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Identifying key structural factors leading to gender disparities in research productivity, impact, and collaboration patterns in STEM disciplines.

机译：确定导致STEM学科研究生产率，影响和协作模式中性别差异的关键结构因素。

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摘要

The under-representation of women in most science, technology, engineering, and mathematical (STEM) disciplines is a troubling phenomenon. Many studies demonstrate that there is still a significant gender bias, especially at higher career levels. It is the major concern of the entire scientific community to elucidate the systemic factors contributing to the gender discrepancy in career performance and advancement in STEM disciplines. However, the complex nature of the problem, lack of data, and the prevalence of qualitative methods make the task highly challenging. Fortunately, the rise of complex system research and advancements in information technology provide us exciting possibilities. With bibliographical data on millions of scientific publications at hand, we can now conduct data collection and analysis on a unprecedentedly large scale. In this dissertation I report a systematic, quantitative investigation of the key structural factors that lead to the current gender discrepancies in STEM. We first fully characterize the academic careers of thousands of researchers in terms of productivity, impact, and collaboration patterns. Using statistically-sound methods, we precisely quantify the gender differences and identify factors that emerge only from a macroscopic perspective. Our analyses reveal for the first time the roles of resource requirements and academic career-choice risk on gender differences in publication rate and impact, as well as field-dependent scientific collaboration patterns. Our findings have significant policy implications for achieving diversity at the faculty level within the STEM disciplines. To accurately measure scientific research impact, we design an objective evaluation system for scientific research impact based on a thorough understanding of the citation process and rigorous statistical framework. In contrast to previous heuristic solutions, our measure is particularly reliable and is robust against manipulation.
机译：在大多数科学，技术，工程和数学（STEM）学科中，女性任职人数不足是一个令人不安的现象。许多研究表明，仍然存在明显的性别偏见，尤其是在较高的职业水平上。阐明导致性别差异导致职业表现和STEM学科发展的系统因素是整个科学界的主要关注。但是，问题的复杂性，缺乏数据以及定性方法的普及使这项任务极具挑战性。幸运的是，复杂系统研究的兴起和信息技术的发展为我们提供了令人兴奋的可能性。有了数百万本科学出版物上的书目数据，我们现在可以进行前所未有的大规模数据收集和分析。在这篇论文中，我报告了导致当前STEM性别差异的关键结构因素的系统，定量研究。我们首先根据生产力，影响力和协作模式全面描述成千上万研究人员的学术职业。使用统计上合理的方法，我们可以精确地量化性别差异并识别仅从宏观角度出现的因素。我们的分析首次揭示了资源需求和学术职业选择风险对性别差异在出版率和影响以及与领域相关的科学合作模式方面的作用。我们的发现对在STEM学科内实现教师级别的多元化具有重要的政策意义。为了准确地衡量科研影响，我们在对引证过程和严格的统计框架有透彻了解的基础上，设计了一套客观的科研影响评估系统。与以前的启发式解决方案相比，我们的方法特别可靠，并且对操作具有鲁棒性。

著录项

  • 作者

    Zeng, Xiaohan.;

  • 作者单位

    Northwestern University.;

  • 授予单位 Northwestern University.;
  • 学科 Information Science.;Physics General.;Statistics.;Gender Studies.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 158 p.
  • 总页数 158
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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