Search (9 results, page 1 of 1)

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Abstract

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.

Date

22. 6.2023 18:11:50

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Abstract

If communication in research and development is efficient, then the current cognitive situation in any specialty should fully reflect all available relevant information. Available evidence suggests that communication in R&D is not in that sense efficient, and a priori arguments seem to show that it could not be. But we try to show that the evidence and arguments are inconclusive, and that the question of effiency is an open one. It is also one which information science has an interest in pursuing

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Abstract

Wilson argues that the subject of a writing is indetermined, by which he means either it is impossible to say which of two descriptions is 'the' description of the subject of a writing or it is impossible to say if a writing has two subjects rather than one.

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Abstract

One knows one is in the presence of "theory" when fundamental questions of a "why" nature are asked. Too often it happens that those involved in the design of bibliographic information systems have no time for brooding. It is thus noteworthy when someone appears an the bibliographic scene who troubles to address, and pursue with philosophic rigor, fundamental questions about the way we organize information. Such a person is Patrick Wilson, formerly philosophy professor at the University of California, Los Angeles, and since 1965, an the faculty of the School of Library and Information Studies, University of California, Berkeley. Bibliographic control is the central concept of Wilson's book Two Kinds of Power. It is represented as a kind of power-a power over knowledge. That power is of two kinds: descriptive and exploitive. Descriptive power is the power to retrieve all writings that satisfy some "evaluatively neutral" description, for instance, all writings by Hobbes or all writings an the subject of eternat recurrence. Descriptive power is achieved insofar as the items in our bibliographic universe are fitted with descriptions and these descriptions are syndetically related. Exploitive power is a less-familiar concept, but it is more important since it can be used to explain why we attempt to order our bibliographic universe in the first place. Exploitive power is the power to obtain the best textual means to an end. Unlike the concept of descriptive power, that of exploitive power has a normative aspect to it. Someone possessing such power would understand the goal of all bibliographic activity; that is, he would understand the diversity of user purposes and the relativity of what is valuable; he would be omniscient both as a bibliographer and as a psychologist. Since exploitive power is ever out of reach, descriptive power is used as a substitute or approximation for it. How adequate this approximation is is the subject of Wilson's book. The particular chapter excerpted in this volume deals with the adequacy of subject access methods. Cutter's statement that one of the objects of a library catalog is to show what the library has an a given subject is generally accepted, as though it were obvious what "being an a given subject" means. It is far from obvious. Wilson challenges the underlying presumption that for any document a heading can be found that is coextensive with its subject. This presumption implies that there is such a thing as the (singular) subject of a document and that it can be identified. But, as Wilson Shows in his elaborate explication, the notion of "subject" is essentially indeterminate, with the consequence that we are limited in our attempts to achieve either descriptive or exploitive power.

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Abstract

Recently announced subject cataloging practices at the Library of Congress, calling for systematic duplication of entries at specific and generic levels, are in direct violation of the rule of exclusively specific entry, hitherto accepted by LC. It is argued that if the new practices are justified, consistency calls for their general application, which results in abandonment of the rule. But the new practices do not accomplish their ostensible goals, do not reveal more of the content of LC's collections, do introduce new inconveniences, do constitute a pointless enlargement of catalogs, and hence should be abandoned

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Abstract

Relevant information known to be available may go unused in research and development because of information overload or because its use is excluded by deliberate policy. Exclusion by policy shows that R&D is not, and does not aim at always being, efficient in the sense of fully reflecting all available relevant information. It may still be efficient relatice to chosen strategies of information use and non-use. Overload may be a sign of strategic error, or may be accepted as routine and normal

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Abstract

Statistics are essential to many areas of research and individual statistical techniques may change the ways in which problems are addressed as well as the types of problems that can be tackled. Hence, specific techniques may tend to generate high-impact findings within science. This article estimates the citation advantage of a technique by calculating the average citation rank of articles using it in the issue of the journal in which they were published. Applied to structural equation modeling (SEM) and four related techniques in 3 broad fields, the results show citation advantages that vary by technique and broad field. For example, SEM seems to be more influential in all broad fields than the 4 simpler methods, with one exception, and hence seems to be particularly worth adding to statistical curricula. In contrast, Pearson correlation apparently has the highest average impact in medicine but the least in psychology. In conclusion, the results suggest that the importance of a statistical technique may vary by discipline and that even simple techniques can help to generate high-impact research in some contexts.

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Abstract

Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with individual article quality scores. It exploits expert norm-referenced peer review scores from the UK Research Excellence Framework 2021 for 67,030+ journal articles in all fields 2014-2017/2018, split into 34 broadly field-based Units of Assessment (UoAs). Altmetrics correlated more strongly with research quality than previously found, although less strongly than raw and field normalized Scopus citation counts. Surprisingly, field normalizing citation counts can reduce their strength as a quality indicator for articles in a single field. For most UoAs, Mendeley reader counts are the best altmetric (e.g., three Spearman correlations with quality scores above 0.5), tweet counts are also a moderate strength indicator in eight UoAs (Spearman correlations with quality scores above 0.3), ahead of news (eight correlations above 0.3, but generally weaker), blogs (five correlations above 0.3), and Facebook (three correlations above 0.3) citations, at least in the United Kingdom. In general, altmetrics are the strongest indicators of research quality in the health and physical sciences and weakest in the arts and humanities.

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Abstract

Citation counts are widely used as indicators of research quality to support or replace human peer review and for lists of top cited papers, researchers, and institutions. Nevertheless, the relationship between citations and research quality is poorly evidenced. We report the first large-scale science-wide academic evaluation of the relationship between research quality and citations (field normalized citation counts), correlating them for 87,739 journal articles in 34 field-based UK Units of Assessment (UoA). The two correlate positively in all academic fields, from very weak (0.1) to strong (0.5), reflecting broadly linear relationships in all fields. We give the first evidence that the correlations are positive even across the arts and humanities. The patterns are similar for the field classification schemes of Scopus and Dimensions.ai, although varying for some individual subjects and therefore more uncertain for these. We also show for the first time that no field has a citation threshold beyond which all articles are excellent quality, so lists of top cited articles are not pure collections of excellence, and neither is any top citation percentile indicator. Thus, while appropriately field normalized citations associate positively with research quality in all fields, they never perfectly reflect it, even at high values.