《中国图书馆学报》(1994-2005年)核心著者的测评

依据发文量和被引量两个计量指标，利用综合指数法测评《中国图书馆学报》（1994-2005年）的核心著者。     

高职院校学生阅读现状调查分析与图书馆服务对策

文章在对广东省各种专业的近一千名高职学生问巷调查结果的基础上。认真分析了目前高职学生的阅读现状，并针对普遍存在的问题提出了提高学生阅读兴趣和阅读能力的设想。     

近六年《江西图书馆学刊》载文、引文及作者分析

以《江西图书馆学刊》1998～2003年载、引、被引及作情况为研究对象，分析了载的数量、栏目和所占页数，引的数量、来源、语种和年代，载被引情况以及作的单位分布和作数量，从而反映出该刊近六年的栽情况及学术影响。     

浅谈高等职业学院图书馆网络化建设--以广东科学技术职业学院图书馆为研讨实例

对高等职业学校图书馆网络化建设的必要性、特征等问题进行了分析和探讨，介绍了图书馆网络化建设的原则、方案，硬、软件平台组成及数据库等。     

论图书馆职业精神

文章论述了图书馆职业精神及其特征，探讨了图书馆职业精神的内涵，分析了构成图书馆职业精神的基本要素。     

高职学院图书馆用户研究

通过对高职学院图书馆用户群体分析，了解不同层次的读者对图书馆有何需求，以及用户与馆员之间存在的矛盾，找到这些矛盾的解决办法，达到提高图书馆服务质量和服务水平的目的。     

中国图书馆学专业教育层次化探讨

当前，图书馆学专业教育面临着专业萎缩、生源不足、学习动力不足等危机。针对这些问题．本文提出了进行中国图书馆学专业教育层次化改革的设想，同时提议教育部图书馆学学科指导委员会的作用，实施图书馆从业人员资格认证制度。     

涉农高职院校现代农业创业教育的实践探索——以温州科技职业学院为例

温州科技职业学院紧扣现代农业创业人才培养目标,改革教育机制,构建"训、研、创、产"一体化的创业人才培养体系,实施以"导师—项目—团队"为核心的"师导生创、师创生学、师生企协创"的创业人才培养路径,成效显著。在总结温州科技职业学院创业教育经验的基础上,提出了培养现代农业创业人才的三点策略建议:充分利用农科专业特点,培养现代农业创业人才;科研创新与创业教育互相促进,构筑创业实践体系;乡村振兴战略与创业人才培养相互支撑,促进地方农业产业经济发展。     

Could scientists use Altmetric.com scores to predict longer term citation counts?

Altmetrics from Altmetric.com are widely used by publishers and researchers to give earlier evidence of attention than citation counts. This article assesses whether Altmetric.com scores are reliable early indicators of likely future impact and whether they may also reflect non-scholarly impacts. A preliminary factor analysis suggests that the main altmetric indicator of scholarly impact is Mendeley reader counts, with weaker news, informational and social network discussion/promotion dimensions in some fields. Based on a regression analysis of Altmetric.com data from November 2015 and Scopus citation counts from October 2017 for articles in 30 narrow fields, only Mendeley reader counts are consistent predictors of future citation impact. Most other Altmetric.com scores can help predict future impact in some fields. Overall, the results confirm that early Altmetric.com scores can predict later citation counts, although less well than journal impact factors, and the optimal strategy is to consider both Altmetric.com scores and journal impact factors. Altmetric.com scores can also reflect dimensions of non-scholarly impact in some fields.     

Impact Factors and the Central Limit Theorem: Why citation averages are scale dependent

Citation averages, and Impact Factors (IFs) in particular, are sensitive to sample size. Here, we apply the Central Limit Theorem to IFs to understand their scale-dependent behavior. For a journal of n randomly selected papers from a population of all papers, we expect from the Theorem that its IF fluctuates around the population average μ, and spans a range of values proportional to $\sigma /\sqrt{n}$, where σ² is the variance of the population's citation distribution. The $1/\sqrt{n}$ dependence has profound implications for IF rankings: The larger a journal, the narrower the range around μ where its IF lies. IF rankings therefore allocate an unfair advantage to smaller journals in the high IF ranks, and to larger journals in the low IF ranks. As a result, we expect a scale-dependent stratification of journals in IF rankings, whereby small journals occupy the top, middle, and bottom ranks; mid-sized journals occupy the middle ranks; and very large journals have IFs that asymptotically approach μ. We obtain qualitative and quantitative confirmation of these predictions by analyzing (i) the complete set of 166,498 IF & journal-size data pairs in the 1997–2016 Journal Citation Reports of Clarivate Analytics, (ii) the top-cited portion of 276,000 physics papers published in 2014–2015, and (iii) the citation distributions of an arbitrarily sampled list of physics journals. We conclude that the Central Limit Theorem is a good predictor of the IF range of actual journals, while sustained deviations from its predictions are a mark of true, non-random, citation impact. IF rankings are thus misleading unless one compares like-sized journals or adjusts for these effects. We propose the Φ index, a rescaled IF that accounts for size effects, and which can be readily generalized to account also for different citation practices across research fields. Our methodology applies to other citation averages that are used to compare research fields, university departments or countries in various types of rankings.