From bias to exclusion: A multilevel emergent theory of gender segregation in organizations

From bias to exclusion: A multilevel emergent theory of gender segregation in organizations
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DOI:
10.1016/j.riob.2012.10.001
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发表时间:
2012-01-01
期刊:
RESEARCH IN ORGANIZATIONAL BEHAVIOR: AN ANNUAL SERIES OF ANALYTICAL ESSAYS AND CRITICAL REVIEWS, VOL 32
影响因子:
--
通讯作者:
Robison-Cox, James
Robison-Cox, James
中科院分区:
其他
文献类型:
--
作者:
Martell, Richard F.;Emrich, Cynthia G.;Robison-Cox, James

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本文提出了一个多层次的组织隔离理论,将绩效评估中的性别偏见(微观层面的现象)与组织中的性别隔离(宏观层面的现象)联系起来。基于多层次研究、涌现理论和信号理论的整合,我们提出:(1)组织中的性别隔离是一种涌现现象,它是由个体的集体行为引起的,这些个体只表现出对男性的微小偏好,与控制晋升决策和组织流动的信号相一致;(B)性别隔离组织的出现往往是无意的,造成隔离的自下而上和自上而下的过程很难看到;和(c)基于代理的建模特别适合于阐明产生性别隔离组织的偏见的动态。这一多层次的基于涌现的理论有助于组织分层的研究文献:(a)揭示了微观和宏观层面的力量合谋的方式,往往是无意中,产生性别隔离的组织;(B)提供了新的和非常不同的方向,为未来的性别隔离研究依赖于基于代理人的建模;最重要的是,(c)将持续了30年的关于性别偏见对“现实世界”影响的辩论转移到更肥沃的土壤上,这场辩论继续占据着人力资源管理领域,最近还占据着最高法院法官的领域。(C)2012爱思唯尔有限公司版权所有。
This article presents a multilevel emergent theory of organizational segregation linking gender bias in performance assessment (a micro-level phenomenon) to gender segregation in organizations (a macro-level phenomenon). Based on an integration of multilevel research, emergence and signaling theory, we propose the following: (a) gender segregation in organizations is an emergent phenomenon that arises from the collective behavior of individuals who express only a small bias in favor of males, in concert with the signals governing promotion decisions and organizational mobility; (b) the emergence of a gender-segregated organization is often unintentional and the bottom up and top down processes that produce segregation are difficult to see; and (c) agent-based modeling is especially well-suited for illuminating the dynamics of bias that produce gender-segregated organizations. This multilevel emergent-based theory contributes to the research literature on organizational stratification by: (a) revealing the manner in which micro-level and macro-level forces conspire, oftentimes unwittingly, to produce gender-segregated organizations; (b) providing new and very different directions for future research on gender segregation that rely on agent-based modeling; and, most importantly, (c) moving a 30-year debate over the "real-world" impact of gender bias that continues to occupy the field of human resource management and, most recently, Supreme Court justices on to more fertile ground. (C) 2012 Elsevier Ltd. All rights reserved.