Shakespeare and Complexity Theory

Claire Hansen

• Publisher: Routledge
• Year: 2017
• Print ISBN: 9781138291287
• eBook ISBN: 9781351967426
• Topic: Literature
• Subtopic: Shakespeare Drama
• Index: Literature

In this new monograph, Claire Hansen demonstrates how Shakespeare can be understood as a complex system, and how complexity theory can provide compelling and original readings of Shakespeare's plays. The book utilises complexity theory to illuminate early modern theatrical practice, Shakespeare pedagogy, and the phenomenon of the Shakespeare 'myth'. The monograph re-evaluates Shakespeare, his plays, early modern theatre, and modern classrooms as complex systems, illustrating how the lens of complexity offers an enlightening new perspective on diverse areas of Shakespeare scholarship. The book's interdisciplinary approach enriches our understanding of Shakespeare and lays the foundation for complexity theory in Shakespeare studies and the humanities more broadly.

1 The Characteristics of Complexity

Complexity theory is a way of seeing the world that is flourishing in a variety of disciplines in the sciences and the arts. As complex systems are ‘usually associated with living things’,¹ complexity theory is deployed to explore a diverse range of phenomena from the creation of life to the aggregation of the slime mould, from the organisation of business corporations to the reshuffling of carbon atoms in a sea urchin embryo.² Complexity theory can be applied ‘to cosmic, galactic, stellar, planetary, chemical, biological, and social systems’.³ It is widely applicable because the principles of complexity apply to systems, not to the content of those systems: ‘What matters are the relationships, not the content matter.’⁴ The modelling of complex systems applies to the relationships between component parts, not to the physical manifestation of the parts themselves.⁵ This is why the sciences of complexity are ‘nomadic’; they are applicable in various fields.⁶

Given that the study of complexity theory is concerned with the identification and investigation of complex systems, it is worth first clarifying the meaning of ‘system’. The word may be misleading due to its familiar connotations of mechanistic order and regularity. Labelling a sophisticated phenomenon (such as weather patterns, ecosystems or the human brain) a complex ‘system’ can imply that the phenomenon is structured by some kind of predetermined plan. We need to be clear about the difference between a ‘system’ and a ‘complex system’. Not all systems are complex; some may be simply complicated. Adrian Mackenzie explicitly warns against the ‘generality’ of complexity theory, arguing that:

The generalisation of complexity into a world-view turns thought in circles on itself. It becomes a movement that goes nowhere because it encounters no obstacles and takes no risks: ‘everything is complex’.⁷

While it is possible to use complexity theory as a way of seeing the world across many disciplines and areas of life, it does not follow that all systems encountered must be complex. The chief difference between a generic idea of ‘system’ and a complex system is the system’s method of organisation. The primary understanding of a system is: ‘a whole composed of parts in orderly arrangement according to some scheme or plan’.⁸ However a complex system’s ‘orderly arrangement’ does not derive from a predetermined scheme or plan: it is ordered by the unpredictable interaction of its parts. These interactions must be dynamic, because a complex system is made up of elements that exert influences upon each other and, in the process, effect changes in themselves and others.⁹ The importance of interactions to a system’s complexity cannot be overstated. In fact, ‘the lack of dependence on any feedback or interactions between objects will make the overall system non-complex’.¹⁰

In its simplest form, then, a non-complex system is a grouping of related parts, ideas, or phenomena, which are organised by some kind of scheme or plan. By contrast, a complex system is identifiable by its unique organising pattern. Complex systems are self-organising, dynamic, evolving networks that operate without any centralised control. They are organised spontaneously and are composed of ongoing interactions between different parts. Despite being part of a complex system, these interacting parts may behave in quite simple ways: simple interactions can produce more complex behaviours and structures.¹¹ It is these interactions – sometimes simple, yet also unpredictable, diverse and numerous – which constitute the system itself, and the phenomena that emerge from these exchanges enable the system to continue developing.

This concept of ‘emergence’ is the reason why complexity theory privileges the interactions of a system’s elements, as it is not in the parts but in their relationships that the system’s complexity emerges: ‘components of a system through their interaction “spontaneously” develop collective properties or patterns’.¹² Although emerging from a complex system’s micro-dynamics, emergent phenomena cannot be reducible to them.¹³ This emergence is related to the system’s ability to spontaneously produce order out of chaotic and disorganised behavioural states. Complex systems can vary from stable to increasingly disordered phases. When a system becomes highly disordered, it enters a phase called ‘bounded instability’ or ‘the edge of chaos’.¹⁴ At such points, a system is far more likely to produce new, creative phenomena and behaviours that may drastically change the system or parts of it. The chaotic state thus generates new forms of order.

The 13 Characteristics of a Complex System

The following characteristics of complex systems provide the foundation of complexity theory’s key concepts, upon which this book is built. As well as offering a guide to the key characteristics of complexity incorporated throughout, these characteristics also function as a standalone list that will be applicable for readers wishing to utilise complexity theory in their own studies or fields. It offers a base for developing a working understanding of complex systems. These characteristics build on Paul Cilliers’ formative list, which has been influential in complexity studies.¹⁵

1 Complex systems are composed of many parts, elements, agents, or individuals (these may include living and non-living things). In this way a complex system can be thought of as ‘decentralised’ or distributed across its component parts.

2 A complex system is generated by a specific type of interactivity: the parts must interact in what Cilliers calls ‘dynamic’ and ‘rich’ ways – in other words, the system’s parts influence and are influenced by each other. The interaction is usually localised, and may comprise communication between individuals, groups and the environment.¹⁶

3 The interactions – and system patterns more broadly – are nonlinear. Their behaviour can appear unpredictable and consequences of the system’s interactions can be disproportionate.

4 A complex system is sustained by positive (turbulent) and negative (stabilising) feedback. In essence, the system’s interactions or output feed back into the system, creating interaction loops. Both positive and negative feedback are necessary for the system. Positive feedback ‘generally promotes changes in a system’,¹⁷ and can also be referred to as turbulence or perturbation. Negative feedback is behaviour that works to counteract turbulence experienced by a system.¹⁸

5 Complex systems are open – which means they interact with their environment. This makes it very difficult to define the system’s borders. What we identify as belonging to the system or to the system’s context is dependent upon the objectives and perspectives of the researcher.¹⁹ An examination of any complex system is thus also a ‘form of worldmaking’.²⁰ The system is inevitably a ‘conceptual construction’ or a model that is similar to but not the same as the reality it models.²¹

6 Complex systems require instability to survive. In fact, although such systems can behave in ordered, semi-ordered, or highly disordered ways, a certain point between organisation and chaos is understood to be the most productive and beneficial for the system. Complex systems can ‘achieve a “poised” state near the boundary between order and chaos, a state which optimises the complexity of tasks the systems can perform and simultaneously optimises evolvability’.²² This liminal state is called either ‘the edge of chaos’ or ‘bounded instability’.²³

7 A system has a history. The past is co-responsible with the present for the system’s behaviour.

8 Every element or part within a system is ignorant of the behaviour of the system as a whole. An individual only understands the system insofar as they understand their local interactions. The complexity of the system is not produced by any individual’s knowledge or design but as a result of the interactions between elements or parts.

9 A complex system is multilayered, comprising many levels or scales of interaction. A system’s levels can be understood spatially and temporally – they indicate both the size and age of the system.²⁴ This complex ‘hierarchy’ of levels can run from atoms to molecules, tissues to organisms, populations to communities.²⁵ This enables multiple perspectives on a system: from a macrocosmic view to a microcosmic or local perspective, to anywhere between ‘the molecular and the macro’.²⁶ A system’s levels are therefore conceptualised through the observer’s proximity to the system. The field of neurobiology provides a us...

Table of contents

• Cover Page
• Half Title
• Title Page
• Copyright Page
• Dedication Page
• Table of Contents
• List of Figures and Table
• Acknowledgements
• Introduction: Shakespeare, the System
• 1 The Characteristics of Complexity
• 2 ‘Like a tangled chain: nothing impaired, but all disordered’: Dance and Bounded Instability in A Midsummer Night’s Dream
• 3 ‘Hath the firmament more suns than one?’ Co-authorship, Space and Self-Organisation in Titus Andronicus
• 4 ‘Such Branches of Learning’: The Unexpected in Shakespeare Pedagogy and The Merchant of Venice
• 5 ‘Constant as the Northern Star’? The Power of Attractors in Stratford-upon-Avon and Julius Caesar
• Conclusion
• Bibliography
• Index