameter is above 3.5 in 13 of the 17 cases. Finally, power laws are typically small, but capture a considerable proportion of the total citations received.

Field-normalized citation impact indicators using algorithmically constructed classification systems of science

We study the problem of normalizing citation impact indicators for differences in citation practices across scientific fields. Normalization of citation impact indicators is usually done based on a field classification system. In practice, the Web of Science journal subject categories are often used for this purpose. However, many of these subject categories have a quite broad scope and are not sufficiently homogeneous in terms of citation practices. As an alternative, we propose to work with algorithmically constructed classification systems. We construct these classification systems by performing a large-scale clustering of publications based on their citation relations. In our analysis, 12 classification systems are constructed, each at a different granularity level. The number of fields in these systems ranges from 390 to 73,205 in granularity levels 1 to 12. This contrasts with the 236 subject categories in the WoS classification system. Based on an investigation of some key characteristics of the 12 classification systems, we argue that working with a few thousand fields may be an optimal choice. We then study the effect of the choice of a classification system on the citation impact of the 500 universities included in the 2013 edition of the CWTS Leiden Ranking. We consider both the MNCS and the PPtop 10% indicator. Globally, for all the universities taken together citation impact indicators generally turn out to be relatively insensitive to the choice of a classification system. Nevertheless, for individual universities, we sometimes observe substantial differences between indicators normalized based on the journal subject categories and indicators normalized based on an appropriately chosen algorithmically constructed classification system.

Quantitative evaluation of alternative field normalization procedures

Wide differences in publication and citation practices make impossible the direct comparison of raw citation counts across scientific disciplines. Recent research has studied new and traditional normalization procedures aimed at suppressing as much as possible these disproportions in citation numbers among scientific domains. Using the recently introduced IDCP (Inequality due to Differences in Citation Practices) method, this paper rigorously tests the performance of six cited-side normalization procedures based on the Thomson Reuters classification system consisting of 172 sub-fields. We use six yearly datasets from 1980 to 2004, with widely varying citation windows from the publication year to May 2011. The main findings are the following three. Firstly, as observed in previous research, within each year the shapes of sub-field citation distributions are strikingly similar. This paves the way for several normalization procedures to perform reasonably well in reducing the effect on citation inequality of differences in citation practices. Secondly, independently of the year of publication and the length of the citation window, the effect of such differences represents about 13% of total citation inequality. Thirdly, a recently introduced two-parameter normalization scheme outperforms the other normalization procedures over the entire period, reducing citation disproportions to a level very close to the minimum achievable given the data and the classification system. However, the traditional procedure of using sub-field mean citations as normalization factors yields also good results.

The skewness of scientific productivity

This paper exploits a unique 2003–2011 large dataset, indexed by Thomson Reuters, consisting of 17.2 million disambiguated authors classified into 30 broad scientific fields, as well as the 48.2 million articles resulting from a multiplying strategy in which any article co-authored by two or more persons is wholly assigned as many times as necessary to each of them. The dataset is characterized by a large proportion of authors who have their oeuvre in several fields. We measure individual productivity in two ways that are uncorrelated: as the number of articles per person and as the mean citation per article per person in the 2003–2011 period. We analyze the shape of the two types of individual productivity distributions in each field using size- and scale-independent indicators. To assess the skewness of productivity distributions we use a robust index of skewness, as well as the Characteristic Scores and Scales approach. For productivity inequality, we use the coefficient of variation. In each field, we study two samples: the entire population, and what we call “successful authors”, namely, the subset of scientists whose productivity is above their field average. The main result is that, in spite of wide differences in production and citation practices across fields, the shape of field productivity distributions is very similar across fields. The parallelism of the results for the population as a whole and for the subset of successful authors, when productivity is measured as mean citation per article per person, reveals the fractal nature of the skewness of scientific productivity in this case. These results are essentially maintained when any article co-authored by two or more persons is fractionally assigned to each of them.

Intermediate inequality and welfare

Abstract. We introduce a new centrist or intermediate inequality concept, between the usual relative and absolute notions, which is shown to be a variant of the α-ray invariant inequality measures in Pfingsten and Seidl (1997). We say that distributions x and y have the same (x, π)-inequality if the total income difference between them is allocated among the individuals as follows: 100π% preserving income shares in x, and 100(1−π)% in equal absolute amounts. This notion can be made as operational as current standard methods in Shorrocks (1983).

The measurement of low- and high-impact in citation distributions: Technical results

This paper introduces a novel methodology for comparing the citation distributions of research units of a certain size working in the same homogeneous field. Given a critical citation level (CCL), we suggest using two real valued indicators to describe the shape of any distribution: a high-impact and a low-impact measure defined over the set of articles with citations above or below the CCL. The key to this methodology is the identification of a citation distribution with an income distribution. Once this step is taken, it is easy to realize that the measurement of low-impact coincides with the measurement of economic poverty. In turn, it is equally natural to identify the measurement of high-impact with the measurement of a certain notion of economic affluence. On the other hand, it is seen that the ranking of citation distributions according to a family of low-impact measures is essentially characterized by a number of desirable axioms. Appropriately redefined, these same axioms lead to the selection of an equally convenient class of decomposable high-impact measures. These two families are shown to satisfy other interesting properties that make them potentially useful in empirical applications, including the comparison of research units working in different fields.

High- and Low-impact Citation Measures: Empirical Applications

This paper contains the first empirical applications of a novel methodology for comparing the citation distributions of research units working in the same homogeneous field. The paper considers a situation in which the world citation distribution in 22 scientific fields is partitioned into three geographical areas: the U.S., the European Union (EU), and the rest of the world (RW). Given a critical citation level (CCL), we suggest using two real valued indicators to describe the shape of each areas distribution: a high- and a low-impact measure defined over the set of articles with citations below or above the CCL. It is found that, when the CCL is fixed at the 80th percentile of the world citation distribution, the U.S. performs dramatically better than the EU and the RW according to both indicators in all scientific fields. This superiority generally increases as we move from the incidence to the intensity and the citation inequality aspects of the phenomena in question. Surprisingly, changes observed when the CCL is increased from the 80th to the 95th percentile are of a relatively small order of magnitude. Finally, it is found that international co-authorship increases the high-impact and reduces the low-impact level in the three geographical areas. This is especially the case for the EU and the RW when they cooperate with the U.S.

Differences in citation impact across countries

Using a large data set, indexed by Thomson Reuters, consisting of 4.4 million articles published in 1998–2003 with a 5‐year citation window for each year, this article studies country citation distributions for a partitioning of the world into 36 countries and two geographical areas in eight broad scientific fields and the all‐sciences case. The two key findings are the following. First, country citation distributions are highly skewed and very similar to each other in all fields. Second, to a large extent, differences in country citation distributions can be accounted for by scale factors. The Empirical situation described in the article helps to understand why international comparisons of citation impact according to (a) mean citations and (b) the percentage of articles in each country belonging to the top 10% of the most cited articles are so similar to each other.