A Probabilistic Model For The Distribution Of Authorships And A Measure Of The Degree Of Research Collaboration

The collaborative coefficient (CC), a measure that combines some of the merits of two earlier measures of research collaboration, is presented. This measure is used to compare the degrees of collaboration in the fields of engineering sciences, medical sciences, physical sciences, mathematical sciences, social sciences, and humanities. A theoretical model for the distribution of authorships is also developed. This model, the shifted Waring distribution, and 15 other discrete probability models are tested for goodness-of-fit against 96 data sets collected from the six fields listed above. The shifted inverse Gaussian-Poisson is found to be the best model. It is suggested that this model could be used in the estimation of the number of entries in an author index and in determining the maximum number of authors per paper to be included in an author index. A relationship is established between the parameters of this model and the collaborative coefficient

Determinants of the international influence of a R&D organisation: a bibliometric approach

Traditionally, studies on the influence and impact of knowledge-producing organisations have been addressed by means of strict economic analysis, stressing their economic impact to a local, regional or national extent. In the present study, an alternative methodology is put forward in order to evaluate the international scientific impact and influence of a knowledge-producing and -diffusing institution. We introduce a new methodology, based on scientometric and bibliometric tools, which complement traditional assessments by considering the influence of a R&D institution when looking at the scientific production undertaken and the recognition of its relevance by its international peer community. Focusing on the most prolific scientific areas of INESC Porto, and resorting to published scientific work recorded in the Science Citation Index (SCI), we show that INESC Porto has enlarged its international scientific network. The logit estimations demonstrate that the wide geographical influence of INESC Porto scientific research is a result not of its international positioning in terms of co-authorships, but rather a result of the quality of its scientific output.Impact and influence assessment methods; R&D Institutions; Bibliometrics, Scientometrics; knowledge network; INESC Porto

Can Synergy in Triple-Helix Relations be Quantified? A Review of the Development of the Triple-Helix Indicator

Triple-Helix arrangements of bi- and trilateral relations can be considered as adaptive eco-systems. During the last decade, we have further developed a Triple-Helix indicator of synergy as reduction of uncertainty in niches that can be shaped among three or more distributions. Reduction of uncertainty can be generated in correlations among distributions of relations, but this (next-order) effect can be counterbalanced by uncertainty generated in the relations. We first explain the indicator, and then review possible results when this indicator is applied to (i) co-author networks of academic, industrial, and governmental authors and (ii) synergies in the distributions of firms over geographical addresses, technological classes, and industrial-size classes for a number of nations. Co-variation is then considered as a measure of relationship. The balance between globalizing and localizing dynamics can be quantified. Too much synergy locally can also be considered as lock-in. Tendencies are different for the globalizing knowledge dynamics versus locally retaining wealth from knowledge in industrial innovations

Determinants of the international influence of a R&D organisation: a bibliometric approach

Traditionally, studies on the influence and impact of knowledge-producing organisations have been addressed by means of strict economic analysis, stressing their economic impact to a local, regional or national extent. In the present study, an alternative methodology is put forward in order to evaluate the international scientific impact and influence of a knowledge-producing and -diffusing institution. We introduce a new methodology, based on scientometric and bibliometric tools, which complement traditional assessments by considering the influence of a R&D institution when looking at the scientific production undertaken and the recognition of its relevance by its international peer community. Focusing on the most prolific scientific areas of INESC Porto, and resorting to published scientific work recorded in the Science Citation Index (SCI), we show that INESC Porto has enlarged its international scientific network. The logit estimations demonstrate that the wide geographical influence of INESC Porto scientific research is a result not of its international positioning in terms of co-authorships, but rather a result of the quality of its scientific output.Impact and influence assessment methods; R&D Institutions; Bibliometrics, Scientometrics; knowledge network; INESC Porto

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship

Gender-Based Homophily in Research: A Large-Scale Study of Man-Woman Collaboration

We examined the male-female collaboration practices of all internationally visible Polish university professors (N = 25,463) based on their Scopus-indexed publications from 2009-2018 (158,743 journal articles). We merged a national registry of 99,935 scientists (with full administrative and biographical data) with the Scopus publication database, using probabilistic and deterministic record linkage. Our unique biographical, administrative, publication, and citation database (The Observatory of Polish Science) included all professors with at least a doctoral degree employed in 85 research-involved universities. We determined what we term an individual publication portfolio for every professor, and we examined the respective impacts of biological age, academic position, academic discipline, average journal prestige, and type of institution on the same-sex collaboration ratio. The gender homophily principle (publishing predominantly with scientists of the same sex) was found to apply to male scientists - but not to females. The majority of male scientists collaborate solely with males; most female scientists, in contrast, do not collaborate with females at all. Across all age groups studied, all-female collaboration is marginal, while all-male collaboration is pervasive. Gender homophily in research-intensive institutions proved stronger for males than for females. Finally, we used a multi-dimensional fractional logit regression model to estimate the impact of gender and other individual-level and institutional-level independent variables on gender homophily in research collaboration.Comment: 46 pages, 15 tables, 8 figure

An empirical review of the different variants of the Probabilistic Affinity Index as applied to scientific collaboration

Responsible indicators are crucial for research assessment and monitoring. Transparency and accuracy of indicators are required to make research assessment fair and ensure reproducibility. However, sometimes it is difficult to conduct or replicate studies based on indicators due to the lack of transparency in conceptualization and operationalization. In this paper, we review the different variants of the Probabilistic Affinity Index (PAI), considering both the conceptual and empirical underpinnings. We begin with a review of the historical development of the indicator and the different alternatives proposed. To demonstrate the utility of the indicator, we demonstrate the application of PAI to identifying preferred partners in scientific collaboration. A streamlined procedure is provided, to demonstrate the variations and appropriate calculations. We then compare the results of implementation for five specific countries involved in international scientific collaboration. Despite the different proposals on its calculation, we do not observe large differences between the PAI variants, particularly with respect to country size. As with any indicator, the selection of a particular variant is dependent on the research question. To facilitate appropriate use, we provide recommendations for the use of the indicator given specific contexts.Comment: 35 pages, 3 figures, 5 table