Purpose: Study how economic parameters affect positions in the Academic Ranking of World Universities' top 500 published by the Shanghai Jiao Tong University Graduate School of Education in countries/regions with ...Purpose: Study how economic parameters affect positions in the Academic Ranking of World Universities' top 500 published by the Shanghai Jiao Tong University Graduate School of Education in countries/regions with listed higher education institutions. Design/methodology/approach: The methodology used capitalises on the multi-variate characteristics of the data analysed. The multi-colinearity problem posed is solved by running principal components prior to regression analysis, using both classical(OLS) and robust(Huber and Tukey) methods. Findings: Our results revealed that countries/regions with long ranking traditions are highly competitive. Findings also showed that some countries/regions such as Germany, United Kingdom, Canada, and Italy, had a larger number of universities in the top positions than predicted by the regression model. In contrast, for Japan, a country where social and economic performance is high, the number of ARWU universities projected by the model was much larger than the actual figure. In much the same vein, countries/regions that invest heavily in education, such as Japan and Denmark, had lower than expected results.Research limitations: Using data from only one ranking is a limitation of this study, but the methodology used could be useful to other global rankings. Practical implications: The results provide good insights for policy makers. They indicate the existence of a relationship between research output and the number of universities per million inhabitants. Countries/regions, which have historically prioritised higher education, exhibited highest values for indicators that compose the rankings methodology; furthermore,minimum increase in welfare indicators could exhibited significant rises in the presence of their universities on the rankings.Originality/value: This study is well defined and the result answers important questions about characteristics of countries/regions and their higher education system.展开更多
通过分析和比较国内外一流高校研究成果被Web of Science核心合集收录的情况和学科分布情况以及这些研究成果的Altmetric.com覆盖率,揭示国内外一流高校研究成果Altmetric.com覆盖率的差异及原因,为提高国内“双一流”建设高校的社会网...通过分析和比较国内外一流高校研究成果被Web of Science核心合集收录的情况和学科分布情况以及这些研究成果的Altmetric.com覆盖率,揭示国内外一流高校研究成果Altmetric.com覆盖率的差异及原因,为提高国内“双一流”建设高校的社会网络影响力提供参考。选择40所国内外学术排名靠前的高校为样本机构,检索到共358 781条被Web of Science收录的2021年研究文献。利用Python语言编程访问Altmetric API,获取这些文献的Altmetrics数据,并在此基础上对国内外及学科间研究文献的Altmetric.com覆盖率进行比较研究。研究发现国内外一流高校研究成果的Altmetric.com覆盖率已经达到相当的份额,但存在较大的国别差异、学科差异和社交网络媒体差异。因此,Altmetric关注度分数作为高校科研影响力计量评价指标的潜力仍有待挖掘。展开更多
通过比较软科世界大学学术排名(Academic Ranking of World Universities,ARWU)、美国新闻与世界报道最好大学排名(US News&World Report Global Universities Rankings,US News)、夸夸雷利·西蒙兹世界大学排名(Quacquarelli S...通过比较软科世界大学学术排名(Academic Ranking of World Universities,ARWU)、美国新闻与世界报道最好大学排名(US News&World Report Global Universities Rankings,US News)、夸夸雷利·西蒙兹世界大学排名(Quacquarelli Symonds World University Ranking,QS)、泰晤士高等教育世界大学排名(Times Higher Educatioin World University Rankings,THE)学科评价体系特点,研究学科排名相关指标及权重,分析我国高等院校药学学科的世界排名和指标差距,提出应重视高水平科研成果的产出、加强人才培养质量、促进国际交流与科研合作、注重学科声誉的提升,以期加快我国药学学科的建设。展开更多
选择56所国内外学术排名靠前的大学为样本机构,以Web of Science核心合集为数据源,检索到样本机构2021年研究文献共469347篇,利用Python语言编程访问Altmetric.com,获取这些文献的替代计量学数据,并在此基础上进行统计分析。首先,比较...选择56所国内外学术排名靠前的大学为样本机构,以Web of Science核心合集为数据源,检索到样本机构2021年研究文献共469347篇,利用Python语言编程访问Altmetric.com,获取这些文献的替代计量学数据,并在此基础上进行统计分析。首先,比较国内外一流大学论文产出、引用和替代计量学指标分数的现状及相关性,探讨国内外一流大学在研究论文产出、学术影响力和社会影响力等方面的差异。其次,分析国内外一流大学研究论文的替代计量学指标分数与各大学排名系统得分之间的相关性。最后,探讨将替代计量学指标作为大学科研影响力评价指标的必要性和可行性,为“双一流”高校建设提供参考。研究发现:国内“双一流”建设高校在研究产出和论文引用情况方面与国外一流大学基本类似,但其替代计量学指标分数显著低于国外大学;大学的替代计量学指标分数与其在大学排名系统中的大多数指标分数之间存在显著的相关性,能够作为大学排名系统评价标准和方法的有益补充。展开更多
讨论了近年来出现的世界大学学术表现排名(University Ranking by Academic Performance,URAP)的主要特点,对比了2016年度我国内地进入URAP、THE、ARWU和QS等世界大学排行榜的入围院校,运用SPSS统计软件,研究了URAP排名与BCUR(中国最好...讨论了近年来出现的世界大学学术表现排名(University Ranking by Academic Performance,URAP)的主要特点,对比了2016年度我国内地进入URAP、THE、ARWU和QS等世界大学排行榜的入围院校,运用SPSS统计软件,研究了URAP排名与BCUR(中国最好大学排名)之间的相关程度。结果表明:URAP排名与BCUR(中国最好大学排名)之间存在高度显著的正相关关系,这两个较新的排行榜,值得我国高校给予更多的关注。展开更多
基金funded by CAPES (Coordinacao de Aperfeicoamento do Ensino) grant N. BEX 8354/13-8 awarded to Esteban Fernández Tuesta
文摘Purpose: Study how economic parameters affect positions in the Academic Ranking of World Universities' top 500 published by the Shanghai Jiao Tong University Graduate School of Education in countries/regions with listed higher education institutions. Design/methodology/approach: The methodology used capitalises on the multi-variate characteristics of the data analysed. The multi-colinearity problem posed is solved by running principal components prior to regression analysis, using both classical(OLS) and robust(Huber and Tukey) methods. Findings: Our results revealed that countries/regions with long ranking traditions are highly competitive. Findings also showed that some countries/regions such as Germany, United Kingdom, Canada, and Italy, had a larger number of universities in the top positions than predicted by the regression model. In contrast, for Japan, a country where social and economic performance is high, the number of ARWU universities projected by the model was much larger than the actual figure. In much the same vein, countries/regions that invest heavily in education, such as Japan and Denmark, had lower than expected results.Research limitations: Using data from only one ranking is a limitation of this study, but the methodology used could be useful to other global rankings. Practical implications: The results provide good insights for policy makers. They indicate the existence of a relationship between research output and the number of universities per million inhabitants. Countries/regions, which have historically prioritised higher education, exhibited highest values for indicators that compose the rankings methodology; furthermore,minimum increase in welfare indicators could exhibited significant rises in the presence of their universities on the rankings.Originality/value: This study is well defined and the result answers important questions about characteristics of countries/regions and their higher education system.
文摘通过分析和比较国内外一流高校研究成果被Web of Science核心合集收录的情况和学科分布情况以及这些研究成果的Altmetric.com覆盖率,揭示国内外一流高校研究成果Altmetric.com覆盖率的差异及原因,为提高国内“双一流”建设高校的社会网络影响力提供参考。选择40所国内外学术排名靠前的高校为样本机构,检索到共358 781条被Web of Science收录的2021年研究文献。利用Python语言编程访问Altmetric API,获取这些文献的Altmetrics数据,并在此基础上对国内外及学科间研究文献的Altmetric.com覆盖率进行比较研究。研究发现国内外一流高校研究成果的Altmetric.com覆盖率已经达到相当的份额,但存在较大的国别差异、学科差异和社交网络媒体差异。因此,Altmetric关注度分数作为高校科研影响力计量评价指标的潜力仍有待挖掘。
文摘通过比较软科世界大学学术排名(Academic Ranking of World Universities,ARWU)、美国新闻与世界报道最好大学排名(US News&World Report Global Universities Rankings,US News)、夸夸雷利·西蒙兹世界大学排名(Quacquarelli Symonds World University Ranking,QS)、泰晤士高等教育世界大学排名(Times Higher Educatioin World University Rankings,THE)学科评价体系特点,研究学科排名相关指标及权重,分析我国高等院校药学学科的世界排名和指标差距,提出应重视高水平科研成果的产出、加强人才培养质量、促进国际交流与科研合作、注重学科声誉的提升,以期加快我国药学学科的建设。
文摘选择56所国内外学术排名靠前的大学为样本机构,以Web of Science核心合集为数据源,检索到样本机构2021年研究文献共469347篇,利用Python语言编程访问Altmetric.com,获取这些文献的替代计量学数据,并在此基础上进行统计分析。首先,比较国内外一流大学论文产出、引用和替代计量学指标分数的现状及相关性,探讨国内外一流大学在研究论文产出、学术影响力和社会影响力等方面的差异。其次,分析国内外一流大学研究论文的替代计量学指标分数与各大学排名系统得分之间的相关性。最后,探讨将替代计量学指标作为大学科研影响力评价指标的必要性和可行性,为“双一流”高校建设提供参考。研究发现:国内“双一流”建设高校在研究产出和论文引用情况方面与国外一流大学基本类似,但其替代计量学指标分数显著低于国外大学;大学的替代计量学指标分数与其在大学排名系统中的大多数指标分数之间存在显著的相关性,能够作为大学排名系统评价标准和方法的有益补充。
文摘讨论了近年来出现的世界大学学术表现排名(University Ranking by Academic Performance,URAP)的主要特点,对比了2016年度我国内地进入URAP、THE、ARWU和QS等世界大学排行榜的入围院校,运用SPSS统计软件,研究了URAP排名与BCUR(中国最好大学排名)之间的相关程度。结果表明:URAP排名与BCUR(中国最好大学排名)之间存在高度显著的正相关关系,这两个较新的排行榜,值得我国高校给予更多的关注。
