Stephen J. Bensman

Classification and powerlaws: The logarithmic transformation

Logarithmic transformation of the data has been recommended by the literature in the case of highly skewed distributions such as those commonly found in information science. The purpose of the transformation is to make the data conform to the lognormal law of error for inferential purposes. How does this transformation affect the analysis? We factor analyze and visualize the citation environment of the Journal of the American Chemical Society (JACS) before and after a logarithmic transformation. The transformation strongly reduces the variance necessary for classificatory purposes and therefore is counterproductive to the purposes of the descriptive statistics. We recommend against the logarithmic transformation when sets cannot be defined unambiguously. The intellectual organization of the sciences is reflected in the curvilinear parts of the citation distributions while negative powerlaws fit excellently to the tails of the distributions.

Urquhart and probability: The transition from librarianship to library and information science

In this article, I analyze the role of Donald J. Urquhart in the creation of modern library and information science. Urquhart was one of the chief architects of information science in Britain and founder of the National Lending Library for Science and Technology (NLL), which evolved into the present-day British Library Document Supply Centre (BLDSC). In particular, I focus on the part played by Urquhart in the development of that branch of information science termed bibliometrics, the application of mathematical and statistical techniques to information phenomena, pursuing both historical and practical aims. The article is intended not only to trace the history of the probability distributions applicable to library use and other facets of human knowledge but also to demonstrate how these distributions can be used in the evaluation and management of scientific journal collections. For these purposes, the paper is divided into three parts of equal importance. The first part is statistical and establishes the theoretical framework, within which Urquhart’s work is considered. It traces the historical development of the applicable probability distributions, discussing their origins on the European continent and how Continental principles became incorporated in the biometric statistics that arose in Britain as a result of the Darwinian revolution. This part analyzes the binomial and Poisson processes, laying out the reasons why the Poisson process is more suitable for modeling information phenomena. In doing so, it describes key distributions arising from these processes as well as the various tests for these distributions, citing the literature that shows how to conduct these tests. Throughout the discussion, the relationship of these distributions to library use and the laws of information science is emphasized. The second part of the article analyzes the pioneering role of Urquhart as a conduit for the entry of these probability distributions into librarianship, converting it into library and information science. He was the first librarian to apply probability to library use, utilizing it not only to establish and manage the scientific journal collections of the NLL but also to evolve his Law of Supralibrary Use. Urquhart’s work is portrayed within the context of a general trend to adopt probabilistic methods for analytical purposes, and a major premise of this article is that his law and the probabilistic breakthrough, on which it was based, were most likely in Britain, which was one of the few countries not only to develop but also maintain the necessary scientific preconditions. The third—and concluding section—discusses how Urquhart’s Law forces a probabilistic reconceptualization of the functioning of the scientific journal system as well as the law’s practical implications for journal sales, collection evaluation and management, resource sharing, and the transition from the paper to the electronic format.

The impact factor: its place in Garfield's thought, in science evaluation, and in library collection management

This paper is a response to that of Vanclay, who proposes, that since the impact factor (IF) is so seriously flawed, Thomson Reuters should either correct the measure or—preferably—no longer publish it and restrict itself to journal certification. It is argued here that Vanclay’s analysis is itself seriously flawed, because he appears totally ignorant of the thought structure of Eugene Garfield, IF’s creator. As a result, Vanclay appears unaware of the importance of total cites and the close connection of IF with review journals, where the paradigms of science are defined. This paper’s author agrees that IF is a defective measure, analyzing its defects from the perspective of the frequency theory of probability, on which modern inferential statistics is based. However, he asserts that abandoning it would be counterproductive because of its demonstrated ability—even with its defects—to identify small important journals like review journals, giving it an important role in science evaluation and library collection management.

Probability distributions in library and information science: a historical and practitioner viewpoint

This paper has a dual character dictated by its twofold purpose. First, it is a speculative historiographic essay containing an attempt to fix the present position of library and information science within the context of the probabilistic revolution that has been encompassing all of science. Second, it comprises a guide to practitioners engaged in statistical research in library and information science. There are pointed out the problems of utilizing statistical methods in library and information science because of the highly and positively skewed distributions that dominate this discipline. Biostatistics are indicated as the source of solutions for these problems, and the solutions are then traced back to the British biometric revolution of 1865–1950, during the course of which modern inferential statistics were created. The thesis is presented that science has been undergoing a probabilistic revolution for over 200 years, and it is stated that this revolution is now coming to library and information science, as general stochastic models replace specific, empirical informetric laws. An account is given of the historical development of the counting distributions and laws of error applicable in statistical research in library and information science, and it is stressed that these distributions and laws are not specific to library and information science but are inherent in all biological and social phenomena. Urquharts Law is used to give a practical demonstration of the distributions. The difficulties of precisely fitting data to theoretical probability models in library and information science because of the inherent fuzziness of the sets are discussed, and the paper concludes with the description of a simple technique for identifying and dealing with the skewed distributions in library and information science. Throughout the paper, emphasis is placed on the relevance of research in library and information science to social problems, both past and present.

Anne-Wil Harzing: The publish or perish book: Your guide to effective and responsible citation analysis

Anne-Wil Harzing is a woman with an agenda. To understand this agenda, you have to know that she is a Professor of International Management at the University of Melbourne, Australia. The discipline of management is a social science, which is as vocational as it is academic. In the United States such disciplines—including, for example, business administration, education, law, library and information science, social work, etc.—are evaluated separately from the academic disciplines, because they operate on different principles and literature bases than academic disciplines in the humanities, social sciences, and—particularly—the sciences. Harzing’s agenda was set forth in a joint article she did with Nancy J. Adler, a management professor at McGill University, Montreal, Canada. In this article Adler and Harzing (2009) argue that current systems of academically ranking institutions and individuals are dysfunctional and counterproductive. Moreover, due to institutional isomorphism, the same systems are being adopted everywhere, leading to the following situation: ‘‘Dominant institutional players form what is referred to as a well-organized field in which each player is influenced to adhere to similar, mutually reinforcing types of ranking and assessment behaviors’’ (p. 85). One way to reform such a system is through the introduction of what Adler and Harzing describe as ‘‘a new and influential field-level player— what has been labeled an institutional entrepreneur’’ (p. 90). Anne-Wil Harzing is such an entrepreneur. Adler and Harzing (2009, p. 90) point out that the field of citation analysis was monopolized for decades by the system developed by Eugene Garfield at the Institute for Scientific Information (ISI) now owned by Thomson Reuter Scientific. This reviewer (Bensman 2007a; Bensman 2007b) has shown that this system was developed on the basis of a sociometric model of science developed by Garfield in conjunction with Derek J. de Solla Price and Robert K. Merton, among others. It was a journal-oriented system fitted to the needs of biochemistry and molecular biology. The model is a cumulative advantage or success-breeds-success system best described by the negative binomial and leading to the dominance of a few scientists, institutions, journals, countries, etc. This reviewer

Donald J. Urquhart and the integration of science with librarianship: Part 2

Purpose – To analyze the historical significance of Donald J. Urquhart, who established the National Lending Library for Science and Technology (NLL) which later was merged into the British Library Lending Division (BLLD), now called the British Library Document Supply Centre (BLDSC). His significance will be considered from the perspective of the development of science as a whole as well as library and information science in particular.Design/methodology/approach – The paper presents a short history of the probabilistic revolution, particularly as it developed in Britain in the form of biometric statistics due to Darwins theory of evolution. It focuses on the overthrow of the normal paradigm, according to which frequency distributions in nature and society conform to the normal law of error. The paper discusses the importance of the Poisson distribution and its utilization in the construction of stochastic models that better describe reality. Here the focus is on the compound Poisson distribution in the...

Urquhart's Law: Probability and the Management of Scientific and Technical Journal Collections Part 3. The Law's Final Formulation and Implications for Library Systems

ABSTRACT This is the last part of an analysis of the law formulated by Donald J. Urquhart in respect to the use of scientific and technical (sci/tech) journals through either interlibrary loan or central document delivery. The first part discussed the genesis of this law as well as its statistical bases; the second dealt with the implications of the law for the development and management of the sci/tech journal collection of a central document delivery library. Part 3 concentrates on its consequences for all the libraries of a given library system. There is analyzed in this part the controversy over the validity of this law that caused Urquhart to formulate it in an explicit manner. Part 3 discusses studies at various libraries that have corroborated this law, postulating that this law forces a probabilistic re-conceptualization of the functioning of the sci/tech journal system. Throughout this part, there are noted the consequences of the law for such matters as sci/tech journal sales, resource sharing, document delivery, interlibrary loan, and the transition from individually held paper copies of journals to shared electronic databases.

Urquhart's Law: Probability and the Management of Scientific and Technical Journal Collections Part 1. The Law's Initial Formulation and Statistical Bases

ABSTRACT The topic of this paper is a law formulated by Donald J. Urquhart on the use of scientific and technical (sci/tech) journals through interlibrary loan and central document delivery. The paper will be published in three parts. Part 1 discusses the genesis of the law and the probabilistic theory on which it is based. A primary aim of this part is to teach librarians about the probability distributions underlying library use and how to identify these distributions through simple mathematical and graphical techniques.

Urquhart's law : Probability and the management of scientific and technical journal collections part 2. probability in the development and management of a central document delivery collection

ABSTRACT Part 1 of this three-part paper discussed the genesis of the law formulated by Donald J. Urquhart on the use of scientific and technical (sci/tech) journals through interlibrary loan and central document delivery. It concentrated on the study of such use conducted by Urquhart in preparation for the establishment of the National Lending Library for Science and Technology (NLL), which became the central document delivery library of Britain. The focus of Part 1 was on the statistical and probabilistic bases of this law. In Part 2 the emphasis shifts to how Urquhart utilized probability to develop and manage the NLLs sci/tech journal collection. Urquhart based his collection development and management policies on a high-loan core of journals, causing the stability of sci/tech journal use over time to become the main theoretical issue. Part 2 analyzes the controversy over this issue between Urquhart and his successor, Maurice B. Line.

Lotka's inverse square law of scientific productivity: Its methods and statistics

This brief communication analyzes the statistics and methods Lotka used to derive his inverse square law of scientific productivity from the standpoint of modern theory. It finds that he violated the norms of this theory by extremely truncating his data on the right. It also proves that Lotka himself played an important role in establishing the commonly used method of identifying power‐law behavior by the R2 fit to a regression line on a log‐log plot that modern theory considers unreliable by basing the derivation of his law on this very method.