The Contribution of Complexity Theory to Understanding and Explaining Policy Processes: A Study of Tertiary Education Policy Processes in New Zealand

<p>The thesis examines how policy processes occur in practice over time, and advances a theory for understanding and explaining them using a complexity analytical lens. This lens provides a different way of 'seeing' policy processes holistically, in comparison with dominant alternative actor-focused, institutions-focused or idea-focused perspectives. The overall aims of the thesis are achieved through four phases. First, to construct the complexity lens, the thesis analyses the potential contribution of complexity theory, particularly as it relates to social systems and organisations. Second, existing theories of policy processes are scrutinised to identify areas where a complexity lens could provide new perspectives for their understanding, through a focus on: - 'wholes' of policy processes - policy problems and solutions - multiple participants - interactions within policy processes - dynamics within policy processes. Third, a study of New Zealand's tertiary education policy processes provides new empirical data. Data collected in unstructured interviews is represented in three differently-themed narratives, corresponding to three well-theorised analytical emphases: (1) participants; (2) institutions; and (3) ideas. The selection of three different perspectives takes into account the socially complex nature of policy processes. Fourth, the narrative data are examined through the complexity analytical lens and the results are compared with the views of policy processes obtained using the single lenses in the themed narratives. The four phases come together by demonstrating that viewing tertiary education policy processes through the complexity analytical lens provides a new perspective on policy processes which has implications for designing and intervening in policy processes. From this new perspective, policy processes are understood as complex social systems in interaction with other complex social systems. These systems consist of large numbers of interdependent and self-referencing participants, interacting with each other in ways that are nonlinear, influenced by prior experiences, and unpredictable in any precise sense.</p>

The Contribution of Complexity Theory to Understanding and Explaining Policy Processes: A Study of Tertiary Education Policy Processes in New Zealand

<p>The thesis examines how policy processes occur in practice over time, and advances a theory for understanding and explaining them using a complexity analytical lens. This lens provides a different way of 'seeing' policy processes holistically, in comparison with dominant alternative actor-focused, institutions-focused or idea-focused perspectives. The overall aims of the thesis are achieved through four phases. First, to construct the complexity lens, the thesis analyses the potential contribution of complexity theory, particularly as it relates to social systems and organisations. Second, existing theories of policy processes are scrutinised to identify areas where a complexity lens could provide new perspectives for their understanding, through a focus on: - 'wholes' of policy processes - policy problems and solutions - multiple participants - interactions within policy processes - dynamics within policy processes. Third, a study of New Zealand's tertiary education policy processes provides new empirical data. Data collected in unstructured interviews is represented in three differently-themed narratives, corresponding to three well-theorised analytical emphases: (1) participants; (2) institutions; and (3) ideas. The selection of three different perspectives takes into account the socially complex nature of policy processes. Fourth, the narrative data are examined through the complexity analytical lens and the results are compared with the views of policy processes obtained using the single lenses in the themed narratives. The four phases come together by demonstrating that viewing tertiary education policy processes through the complexity analytical lens provides a new perspective on policy processes which has implications for designing and intervening in policy processes. From this new perspective, policy processes are understood as complex social systems in interaction with other complex social systems. These systems consist of large numbers of interdependent and self-referencing participants, interacting with each other in ways that are nonlinear, influenced by prior experiences, and unpredictable in any precise sense.</p>

Learning to embed lifetime social behavior from interaction dynamics

Interactions of individuals in complex social systems give rise to emergent behaviors at the group level. Identifying the functional role that individuals take in the group at a specific time facilitates understanding the dynamics of these emergent processes. An individual's behavior at a given time can be partially inferred by common factors, such as age, but internal and external factors also substantially influence behavior, making it difficult to disentangle common development from individuality. Here we show that such dependencies on common factors can be used as an implicit bias to learn a temporally consistent representation of a functional role from social interaction networks. Using a unique dataset containing lifetime trajectories of multiple generations of individually-marked honey bees in two colonies, we propose a new temporal matrix factorization model that jointly learns the average developmental path and structured variations of individuals in the social network over their entire lives. Our method yields inherently interpretable embeddings that are biologically relevant and consistent over time, allowing one to compare individuals' functional roles regardless of when or in which colony they lived. Our method provides a quantitative framework for understanding behavioral heterogeneity in complex social systems, and is applicable to fields such as behavioral biology, social sciences, neuroscience, and information science.

A missing link: a distributed cognitive perspective on fit

PurposeThis article presents a cognitive framework to study dynamic/adaptive aspects of a collection of popular fit measures used in organisation research, in an attempt to highlight what there is to be gained.Design/methodology/approachThis paper uses a distributed e-cognition (DEC) framework to examine the current organisational literature of fit measures.FindingsThis paper highlights that most measures have a rather narrow focus and do not address dynamic/adaptive aspects in complex social systems (e.g. organisations). To both provide a way to integrate fit measures and cover the cognition gap in this literature, this article highlights the need for a more sophisticated measure.Originality/valueThis paper provides a novel approach to examining organisational fit literature through a distributed (e)-cognitive framework.

ROLE OF THE SELF-ORGANIZATION MODEL IN COMPLEX SOCIAL SYSTEMS

The article substantiates the following turning point in the evolution of a planetary civilization with unprecedented technological potential, timely improve the system of values, norms and mechanisms of self-organization in accordance with the new requirements of history, also, such thinking requires a lot of intellectual effort and a lot of information, and that this thinking, due to the influence of passing political sympathy and antipathy, is generally different from conventional thinking.

Ladders of Authority, Status, Responsibility and Ideology: Toward a Typology of Hierarchy in Social Systems

Hierarchy is a key characteristic of any complex system. This paper explores which notions of hierarchy are being used in the field of organization and management studies. Four distinct types of hierarchy are identified: a ladder of formal decision-making authority, a ladder of achieved status, a self-organized ladder of responsibility and an ideology-based ladder. A social mechanism-based perspective serves to define and distinguish these four types. Subsequently, the typology is further developed by comparing the four hierarchy types in terms of their tacit/explicitness, (in)transitivity and behavior- versus cognition-centeredness. This article contributes to the literature by dissecting the general metaphor of hierarchy into four different constructs and their social mechanisms, which serves to create a typology of the various ways in which complex social systems can be characterized as hierarchical. This typology can inform future research drawing on any type of hierarchy.

Towards a Learning Organization

A learning organization is one that is consistently capable of adaptive change in response to signals from its environment. However, knowledge management initiatives to enact learning organizations have not been uniformly successful. This chapter focuses on the role of the psychological environment of the individual in enabling or hampering organizational learning. Six theories drawn from multiple fields are reviewed to identify both opportunities and barriers to fostering change at the level of the individual. These include orientation to learning, motivation to act, and capacity for change. However, the authors argue that organizations ought to be regarded as complex social systems. Change strategies intended to foster a learning organization are more likely to succeed if they embrace the idea that designing change for complex social systems requires a special approach: design thinking. This is characterized by iterative prototyping, experimenting, trialing, and piloting changes to work processes, structures, and tasks.

Health inequality as a large-scale outcome of complex social systems: Lessons for action on the sustainable development goals

© 2020 by the author. Licensee MDPI, Basel, Switzerland. Action on the Sustainable Development Goals (SDGs) needs to become real and impactful, taking a “whole systems” perspective on levers for systems change. This article reviews what we have learned over the past century about the large-scale outcome of health inequality, and what we know about the behaviour of complex social systems. This combined knowledge provides lessons on the nature of inequality and what effective action on our big goals, like the SDGs, might look like. It argues that economic theories and positivist social theories which have dominated the last 150 years have largely excluded the nature of human connections to each other, and the environment. This exclusion of intimacy has legitimatised arguments that only value-free economic processes matter for macro human systems, and only abstract measurement constitutes valuable social science. Theories of complex systems provide an alternative perspective. One where health inequality is viewed as emergent, and causes are systemic and compounding. Action therefore needs to be intensely local, with power relationships key to transformation. This requires conscious and difficult intervention on the intolerable accumulation of resources; improved reciprocity between social groups; and reversal of system flows, which at present ebb away from the local and those already disadvantaged.