The Neuroscience of Gender Bias within Organisations: Implicit and Explicit Influences

2021 ◽  
Author(s):  
◽  
James Wicks

<p>It has been 30 years since the metaphor of a ‘glass ceiling’ was introduced, yet progress to address gender bias in organisations has been slow. Within a context in which employment is rapidly changing and technologies are enabling new ways of working, gender bias in organisations remains a persistent and complex issue that requires new ways of thinking. This study integrates across two scientific disciplines: social cognitive neuroscience and complex adaptive systems, in order to examine the complex nature of gender bias in organisations and advance implications for practice.  The central proposition underlying this study is that the gender composition of a person’s ‘in-group’, that is the group of people one most closely relates to in a work setting, has implications for their level of gender bias. The relationship between in-group composition and gender bias is examined from implicit (unconscious) and explicit (conscious) bias perspectives. The composition of in-group is measured by homogeneity, size and trust, and is captured within an integrated instrument that includes measures of implicit and explicit bias.  The study is informed by the theory of interactive person construal. It is proposed that biases are a dynamic, continuously evolving phenomena emerging from top down and bottom up cues. Specifically, the essence of this research is the relationship between the neuroscientific dynamics of in-group and out-group differentiation within the human brain and the complex systemic nature of the modern workplace. The study endeavours to make a contribution to the understanding of how people who share common values and interests (ingroup) influence gender bias in organisations.  The research has been conducted in a professional services organisation. A group of people within the organisation were asked to participate in an online survey to capture implicit bias, explicit bias, composition of their in-group and demographic details. This research applied a quantitative survey methodology.  The aims of the study are to:  • examine the relationship between in-group composition and gender bias building from theoretical insights from neuroscience and complex adaptive systems theory,  • test both implicit and explicit attitudes towards gender bias,  • test the relationship between implicit and explicit measures of bias, and  • provide a contribution to theory and practice in relation to addressing the issue of gender bias in organisations.  It is concluded that there is a statistically significant association between in-group composition and the manifestation of implicit and explicit bias using a variety of measures. The model of in-group composition developed for this study could be used as a means to understand gender system dynamics. A dynamic systems model of bias is proposed based on the research variables and complexity ideas examined in the study. For organisations, this research has implications for how the issue of gender bias should be approached. Connecting ideas from social cognitive neuroscience and complex adaptive systems, this research highlights the interrelationship between recurring levels (neural, individual, group, organisation) within the bias system and the nature of interventions that may lead to enduring change.</p>

2021 ◽  
Author(s):  
◽  
James Wicks

<p>It has been 30 years since the metaphor of a ‘glass ceiling’ was introduced, yet progress to address gender bias in organisations has been slow. Within a context in which employment is rapidly changing and technologies are enabling new ways of working, gender bias in organisations remains a persistent and complex issue that requires new ways of thinking. This study integrates across two scientific disciplines: social cognitive neuroscience and complex adaptive systems, in order to examine the complex nature of gender bias in organisations and advance implications for practice.  The central proposition underlying this study is that the gender composition of a person’s ‘in-group’, that is the group of people one most closely relates to in a work setting, has implications for their level of gender bias. The relationship between in-group composition and gender bias is examined from implicit (unconscious) and explicit (conscious) bias perspectives. The composition of in-group is measured by homogeneity, size and trust, and is captured within an integrated instrument that includes measures of implicit and explicit bias.  The study is informed by the theory of interactive person construal. It is proposed that biases are a dynamic, continuously evolving phenomena emerging from top down and bottom up cues. Specifically, the essence of this research is the relationship between the neuroscientific dynamics of in-group and out-group differentiation within the human brain and the complex systemic nature of the modern workplace. The study endeavours to make a contribution to the understanding of how people who share common values and interests (ingroup) influence gender bias in organisations.  The research has been conducted in a professional services organisation. A group of people within the organisation were asked to participate in an online survey to capture implicit bias, explicit bias, composition of their in-group and demographic details. This research applied a quantitative survey methodology.  The aims of the study are to:  • examine the relationship between in-group composition and gender bias building from theoretical insights from neuroscience and complex adaptive systems theory,  • test both implicit and explicit attitudes towards gender bias,  • test the relationship between implicit and explicit measures of bias, and  • provide a contribution to theory and practice in relation to addressing the issue of gender bias in organisations.  It is concluded that there is a statistically significant association between in-group composition and the manifestation of implicit and explicit bias using a variety of measures. The model of in-group composition developed for this study could be used as a means to understand gender system dynamics. A dynamic systems model of bias is proposed based on the research variables and complexity ideas examined in the study. For organisations, this research has implications for how the issue of gender bias should be approached. Connecting ideas from social cognitive neuroscience and complex adaptive systems, this research highlights the interrelationship between recurring levels (neural, individual, group, organisation) within the bias system and the nature of interventions that may lead to enduring change.</p>


Glottotheory ◽  
2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Stefan Hartmann

AbstractThe relationship between “language change” and “language evolution” has recently become subject to some debate regarding the scope of both concepts. It has been claimed that while the latter used to refer to the language origins in the first place, both terms can now, to a certain extent, be used synonymously. In this paper, I argue that this can partly be explained by parallel developments both in historical linguistics and in the field of language evolution research that have led to a considerable amount of convergence between both fields. Both have adopted usage-based approaches and data-driven methods, which entails similar research questions and similar perspectives on the phenomena under investigation. This has ramifications for current models and theories of language change (or evolution). Two approaches in particular, the concept of complex adaptive systems and construction grammar, have been combined in integrated approaches that seek to explain both language emergence and language change over historical time. I discuss the potential and limitations of this integrated approach, and I argue that there is still some unexplored potential for cross-fertilization.


1997 ◽  
Vol 8 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Daniel Cervone

This article presents a social-cognitive analysis of cross-situational coherence in personality functioning Social-cognitive analyses are contrasted with those of trait approaches in personality psychology Rather than attributing coherence to high-level constructs that correspond directly to observed patterns of social behavior, social-cognitive theory pursues a “bottom-up” analytic strategy in which coherence derives from interactions among multiple underlying causal mechanisms, no one of which corresponds directly to a broad set of responses Research investigating social and self-knowledge underlying cross-situational coherence in a central social-cognitive mechanism, perceived self-efficacy, is presented Idio-graphic analyses revealed that individuals' schematic self-knowledge and situational beliefs give rise to patterns of high and low self-efficacy appraisal across diverse, idiosyncratic sets of situations that do not, in general, correspond to traditional high-level trait categories Bottom-up analyses in personality psychology are related to other disciplines' analyses of organization in complex, adaptive systems


Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1330-1354 ◽  
Author(s):  
Maurice Yolles

PurposeComplex systems adapt to survive, but little comparative literature exists on various approaches. Adaptive complex systems are generic, this referring to propositions concerning their bounded instability, adaptability and viability. Two classes of adaptive complex system theories exist: hard and soft. Hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and softer theories, which we refer to as Viable Systems Theories (VSTs), that include Management Cybernetics at one extreme and Humanism at the other. This paper has a dual purpose distributed across two parts. In Part 1, the purpose of this paper is to identify the conditions for the complementarity of the two classes of theory. In Part 2, the purpose is to explore (in part using Agency Theory) the two classes of theory and their proposed complexity continuum.Design/methodology/approachA detailed analysis of the literature permits a distinction between hard and softer approaches towards modelling complex social systems. Hard theories are human-incommensurable, while soft ones are human-commensurable, therefore more closely related to the human condition. The characteristics that differentiate between hard and soft approaches are identified.FindingsHard theories are more restrictive than the softer theories. The latter can embrace degrees of “softness” and it is explained how hard and soft approaches can be mixed, sometimes creating Harmony.Originality/valueThere are very few explorations of the relationship between hard and soft approaches to complexity theory, and even fewer that draw in the notion of harmony.


2019 ◽  
Vol 46 (8) ◽  
pp. 961-984
Author(s):  
Nathan Eckstrand

This article explores the relationship between deliberative democracy, the Internet, and systems theory’s thoughts on diversity. After introducing Habermas’s theory of deliberative democracy and how diversity fits into it, the article discusses various ideas about whether and how it could work on the Internet. Next, the article looks at research into diversity done in the field of complex adaptive systems, showing that diversity has both good and bad effects, but is clearly preferred for the purpose of survival. The article concludes with an analysis of how the results of systems theory’s study of diversity can assist society in bringing democracy to the Web.


2020 ◽  
Author(s):  
Wiljeana Glover ◽  
Noa Nissinboim ◽  
Eitan Naveh

Abstract Background: Health innovation has been dominant in the pharmaceutical, biomedical, and to some extent insurance institutions for quite some time. Now we are in an innovation age for healthcare delivery. Some note that the complexity of healthcare delivery may make innovation in this setting more difficult and may require more adaptive solutions. The aim of this study is to examine the relationship between departmental complexity and innovation, using a complex adaptive systems approach in a hospital setting. Methods: We conducted a quantitative study of 31 hospital units within one hospital and use complex adaptive systems (CAS) theory to examine how two CAS factors, autonomy and performance orientation, moderate the relationship between departmental complexity and innovation. Results: We find that departmental complexity is associated with higher innovation performance when autonomy is low rather than high. We also find that departmental complexity is associated with higher innovation performance when performance orientation is high rather than low. Our findings make three distinct contributions: we quantify the influence of complexity on innovation success in the health care sector, we examine the impact of autonomy on innovation in health care, and we are the first to examine performance orientation on innovation in health care. Conclusions: This study tackles the long debate about the influence of complexity on healthcare delivery, particularly innovation. Instead of being subject to the influence of complexity with no means of making progress or gaining control, hospitals looking to implement innovation programs should provide guidance to teams and departments regarding the type of innovation sought and provide support in terms of time and management commitment. Hospitals should also find ways to promote and make successful pilot implementations of such innovations visible in the organization. A close connection between the targeted innovation and the overall success and performance of the hospital unit is ideal.


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