The Atlas of Social Complexity. Chapter 4: Cartography and constructing the atlas

 

Chapter 4 of the ATLAS OF SOCIAL COMPLEXITY is really our methods chapter; that is, how did we go about doing our research for the book.

 

Our approach is a critical cartography. More than just stating the facts, this Atlas is about the ways in which we can reimagine the global landscape of social complexity such that we discover new borders of knowledge. Our map is one of the present future, as we could best identify it, looking for common trends and trajectories. The adjacent possible to the current situation.

 

In compiling the Atlas, we relied on several sources.

·      This includes 41 interviews with a wide variety of people, from scientists to artists and practitioners. As interviewers, we focused on how these people enact the transdisciplinary nature of the complexity sciences by addressing some combination of the thirteen situations.

·      We also review the source materials we used for each of the chapters; and end by highlighting the role that art plays in the themes and chapters.

 

KEY WORDS: complexity map, cartography, mapping science, history of science, complexity sciences, Foucault and genealogy.

 

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The Atlas of Social Complexity. Chapter 3: The Thirteen Situations

 

As we mentioned in our previous blog post on Chapter 2 of the Atlas, the study of social complexity is up against thirteen situations that are holding it back from evolving into the truly disruptive transdisciplinary science it has sought over the last three decades to become.

 

The 24+ areas of research we review in the rest of the book are, in one way or another, using the social science turn and a social complexity imagination to get past these situations. Some more so than others, but nonetheless, that is the goal. The purpose of is to outline these thirteen situations.

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ABSTRACT:  

This chapter is key for all readers as it outlines the thirteen challenges that the study of social complexity must address to advance as a transdisciplinary disruptive science -- see Table below for the list. 

 

These situations range from ignoring the social sciences and qualitative methods, to treating computational models and simulation as the holy grail to all things socially complex, to failing to address issues of power and inequality in systems, to being tone-deaf about the real world. 

 

By understanding these situations, readers will gain a strong sense of the innovations and advances numerous fields we survey in the Atlas make to overcome those thirteen situations. This chapter works in conjunction with the critical history of Chapter 2.

 

KEY WORDS: philosophy of complexity, history of complexity science, sociology of science, map of complexity, policy and complexity, coming crisis of empirical social science. 

 

Situation	Characteristics
1. No philosophy of complexity	=Few attempts to define an epistemology and ontology for social complexity
2. A failure to engage the wider social sciences	=Assumption that the social sciences can be ignored because the complexity sciences would offer superior insights
3. Reinventing the wheel	=Reinventing existing insights from the social sciences that are then presented as new insights
4. Old words, new words	=Rebranding existing insights using terms from the complexity sciences
5. Obscurantism and mystification	=Scientific overreach and complicated jargon combine to suggest that life’s biggest questions are uncovered
6. Forgetting multilevel thinking and modelling	=Despite the transdisciplinary approach of social complexity, almost all research focuses on a single level of analysis.
7. Technique in the absence of theory	=Focus on computational methods and big data pushes social theory out of sight
8. Learning tools vs. predictive machines	=The ability to learn from simulations is replaced by a desire to predict and control social complexity
9. Minor role of qualitative research	=Dominance of quantitative research and quantification of data established a blind spot for qualitative data and methods
10. Methodological closing of social scientific mind	=Shying away from advances in computational methods sees many social scientists becoming illiterate with such methods
11. The dire sound of technicalities	=Going into a spiral of ever-smaller technical refinement while losing the bigger picture out of sight.
12. Being tone-deaf about the real world	=Advanced analyses are coupled to crude recommendations that fail to appreciate the complexity in the target domain
13. Practice does not make perfect	=Pragmatic and rushed adoption of the complexity sciences by practitioners constitutes verbal detritus

 

 

 

 

The Atlas of Social Complexity. Chapter 2. Origins of the Study of Social Complexity

Most histories of complexity are heroic adventures, focusing entirely on advance; ours is critical, exploring the challenges holding back the study of social complexity. The complexity sciences are not the disruptive, transdisciplinary science they promised to be.

Map, Special Collections, University of Amsterdam

 

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CHAPTER 2 SUMMARY:

Chapter 2 is all about setting the context for the tour the Atlas takes. You must set sail from somewhere. Our point of departure is the challenging and problematic place the complexity sciences find themselves in, presently, in terms of the study of social complexity.

 

Critically mapping that problematic space is the focus of Chapter 3. As outlined in that chapter, we have identified a set of thirteen situations that are holding the study of social complexity back from being a truly transdisciplinary disruptive science.

 

Chapter 2 focuses on understanding the historical pathways by which the study of social complexity ended up in a challenging space in the first place. We start by defining complexity. From there we present a critical history of the study of social complexity, focusing on four major historical shifts:

 

(1) the emergence of the complexity sciences.

(2) the invasion of natural scientists into everything social.

(3) the 1990s complexity turn in the social sciences.

(4) the social science turn in complexity, circa 2020s, which is the shift that holds our attention for the rest of the book.

 

 

Map of the early years of the complexity sciences, with a focus on the Santa Fe Institute

 

Johanna Bergmann, John Casti, 2002

 

Map of the complexity sciences, circa 2022. The field has massively expanded, but also, in the process, become watered down, evolving into ‘normal’ science in the Kuhnian sense of the word.

 

 

No, Not Everything is Scale-Free!!!!

Of the various examples we provide in Chapter 2 of how, historically speaking, the study of social complexity has evolved into the current predicament it faces, one of the most straightforward is the study of scale-free networks.

There is significant controversy around whether scale-free networks exist, given that the definition requires that the distribution fit a power-law, which most networks with long-tails do not meet. The problem is that, in the real-world, scale-free networks that fit a power law are not so easily identified and mapped. After the initial excitement resided, then, in the 1990s,researchers started running into all sorts of problems fitting the tails of these distributions.What they found was that, while lots of scale-free networks have the classic heavy tail distribution, they do not regularly fit the power law criteria.

 

Here is the problem: instead of evolving the concept in response to the empirical data, divisions emerged, with many of those involved in its initial conception holding on to the concept as sacred. In fact, these are literally the words used by Voitalov and colleagues’ in their 2019 article, 'Scale-Free Networks Well Done’, which is a defence of scale-free networks.  They state, “Scale-free and power-law are sacral words in network science, a mature field that studies complex systems in nature and society by representing these systems as networks of interacting elements” (p. 1). 

 

(For more on this controversy, see Erica Klarreich’s article, CLICK HERE. For Barabasi’s response, amongst, others, CLICK HERE.)

 

What is our point? We are not saying complexity science cannot be without controversies. We are saying the opposite. It should be controversial! For us, most of science is a dialogue, a critical argument, in search of useful insights into how the world works. When concepts in the complexity sciences are considered sacred, one is venturing into troublesome territory, with boundaries being built around ideas, including who is allowed to say what and when, as in the case of natural science over social science. If the complexity sciences are to be continually transdisciplinary and disruptive for the purposes of studying social complexity, the field needs a bit of a shake. It needs what we are calling a social science turn – a critical reflection on complexity from a different perspective, it needs a rigorous and critical engagement with the social sciences it sought to advance.

 

REFERENCES

1.         Anna D. Broido and Aaron Clauset, ‘Scale-Free Networks Are Rare’, Nature Communications 10, no. 1 (December 2019): 1017.

2.         Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman, ‘Power-Law Distributions in Empirical Data’, SIAM Review 51, no. 4 (4 November 2009): 661–703.

3.         Brian Castellani and Rajeev Rajaram, ‘Past the Power Law: Complex Systems and the Limiting Law of Restricted Diversity’, Complexity 21, no. S2 (2016): 99–112.

4.         Voitalov et al., ‘Scale-Free Networks Well Done’, Physical Review Research 1, no. 3 (18 October 2019): 033034, https://doi.org/10.1103/PhysRevResearch.1.033034.

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The Atlas of Social Complexity. Chapter 1: advancing transdisciplinarity and a social complexity imagination

The Atlas of Social Complexity

As a quick summary, the Atlas of Social Complexity charts the future of the field, focusing on the avenues of research with the greatest promise for advancing social complexity as a truly disruptive, transdisciplinary science. Together, these advances, organised around six transdisciplinary themes and twenty-four topics, constitute the social science turn in complexity. The first theme sets the agenda for the tour, exploring the thirteen challenges presently facing the field – from overvaluing computational modelling to ignoring social science – and the social complexity imagination necessary to address them. The tour then takes off, surveying twenty-four research areas – from immune system cognition to network theories of psychopathology to resilience and configurational social science to complex realism – thematically organised around: cognition, emotion and consciousness; the dynamics of human psychology; living in social systems; advancing a new methods agenda; and the creative value of unfinished spaces. The tour ends encouraging readers to use the Atlas maps to chart their own travels into new territory.

 

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PURPOSE OF CHAPTER 1

This chapter marks the start of our tour by clarifying what we mean by transdisciplinarity; outlining the contours of a social complexity imagination; summarising the six themes of the tour; and detailing how to read the book in a nonlinear and even team-based way. The Atlas of Social Complexity maps the future of the field, focusing on the avenues of research with the greatest promise for advancing the study of social complexity as a truly disruptive, transdisciplinary science. For those looking to do research in the field, it provides an extensive array of topics to explore or combine, including methods

Social Complexity Imagination: In the spirit of C. Wright Mills, the best way for the study of social complexity to overcome its current limitations and to become truly transdisciplinary is to reembrace a social complexity imagination. This time, however, the inspiration comes from a different direction: it comes from a direct engagement with the social sciences, practice, policy and the arts, in particular those areas that don’t associate themselves with the complexity sciences.  

We see such a renewed social complexity imagination expanding outward in four directions. 

• The first is to imagine a study of social complexity that moves beyond the wider and often contradictory social organisational and historical patterns that bracket the social sciences and the relationship between those sciences and practices of everyday life. This implies attending to the thirteen situations that are currently threatening the study of social complexity. 
•  The second is to imagine the study of social complexity as belonging and contributing to a long lineage of intellectual development that comes in fits and bounds, and that features waves of creation and destruction. In fact, C. Wright Mills wrote the sociological imagination in 1959, in part, to challenge the hubris, blind spots, trappings and failures of Talcott Parsons’ grand social systems theory, which was built on a combination of cybernetics, systems theory and classic sociology and which sought to promote a transdisciplinary social science. It seems to us that these attempts and subsequent criticism are part of a cycle of creation and destruction that drives the social sciences. 
•  The third is to imagine the study of social complexity as embracing the complexity of the globalised world in which we live. This includes the development of a more sophisticated (social) psychological response to complexity by thinking, feeling, behaving and changing in complex ways. There is often a disconnect between the analysis of social complexity on the one hand, and the full acceptance of it in daily life on the other hand. 
•  The fourth direction imagines the study of social complexity as one that critically examines the role of politics, power and inequality – not just as one of the many measures in complex system analysis but above all in qualitative terms.

 

 

Using case-based systems mapping for policy evaluation: A case study using policy data on urban planning

 

At ICCS this year (24th International Conference on Computational Science), which was in Malaga Spain, Mike Lees, Roland Bouffanais and I ran our Second Workshop on Computational Diplomacy and Policy (CodiP).

 

A QUICK SUMMARY OF CodiP

Our (quickly becoming) annual workshop provides a platform for scientists and policy makers to share and discuss the latest developments in the multidisciplinary areas at the intersection between computational science, international relations, policy and governance.

 

Following the successful launch of the inaugural CodiP workshop during ICCS 2023, this second edition builds on the solid foundation laid previously in applying computational techniques, and in particular computational modeling, to address decision-making challenges in policy and diplomacy, including the latest developments in AI and modelling software that supports or stands in for real-time decision making. This upcoming workshop is designed to delve deeper into the subject matter with an emphasis on state-of-the-art methods.

 

This second edition is co-organized by the Universities of Amsterdam, Geneva, and Durham. At Amsterdam, the POLDER initiative is developing co-created research and new educational programmes around complexity, policy and social systems. The University of Geneva, through the SiDLab is building a new group around computational diplomacy. The University of Durham, through the Durham Research Methods Centre is working with scholars and non-academic partners to develop interdisciplinary methods training and research. The second edition of this annual workshop will provide a platform for scientists and policy makers to share and discuss the latest developments in these emerging areas.

 

MY PRESENTATION:

Using case-based systems mapping for policy evaluation:

A case study using policy data on urban planning

Lasse Gerrits and I recently published The Atlas of Social Complexity. The Atlas is a cartography of social complexity’s future, charting the leading-edge transformations taking place across six major transdisciplinary themes and over twenty-four research topics. Grounded in a social complexity imagination, which gets back to the importance of social science, the environment, our embodied minds, and real-world impact, these transformations constitute a new social science turn in complexity studies. Themes range from cognition, emotion and consciousness to the dynamics of human psychology to living in social systems to advancing a new methods agenda. Topics range from immune system cognition and network theories of psychopathology to configurational and intersectional social science to the complexities of place and governance to resilience and economics in an unstable world. For those looking to get past the normalising conventions of the complexity sciences (particularly postgraduate students and early career researchers) in search of new ideas and new ways of working, this is the tour you’re looking for.

In the book, we devote an entire theme to the latest developments in multi-methods (including qualitative) for exploring social complexity. Two key developments are case-based configurational methods and systems mapping. 

Based on these developments, my colleagues and I have developed COMPLEX-IT, an R-shiny, online case-based, computational, multi-methods approach to systems mapping for helping policy evaluators engage their data, including qualitative data. For non-numeric data this approach employs a Fuzzy-set algebraic approach that converts qualitative policy evaluation data into a format that can then be modelled. Be it numeric or Boolean, our approach uses a suite of tools, including machine learning, k-means cluster analysis and hierarchical cluster analysis, to produce an immediate ‘systems map’ for exploration. The systems map is generated using zero-order correlations and can be explored using several network mapping tools, including in-degree/out-degree, ego-network analysis, etc. It can also be modified, or added to, to explore barriers or levers to change, and used in the standard manner of most systems mapping exercises. To demonstrate the value of our approach, we use policy data on urban planning from several European cities.

 

Here is a link to COMPLEX-IT

 

Here is a link to our new book, The Atlas of Social Complexity