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Metadata Characteristics as Predictors for Editor Selectivity in a CurrentAwareness Service

机译:元数据特征作为CurrentAwareness服务中编辑者选择性的预测因素

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摘要

RePEc is a large digital library for the economics community. "NEP: New Economics Papers" is a current awarenessrnservice for recent additions to RePEc. The service is run by volunteer editors. They filter new additions to RePEc intornsubject-specific reports. The intended purpose of this current awareness service is to filter papers by subject matterrnwithout any judgment of their academic quality. We use binary logistic regression analysis to estimate the probability ofrna paper being included in any of the subject reports as a function of a range of observable variables. Our analysisrnsuggests that, contrary to their own claims, editors use quality criteria. These include the reputation of the series asrnwell as the reputation of the authors. Our findings suggest that a current awareness service can be used as a first steprnof a peer-review process.
机译:RePEc是面向经济学界的大型数字图书馆。 “ NEP:新经济学论文”是对RePEc的最新添加的最新意识服务。该服务由志愿者编辑运行。他们将RePEc的新添加内容过滤到特定于主题的报告中。该当前意识服务的预期目的是按主题过滤论文,而不对其学术质量做出任何判断。我们使用二进制逻辑回归分析来估计作为任何可观察变量的函数的论文被纳入任何主题报告的概率。我们的分析建议,与他们自己的主张相反,编辑者使用质量标准。这些包括asrnwell系列的声誉以及作者的声誉。我们的发现表明,当前的意识服务可以用作同行评审过程的第一步。

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  • 会议地点 Charlotte NC(US);Charlotte NC(US)
  • 作者单位

    Palmer School of Library and Information Science, Long Island University, 720 Northern Boulevard, Brookville, NYrn11548 krichel@openlib.org;

    Kline Science Library, Yale University, 219 Prospect Street, PO Box 208111, New Haven, CT 06520-8111 nisa.bakkalbasi@yale.edu;

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