Purpose: The "Norwegian model" has become widely used for assessment and resource allocation purposes. This paper investigates why this model has becomes so widespread and influential. Approach: A theoretica...Purpose: The "Norwegian model" has become widely used for assessment and resource allocation purposes. This paper investigates why this model has becomes so widespread and influential. Approach: A theoretical background is outlined in which the reduction of "uncertainty" is highlighted as a key feature of performance measurement systems. These theories are then drawn upon when revisiting previous studies of the Norwegian model, its use, and reactions to it, in Sweden.Findings: The empirical examples, which concern more formal use on the level of universities as well as responses from individual researchers, shows how particular parts—especially the "publication indicator"—are employed in Swedish academia. The discussion posits that the attractiveness of the Norwegian model largely can be explained by its ability to reduce complexity and uncertainty, even in fields where traditional bibliometric measurement is less applicable. Research limitations: The findings presented should be regarded as examples that can be used for discussion, but one should be careful to interpret these as representative for broader sentiments and trends.Implications: The sheer popularity of the Norwegian model, leading to its application in contexts for which it was not designed, can be seen as a major challenge for the future.Originality: This paper offers a novel perspective on the Norwegian model by focusing on its general "appeal", rather than on its design, use or(mis)-use.展开更多
Classification of bibliometric indicators is a fundamental issue in information science.Traditionally,the classification is based on subjective classification.This article presents an empirical study on the mathematic...Classification of bibliometric indicators is a fundamental issue in information science.Traditionally,the classification is based on subjective classification.This article presents an empirical study on the mathematics journals listed in JCR 2019 by using objective classification methods including cluster analysis,factor analysis,and principal component analysis to classify bibliometric indicators.Different classification results are compared and further interpreted,major finding are:the classification results of objective classification methods share similarities;objective classification helps better comprehend bibliometric indicators;objective classification should be used in combination with subjective classification;cluster analysis performs better in classifying bibliometric indicators than factor analysis and principal component analysis;not all the results of objective classification are meaningful;cluster of indicators has sufficient influence on subsequent evaluation and regression analysis.This study provides a new paradigm for journal classification and indicator analysis.展开更多
基金supported by the Swedish Foundation for the Social Sciences and Humanities(Grant No.SGO14-1153:1)
文摘Purpose: The "Norwegian model" has become widely used for assessment and resource allocation purposes. This paper investigates why this model has becomes so widespread and influential. Approach: A theoretical background is outlined in which the reduction of "uncertainty" is highlighted as a key feature of performance measurement systems. These theories are then drawn upon when revisiting previous studies of the Norwegian model, its use, and reactions to it, in Sweden.Findings: The empirical examples, which concern more formal use on the level of universities as well as responses from individual researchers, shows how particular parts—especially the "publication indicator"—are employed in Swedish academia. The discussion posits that the attractiveness of the Norwegian model largely can be explained by its ability to reduce complexity and uncertainty, even in fields where traditional bibliometric measurement is less applicable. Research limitations: The findings presented should be regarded as examples that can be used for discussion, but one should be careful to interpret these as representative for broader sentiments and trends.Implications: The sheer popularity of the Norwegian model, leading to its application in contexts for which it was not designed, can be seen as a major challenge for the future.Originality: This paper offers a novel perspective on the Norwegian model by focusing on its general "appeal", rather than on its design, use or(mis)-use.
文摘Classification of bibliometric indicators is a fundamental issue in information science.Traditionally,the classification is based on subjective classification.This article presents an empirical study on the mathematics journals listed in JCR 2019 by using objective classification methods including cluster analysis,factor analysis,and principal component analysis to classify bibliometric indicators.Different classification results are compared and further interpreted,major finding are:the classification results of objective classification methods share similarities;objective classification helps better comprehend bibliometric indicators;objective classification should be used in combination with subjective classification;cluster analysis performs better in classifying bibliometric indicators than factor analysis and principal component analysis;not all the results of objective classification are meaningful;cluster of indicators has sufficient influence on subsequent evaluation and regression analysis.This study provides a new paradigm for journal classification and indicator analysis.
