Search (1374 results, page 1 of 69)

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a

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Abstract

The paper reports a longitudinal analysis of the topical and methodological development of Library and Information Science (LIS). Its focus is on the effects of researchers' disciplines on these developments. The study extends an earlier cross-sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706-1722) by a coordinated dataset representing a content analysis of articles published in 31 scholarly LIS journals in 1995, 2005, and 2015. It is novel in its coverage of authors' disciplines, topical and methodological aspects in a coordinated dataset spanning two decades thus allowing trend analysis. The findings include a shrinking trend in the share of LIS from 67 to 36% while Computer Science, and Business and Economics increase their share from 9 and 6% to 21 and 16%, respectively. The earlier cross-sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706-1722) for the year 2015 identified three topical clusters of LIS research, focusing on topical subfields, methodologies, and contributing disciplines. Correspondence analysis confirms their existence already in 1995 and traces their development through the decades. The contributing disciplines infuse their concepts, research questions, and approaches to LIS and may also subsume vital parts of LIS in their own structures of knowledge production.

Date

22. 6.2023 18:15:06

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a

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Abstract

This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.

Type

a

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Abstract

Detecting emerging research topics is essential, not only for research agencies but also for individual researchers. Previous studies have created various bibliographic indicators for the identification of emerging research topics. However, as indicated by Rotolo et al. (Research Policy 44, 1827-1843, 2015), the most serious problems are the lack of an acknowledged definition of emergence and incomplete elaboration of the linkages between the definitions that are used and the indicators that are created. With these issues in mind, this study first adjusts the definition of an emerging technology that Rotolo et al. (2015) have proposed to accommodate the analysis. Next, a set of criteria for the identification of emerging topics is proposed according to the adjusted definition and attributes of emergence. Using two sets of parameter values, several emerging research topics are identified. Finally, evaluation tests are conducted by demonstration of the proposed approach and comparison with previous studies. The strength of the present methodology lies in the fact that it is fully transparent, straightforward, and flexible.

Type

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Abstract

This year marks 350 years since the inaugural publications of both the Journal des Sçavans and the Philosophical Transactions, first published in 1665 and considered the birth of the peer-reviewed journal article. This form of scholarly communication has not only remained the dominant model for disseminating new knowledge (particularly for science and medicine), but has also increased substantially in volume. Derek de Solla Price - the "father of scientometrics" (Merton and Garfield, 1986, p. vii) - was the first to document the exponential increase in scientific journals and showed that "scientists have always felt themselves to be awash in a sea of the scientific literature" (Price, 1963, p. 15), as, for example, expressed at the 1948 Royal Society's Scientific Information Conference: Not for the first time in history, but more acutely than ever before, there was a fear that scientists would be overwhelmed, that they would be no longer able to control the vast amounts of potentially relevant material that were pouring forth from the world's presses, that science itself was under threat (Bawden and Robinson, 2008, p. 183).
One of the solutions to help scientists filter the most relevant publications and, thus, to stay current on developments in their fields during the transition from "little science" to "big science", was the introduction of citation indexing as a Wellsian "World Brain" (Garfield, 1964) of scientific information: It is too much to expect a research worker to spend an inordinate amount of time searching for the bibliographic descendants of antecedent papers. It would not be excessive to demand that the thorough scholar check all papers that have cited or criticized such papers, if they could be located quickly. The citation index makes this check practicable (Garfield, 1955, p. 108). In retrospective, citation indexing can be perceived as a pre-social web version of crowdsourcing, as it is based on the concept that the community of citing authors outperforms indexers in highlighting cognitive links between papers, particularly on the level of specific ideas and concepts (Garfield, 1983). Over the last 50 years, citation analysis and more generally, bibliometric methods, have developed from information retrieval tools to research evaluation metrics, where they are presumed to make scientific funding more efficient and effective (Moed, 2006). However, the dominance of bibliometric indicators in research evaluation has also led to significant goal displacement (Merton, 1957) and the oversimplification of notions of "research productivity" and "scientific quality", creating adverse effects such as salami publishing, honorary authorships, citation cartels, and misuse of indicators (Binswanger, 2015; Cronin and Sugimoto, 2014; Frey and Osterloh, 2006; Haustein and Larivière, 2015; Weingart, 2005).
Furthermore, the rise of the web, and subsequently, the social web, has challenged the quasi-monopolistic status of the journal as the main form of scholarly communication and citation indices as the primary assessment mechanisms. Scientific communication is becoming more open, transparent, and diverse: publications are increasingly open access; manuscripts, presentations, code, and data are shared online; research ideas and results are discussed and criticized openly on blogs; and new peer review experiments, with open post publication assessment by anonymous or non-anonymous referees, are underway. The diversification of scholarly production and assessment, paired with the increasing speed of the communication process, leads to an increased information overload (Bawden and Robinson, 2008), demanding new filters. The concept of altmetrics, short for alternative (to citation) metrics, was created out of an attempt to provide a filter (Priem et al., 2010) and to steer against the oversimplification of the measurement of scientific success solely on the basis of number of journal articles published and citations received, by considering a wider range of research outputs and metrics (Piwowar, 2013). Although the term altmetrics was introduced in a tweet in 2010 (Priem, 2010), the idea of capturing traces - "polymorphous mentioning" (Cronin et al., 1998, p. 1320) - of scholars and their documents on the web to measure "impact" of science in a broader manner than citations was introduced years before, largely in the context of webometrics (Almind and Ingwersen, 1997; Thelwall et al., 2005):
There will soon be a critical mass of web-based digital objects and usage statistics on which to model scholars' communication behaviors - publishing, posting, blogging, scanning, reading, downloading, glossing, linking, citing, recommending, acknowledging - and with which to track their scholarly influence and impact, broadly conceived and broadly felt (Cronin, 2005, p. 196). A decade after Cronin's prediction and five years after the coining of altmetrics, the time seems ripe to reflect upon the role of social media in scholarly communication. This Special Issue does so by providing an overview of current research on the indicators and metrics grouped under the umbrella term of altmetrics, on their relationships with traditional indicators of scientific activity, and on the uses that are made of the various social media platforms - on which these indicators are based - by scientists of various disciplines.

Date

20. 1.2015 18:30:22

Type

a

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Abstract

State-of-the-Art Reports are enriched information compilations that are generated by quantitative and qualitative fact collections on a well defined discipline. On the basis of experience with an informative documentation on `Nutrition and Society' it will be outlined what kind of information can be distilled from bibliographical data bases and how they can be analysed. The general conclusion of this paper is that aggregated information on bibliographical material must be interpreted with respect to the special patterns, and often should be approached with multiple methods and be disaggregated or differentiated to get a real, enriched view of the disciplines under consideration.

Source

Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al

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Abstract

Purpose The introduction of "altmetrics" as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields. Design/methodology/approach The authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013). Findings There are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on "exchange rates (ERs)" for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results. Originality/value These findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition.

Date

20. 1.2015 18:30:22

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Abstract

Co-word analysis is a technique for detecting the knowledge structure of scientific literature and mapping the dynamics in a research field. It is used to count the co-occurrences of term pairs, compute the strength between term pairs, and map the research field by inserting terms and their linkages into a graphical structure according to the strength values. In previous co-word studies, there are two indexes used to measure the strength between term pairs in order to identify the major areas in a research field - the inclusion index (I) and the equivalence index (E). This study will conduct two co-word analysis experiments using the two indexes, respectively, and compare the results from the two experiments. The results show, due to the difference in their computation, index I is more likely to identify general subject areas in a research field while index E is more likely to identify subject areas at more specific levels

Source

Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al

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Abstract

To this day the analysis of citations has been aimed mainly to the exploration of different ways to count them, such as the total count, the h-index or the s-index, in order to quantify a researcher's overall contribution and impact. In this work we show how the consideration of the structured metadata that accompany citations, such as the publication outlet in which they have appeared, can lead to a considerably more insightful understanding of the ways in which a researcher has impacted the work of others.

Source

Semantic keyword-based search on structured data sources: COST Action IC1302. Second International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8-9, 2016, Revised Selected Papers. Eds.: A. Calì, A. et al

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Abstract

A citation analysis examined the 28 best articles published in JASIS from 1969-1996. Best articles tend to single-authored works twice as long as the avergae article published in JASIS. They are cited and self-cited much more often than the average article. The greatest source of references made to the best articles is from JASIS itself. The top 5 best papers focus largely on information retrieval and online searching

Content

Top by numbers of citations: (1) Saracevic, T. et al.: A study of information seeking and retrieving I-III (1988); (2) Bates, M.: Information search tactics (1979); (3) Cooper, W.S.: On selecting a measure of retrieval effectiveness (1973); (4) Marcus, R.S.: A experimental comparison of the effectiveness of computers and humans as search intermediaries (1983); (4) Fidel, R.: Online searching styles (1984)

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Abstract

Using Web of Science data, portfolio analysis in terms of journal coverage can be projected onto a base map for units of analysis such as countries, cities, universities, and firms. The units of analysis under study can be compared statistically across the 10,000+ journals. The interdisciplinarity of the portfolios is measured using Rao-Stirling diversity or Zhang et?al.'s improved measure 2D3. At the country level we find regional differentiation (e.g., Latin American or Asian countries), but also a major divide between advanced and less-developed countries. Israel and Israeli cities outperform other nations and cities in terms of diversity. Universities appear to be specifically related to firms when a number of these units are exploratively compared. The instrument is relatively simple and straightforward, and one can generalize the application to any document set retrieved from the Web of Science (WoS). Further instruction is provided online at http://www.leydesdorff.net/portfolio.

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Abstract

We prove that Ochiai similarity of the co-occurrence matrix is equal to cosine similarity in the underlying occurrence matrix. Neither the cosine nor the Pearson correlation should be used for the normalization of co-occurrence matrices because the similarity is then normalized twice, and therefore overestimated; the Ochiai coefficient can be used instead. Results are shown using a small matrix (5 cases, 4 variables) for didactic reasons, and also Ahlgren et?al.'s (2003) co-occurrence matrix of 24 authors in library and information sciences. The overestimation is shown numerically and will be illustrated using multidimensional scaling and cluster dendograms. If the occurrence matrix is not available (such as in internet research or author cocitation analysis) using Ochiai for the normalization is preferable to using the cosine.

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Abstract

Research evaluation is increasingly popular and important among research funding bodies and science policy makers. Various indicators have been proposed to evaluate the standing of individual scientists, institutions, journals, or countries. A simple and popular one among the indicators is the h-index, the Hirsch index (Hirsch 2005), which is an indicator for lifetime achievement of a scholar. Several other indicators have been proposed to complement or balance the h-index. However, these indicators have no conception of aging. The AR-index (Jin et al. 2007) incorporates aging but divides the received citation counts by the raw age of the publication. Consequently, the decay of a publication is very steep and insensitive to disciplinary differences. In addition, we believe that a publication becomes outdated only when it is no longer cited, not because of its age. Finally, all indicators treat citations as equally material when one might reasonably think that a citation from a heavily cited publication should weigh more than a citation froma non-cited or little-cited publication.We propose a new indicator, the Discounted Cumulated Impact (DCI) index, which devalues old citations in a smooth way. It rewards an author for receiving new citations even if the publication is old. Further, it allows weighting of the citations by the citation weight of the citing publication. DCI can be used to calculate research performance on the basis of the h-core of a scholar or any other publication data.

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Abstract

In a recently published PNAS paper, Radicchi, Fortunato, and Castellano (2008) propose the relative indicator cf as an unbiased indicator for citation performance across disciplines (fields, subject areas). To calculate cf, the citation rate for a single paper is divided by the average number of citations for all papers in the discipline in which the single paper has been categorized. cf values are said to lead to a universality of discipline-specific citation distributions. Using a comprehensive dataset of an evaluation study on Angewandte Chemie International Edition (AC-IE), we tested the advantage of using this indicator in practical application at the micro level, as compared with (1) simple citation rates, and (2) z-scores, which have been used in psychological testing for many years for normalization of test scores. To calculate z-scores, the mean number of citations of the papers within a discipline is subtracted from the citation rate of a single paper, and the difference is then divided by the citations' standard deviation for a discipline. Our results indicate that z-scores are better suited than cf values to produce universality of discipline-specific citation distributions.

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Abstract

This study is a follow-up to a published Correspondence Factorial Analysis (CFA) of a dataset of over 6 million bibliometric entries (Doré et al. JASIS, 47(8), 588-602,1996), which compared the publication output patterns of 48 countries in 18 disciplines over a 12-year period (1981-1992). It analyzes by methods suitable for investigating short time series how these output patterns evolved over the 12-year span. Three types of approach are described. (1) the chi**2 distances of the publication output patterns from the center of gravity of the multidimensional system-which represents an average world pattern-were calculated for each country and for each year. We noted whether the patterns moved toward or away from the center with time; (2) individual annual output patterns were introduced as supplementary variables into an existing global overview covering the whole time-span [CFA map of (countries x disciplines)]. We observed how these patterns moved about within the map year by year; (3) the matrix (disciplines x time) was analyzed by CFA to derive time trends for each country. CFA revealed the "inner clocks" governing publication trends. The time scale that best fitted the data was not a linear but an elastic scale. Although different countries laid emphasis on publication in different disciplines, the overall tendency was toward greater uniformity in publication patterns with time

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Abstract

In the study of growth dynamics of artificial and natural systems, the scaling properties of fluctuations can exhibit information an the underlying processes responsible for the observed macroscopic behavior according to H.E. Stanley and colleagues (Lee, Amaral, Canning, Meyer, & Stanley, 1998; Plerou, Amaral, Gopikrishnan, Meyer, & Stanley, 1999; Stanley et al., 1996). With such an approach, they examined the growth dynamics of firms, of national economies, and of university research fundings and paper output. We investigated the scaling properties of journal output and impact according to the Journal Citation Reports (JCR; ISI, Philadelphia, PA) and find distributions of paper output and of citations near to lognormality. Growth rate distributions are near to Laplace "tents," however with a better fit to Subbotin distributions. The width of fluctuations decays with size according to a power law. The form of growth rate distributions seems not to depend an journal size, and conditional probability densities of the growth rates can thus be scaled onto one graph. To some extent even quantitatively, all our results are in agreement with the observations of Stanley and others. Further on, a Matthew effect of journal citations is confirmed. If journals "behave" like business firms, a better understanding of Bradford's Law as a result of competition among publishing houses, journals, and topics suggests itself.

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Abstract

In this paper we analyze a major part of the research output of the Networked Knowledge Organization Systems (NKOS) community in the period 2000 to 2015 from a network analytical perspective. We fo- cus on the paper output presented at the European NKOS workshops in the last 15 years. Our open dataset, the "NKOS bibliography", includes 14 workshop agendas (ECDL 2000-2010, TPDL 2011-2015) and 4 special issues on NKOS (2001, 2004, 2006 and 2015) which cover 171 papers with 218 distinct authors in total. A focus of the analysis is the visualization of co-authorship networks in this interdisciplinary eld. We used standard network analytic measures like degree and betweenness centrality to de- scribe the co-authorship distribution in our NKOS dataset. We can see in our dataset that 15% (with degree=0) of authors had no co-authorship with others and 53% of them had a maximum of 3 cooperations with other authors. 32% had at least 4 co-authors for all of their papers. The NKOS co-author network in the "NKOS bibliography" is a typical co- authorship network with one relatively large component, many smaller components and many isolated co-authorships or triples.

Source

Proceedings of the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) co-located with the 20th International Conference on Theory and Practice of Digital Libraries 2016 (TPDL 2016), Hannover, Germany, September 9, 2016. Edi. by Philipp Mayr et al. [http://ceur-ws.org/Vol-1676/=urn:nbn:de:0074-1676-5]

Type

a

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Abstract

Purpose This paper analyses the research in Library and Information Science (LIS) and reports on (1) the status of LIS research in 2015 and (2) on the evolution of LIS research longitudinally from 1965 to 2015. Design/methodology/approach The study employs a quantitative intellectual content analysis of articles published in 30+ scholarly LIS journals, following the design by Tuomaala et al. (2014). In the content analysis, we classify articles along eight dimensions covering topical content and methodology. Findings The topical findings indicate that the earlier strong LIS emphasis on L&I services has declined notably, while scientific and professional communication has become the most popular topic. Information storage and retrieval has given up its earlier strong position towards the end of the years analyzed. Individuals are increasingly the units of observation. End-user's and developer's viewpoints have strengthened at the cost of intermediaries' viewpoint. LIS research is methodologically increasingly scattered since survey, scientometric methods, experiment, case studies and qualitative studies have all gained in popularity. Consequently, LIS may have become more versatile in the analysis of its research objects during the years analyzed. Originality/value Among quantitative intellectual content analyses of LIS research, the study is unique in its scope: length of analysis period (50 years), width (8 dimensions covering topical content and methodology) and depth (the annual batch of 30+ scholarly journals).

Type

a

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Abstract

If you are an academic researcher but did not earn (yet) your Nobel prize or your retirement, it is unlikely you never heard about research metrics. These metrics aim at quantifying various aspects of the research process, at the level of individual researchers (e.g. h-index, altmetrics), scientific journals (e.g. impact factors) or entire universities/ countries (e.g. rankings). Although such "measurements" have existed in a simple form for a long time, their widespread calculation was enabled by the advent of the digital era (large amount of data available worldwide in a computer-compatible format). And in this new era, what becomes technically possible will be done, and what is done and appears to simplify our lives will be used. As a result, a rapidly growing number of statistics-based numerical indices are nowadays fed into decisionmaking processes. This is true in nearly all aspects of society (politics, economy, education and private life), and in particular in research, where metrics play an increasingly important role in determining positions, funding, awards, research programs, career choices, reputations, etc.

Content

Inhalt: Metrics in Research - For better or worse? / Jozica Dolenc, Philippe Hünenberger Oliver Renn - A brief visual history of research metrics / Oliver Renn, Jozica Dolenc, Joachim Schnabl - Bibliometry: The wizard of O's / Philippe Hünenberger - The grip of bibliometrics - A student perspective / Matthias Tinzl - Honesty and transparency to taxpayers is the long-term fundament for stable university funding / Wendelin J. Stark - Beyond metrics: Managing the performance of your work / Charlie Rapple - Scientific profiling instead of bibliometrics: Key performance indicators of the future / Rafael Ball - More knowledge, less numbers / Carl Philipp Rosenau - Do we really need BIBLIO-metrics to evaluate individual researchers? / Rüdiger Mutz - Using research metrics responsibly and effectively as a researcher / Peter I. Darroch, Lisa H. Colledge - Metrics in research: More (valuable) questions than answers / Urs Hugentobler - Publication of research results: Use and abuse / Wilfred F. van Gunsteren - Wanted: Transparent algorithms, interpretation skills, common sense / Eva E. Wille - Impact factors, the h-index, and citation hype - Metrics in research from the point of view of a journal editor / Renato Zenobi - Rashomon or metrics in a publisher's world / Gabriella Karger - The impact factor and I: A love-hate relationship / Jean-Christophe Leroux - Personal experiences bringing altmetrics to the academic market / Ben McLeish - Fatally attracted by numbers? / Oliver Renn - On computable numbers / Gerd Folkers, Laura Folkers - ScienceMatters - Single observation science publishing and linking observations to create an internet of science / Lawrence Rajendran.

Editor

Hünenberger, P. et al.

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Abstract

Digital libraries such as the NASA Astrophysics Data System (Kurtz et al., 2005) permit the easy accumulation of a new type of bibliometric measure, the number of electronic accesses ("reads") of individual articles. We explore various aspects of this new measure. We examine the obsolescence function as measured by actual reads and show that it can be weIl fit by the sum of four exponentials with very different time constants. We compare the obsolescence function as measured by readership with the obsolescence function as measured by citations. We find that the citation function is proportional to the sum of two of the components of the readership function. This proves that the normative theory of citation is true in the mean. We further examine in detail the similarities and differences among the citation rate, the readership rate, and the total citations for individual articles, and discuss some of the causes. Using the number of reads as a bibliometric measure for individuals, we introduce the read-cite diagram to provide a two-dimensional view of an individual's scientific productivity. We develop a simple model to account for an individual's reads and cites and use it to show that the position of a person in the read-cite diagram is a function of age, innate productivity, and work history. We show the age biases of both reads and cites and develop two new bibliometric measures which have substantially less age blas than citations: SumProd, a weighted sum of total citations and the readership rate, intended to show the total productivity of an individual; and Read10, the readership rate for articles published in the last 10 years, intended to show an individual's current productivity. We also discuss the effect of normalization (dividing by the number of authors an a paper) an these statistics. We apply SumProd and Read10 using new, nonparametric techniques to compare the quality of different astronomical research organizations.

Type

a