The Scholarly Impact Matrix: An Empirical Study of How Multiple Metrics Create an Informed Story of a Scholar's Work

Caroline L. Osborne, Stephanie C. Miller
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引用次数: 1

Abstract

This article analyzes data collected in an empirical study of citation metrics. Between February 1, 2019 and April 30, 2019, the authors collected citation data from Google Scholar, HeinOnline, Westlaw, Lexis, SSRN, and Digital Commons repositories on randomly selected faculty members at U.S. law schools for the purpose of answering questions regarding fit and utility of citation metrics. Analysis of the citation data examines the impact of adoption of scholarly profiles, gender, and stage in the profession, and discipline, on exposure on citation with the conclusion that exposure results in increased citations.
学术影响矩阵:多重指标如何创造学者工作的知情故事的实证研究
本文分析了在引文度量的实证研究中收集的数据。在2019年2月1日至2019年4月30日期间,作者从Google Scholar、HeinOnline、Westlaw、Lexis、SSRN和数字共享数据库中收集了随机选择的美国法学院教员的引文数据,目的是回答有关引文指标的适合性和实用性的问题。对引文数据的分析考察了采用学术概况、性别、专业阶段和学科对引文曝光的影响,得出的结论是,曝光导致引文增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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