Study of Salary Differentials by Gender and Discipline

IF 1.5 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS Statistics and Public Policy Pub Date : 2017-01-01 DOI:10.1080/2330443X.2017.1317223
L. Billard
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引用次数: 2

Abstract

ABSTRACT Although it is 45 years since legislation made gender discrimination on university campuses illegal, salary inequities continue to exist today. The seminal work in studying the existence of salary inequities is that of the American Association of University Professors (AAUP), by Scott (1977) and Gray (1980). Subsequently, innumerable analyses based on versions of their multiple regression model have been published. Salary is the dependent variable and is modeled to depend on various independent predictor variables such as years employed. Often, indicator terms, for gender and/or discipline are included in the model as independent predicator variables. Unfortunately, many of these studies are not well grounded in basic statistical science. The most glaring omission is the failure to include indicator by predictor interaction terms in the model when required. The present work draws attention to the broader implications of using these models incorrectly, and the difficulties that ensue when they are not built on an appropriate sound statistical framework. Another issue surrounds the inclusion of “tainted” predictor variables that are themselves gender-biased, the most contentious being the (intuitive) choice of rank. Therefore, a brief look at this issue is included; unfortunately, it is shown that rank still today seems to persist as a tainted variable.
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性别与学科薪酬差异研究
摘要尽管立法将大学校园性别歧视定为非法已经45年了,但薪酬不平等现象仍然存在。Scott(1977)和Gray(1980)的美国大学教授协会(AAUP)在研究薪酬不平等的存在方面做了开创性的工作。随后,基于多元回归模型版本的无数分析已经发表。工资是因变量,并根据各种独立的预测变量(如工作年限)进行建模。通常,性别和/或学科的指标术语作为独立的预测变量包含在模型中。不幸的是,这些研究中的许多都没有很好的基础统计科学。最明显的遗漏是在需要时未能在模型中包含逐指标的交互项。本工作提请注意错误使用这些模型的更广泛影响,以及如果这些模型没有建立在适当健全的统计框架上,会带来的困难。另一个问题围绕着包含“污点”预测变量,这些变量本身就有性别偏见,最具争议的是(直观的)排名选择。因此,本文简要介绍了这一问题;不幸的是,研究表明,排名在今天似乎仍然是一个受污染的变量。
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来源期刊
Statistics and Public Policy
Statistics and Public Policy SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
3.20
自引率
6.20%
发文量
13
审稿时长
32 weeks
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