COMPLEX-IT: A User-friendly platform for doing QCA with computational methods

Lasse Gerrits and I would like to thank the organisers for the opportunity to present at the 11th International QCA Workshops, Antwerp 2023.

 

 Our presentation is based on The Atlas of Social Complexity, a book we recently completed, which will be launched spring 2024. Organised around six transdisciplinary themes and twenty-four topics the Atlas is an invaluable resource for all social science and complexity science scholars and students interested in new ideas and new ways of working in social complexity. It paves the way for the next generation of research in the study of social complexity.

 

One area of significant promise is the emergence of configurational social science (Chapter 20 and Chapter 30), which sits at the nexus of case-based configurational approaches – specifically QCA – intersectionality theory, critical complexity, and complex systems thinking.

 

 

QUICK OVERVIEW OF OUR PRESENTATION

While not widely recognized, the majority of computational methods are case-based and configurational e.g., online websites profiling users based on some configuration of factors. The challenge is making these methods accessible to social scientists, including qualitative researchers. Enter COMPLEX-IT, a freely available platform for users to explore data using a bespoke suite of computational methods: cluster analysis, machine learning, data visualisation, simulation, data forecasting and systems mapping. A key strength of COMPLEX-IT is that is works with set theoretic data so that users can explore their topic and its causality from a qualitative-comparative perspective (QCA), including modelling set-theoretic data across time.

 

In this lecture, we introduce the field of configurative social science, the multi-methods involved in this approach and their linkages to QCA, and then, as demonstration, a case study to explore how COMPLEX-IT, a platform for multi-methods configurational research, can be used to engage in a QCA approach using the latest developments in computational methods.

 

HERE ARE LINKS TO MATERIALS FROM OUR PRESENTATION

CLICK HERE to learn more about The Atlas of Social Complexity. 

CLICK HERE for a link to our POWER POINT presentation.

 

CLICK HERE to explore COMPLEX-IT, including tutorials and example dataset.

CLICKHERE for an introductory article on COMPLEX-IT

 

CLICK HERE for the mock QCA Urban Transformation Datase 

 

CLICK HERE for the mock DATA FORECASTING QCA Urban Transformation Datase

 

 

Using ChatGPT for Advanced Data Analysis - An example of the field of AM-Smart methods (approachable modelling and smart methods)

 

As some readers may recall, my colleague CoreySchimpf and I published an article in 2022 identifying a new area of methods development, called smart and approachable methods or AM-Smart for short. CLICK HERE for an open access copy of the article at IJSRM.

 

What are AM-Smart methods?

AM-Smart methods emerged over the last several years out of the intersection of smart technology, human-computer interface, educational design and interdisciplinary methods. AM-Smart platforms address a major challenge for applied and public sector analysts, educators and those trained in traditional methods: accessing the latest advances in interdisciplinary (particularly computational) methods.

 

AM-Smart platforms do so through nine design features. They are (1) bespoke tools that (2) involve a single or small network of interrelated (mostly computational) methods. They also (3) embed distributed expertise, (4) scaffold methods use, (5) provide rapid and formative feedback, (6) leverage visual reasoning, (7) enable productive failure, and (8) promote user-driven inquiry; all while (9) counting as rigorous and reliable tools.

 

Examples include R-shiny programs, computational modeling and statistical apps, public-sector data management platforms, data visualization tools, and smart phone apps. 

 

 

What about ChatGPT for advanced data analysis?

What we had not thought about was that advances such as ChatGPT also constituted a form of AM-Smart methods. That is until today, when I saw an advertisement for a 2-day instats workshop by Peter Gruber, titled, appropriately enough, UsingChatGPT for Advanced Data Analysis. Here is the brief description of the workshop:

 

This 2-day workshop teaches researchers, from PhD students to professors, how to use ChatGPT and its Advanced Data Analytics tool for statistical analysis without writing a line of code or even knowing how to use a statistics program. The seminar covers a range of topics from data preparation and descriptive statistics to regression analysis, advanced statistical tests and visualisation. Special emphasis is placed on understanding the workings and limits of AI models such as ChatGPT and reflecting on its implications for data analysis.

 

In addition to the description of the workshop, what caught my eye was the instats description of Gruber’s work around teaching methods.

 

Dr Gruber has been an early adopter of Large Language Models for teaching and research and leads the efforts of USI to integrate LLMs into the curriculum. He has been teaching statistics, financial econometrics and numerical methods with MATLAB, Python and R since 2005 at USI, University of St. Gallen, University of Geneva and Bocconi.

 This was insightful, because it suggested the approach that is very much driving the AM-Smart movement. Which is super cool.

 

This is not the only workshop!!!

To lean more, I started exploring on Google if other such workshops or courses were being offered. They are being offered! Lots of them. A whole new field of study and pedagogy seems to have emerged over night! Digital sociology and data science have a lot to think about!

 

Which led me to next ask, What is ChatGPT for advanced data analysis?

 

 

What is ChatGPT for advanced data analysis?

The best I can understand is that in August 2023, ChatGPT recently launched a new business version called ChatGPT Enterprise. Part of the package is the revamping of what used to be called CodeInterpreter – one of the quickly expanding list of Plugins being developed for ChatGPT – into its new version called Advanced Data Analysis – click here for a nice summary.

 

 

 

Let’s not get too excited!!!!

As Corey and I outlined in our articleon AM-Smart methods, while offering new possibilities for data analysis, critical reflection on AM-Smart platforms reveals considerable unevenness in these design features, which hamper their effectiveness.

 

A rigorous research agenda is vital.

 

A case in point is ChatGPT Advanced Data Analysis.

·       First, while currently free, it is not clear if it will not stay that way for long. This is potentially a major issue and goes against the open-access environment of current science and programming platforms such as R.

·       Second, it is not a bespoke suite of methods. It is unclear what sorts of algorithms are used in the background to do the work. What are the limits of these methods?

·       Third, it is not as user-friendly as it suggests. Part of the whole point of AM-Smart methods is ease of access. For example, there are limits to what data can be used and how it can be used. I am sure these issues will be addressed going forward, but presently the plug-in seems to be very much at the ground level.

·       There is still a significant learning curve to using it, including getting the plug-in to work.

·       Then there is the issue of data safety and access globally!

 

Then there is the question of pedagogy and value for teaching. It is key to have methods experts such as Peter Gruber involved in the development of AM-Smart methods, such as ChatGPT.  There are so many questions to explore. Is this a good way to learn statistics? Is fast statistics good statistics? What about gaming? Is that a good way to use methods? For example, I am increasingly worried about students not learning the math behind the methods they use, in the case of numerical analysis, and, in turn, the craft of qualitative inquiry, as in the case of ethnography.

 

Conclusion?

My short conclusion is that ChatGPT is a good example of AM-Smart methods but comes with lots of concerns that require the methods community to engage with it before endorsing it.

 

I do not make this point nonchalantly, as these sorts of smart tools are not the necessary future of methods. There is no inevitability here. Instead, there is lots of room for creative but critical interrogation and development, both for educational purposes and for the wider usage of methods in research, policy and practice.

 

 

 

 

 

Actearly Methods Club: The COMPLEX-IT Platform and Smart Methods at University of York

Much thanks to Philip Garnett and Liina Mansukoski for the chance to present at the ActEarly Methods Club at University of York. (ActEarly focusses on early life changes to improve the health and opportunities for children living in areas with high levels of child poverty; Bradford, West Yorkshire and Tower Hamlets, London.)

 

 The COMPLEX-IT Platform and the New Field of Approachable Modelling and Smart Methods

 

 Abstract:

Smart platforms constitute an entirely new field of methods that are still in the emergent stage, requiring critical engagement and also the real potential to develop a new methodological toolkit for social and health inquiry. Smart platforms are comprised of bespoke tools that facilitate user-driven learning by building expertise into the platform to create an intuitive, supportive, and open-ended environment for complex social and health inquiry. Unlike statistical platforms, AM-Smart platforms focus on a single technique or small network of interrelated (mostly computational) methods, which help users engage new methods. Smart platforms provide method-specific operational scaffolding, rapid and formative feedback, and which requires modest technical skill while being rigorous and reliable. This session will introduce this newly emerging field by exploring the AM-Smart platform, COMPLEX-IT.

 

Bio:

Brian is Director of the Research Methods Centre and Director of the Wolfson Research Institute for Health and Wellbeing at Durham University, UK. He is also editor of the Routledge Complexity in Social Science series, CO-I for the Centre for the Evaluation of Complexity Across the Nexus, and a Fellow of the UK National Academy of Social Sciences. Brian also runs InSPIRE, a UK policy and research consortium for mitigating the impact places have on air quality, dementia and brain health across the life course. Brian and his colleagues have spent the past ten years developing a new case-based, data mining approach to modelling complex social systems and social complexity, called COMPLEX-IT, which they have used to help researchers, policy evaluators, and public sector organisations address a variety of complex public health issues. Staff Profile

 

CLICK HERE for a link to a PDF of my presentation

 

CLICK HERE for a link to our paper on AM-Smart Methods

 

CLICK HERE for a link to COMPLEX-IT

InSPIRE Consortium for Mitigating the Impact of Air Pollution on Brain Health: Doing research to make an impact on policy and practice

Jonathan Wistow and I would like to thank Patrik Nordin, Helka Kallomäki, Harri Jalonen, Paula Rossi and their team for the opportunity to attend and present at the University of Vaasa summer school workshop, Writing Policy & Practice Relevant Research Papers: Why, What, When and How?

 

Our presentation was on the “What?” of policy practice

 

 

InSPIRE Consortium for Mitigating the Impact of Air Pollution on Brain Health: Doing research to make an impact on policy and practice

 

InSPIRE is a UK policy and research consortium devoted to mitigating the impact that air pollution and the exposome have on brain health (including cognitive function, cognitive frailty, mental health and dementia). As a knowledge hub/network, we have three foci: Acting as a repository for the latest advances in research, practice, and policy guidance. Co-producing tools and translational materials for the public and third sector. Engaging in world-leading research on places, the exposome and brain health. For this talk, I will explain how we set up the consortium to maximise our impact on policy and practice in this area and how informs the research we do and the works we publish.

 

HERE ARE SOME KEY LINKS:

 

CLICK HERE for a PDF of the presentation

 

CLICK HERE to visit InSPIRE Consortium

 

CLICK HERE to visit CECAN

 

CLICK HERE to visit the MAP OF COMPLEXITY SCIENCES

How to escape the dilemmas of complex systems modelling in public health: A users guide and map. 18th Social Simulation Conference (SSC)

I would like to thank Corinna Elsenbroich and team for organising the 18th Social Simulation Conference, which was hosted by the MRC/CSO Social and Public Health Sciences Unit University of Glasgow, 4-8th September 2023. Thanks also for inviting me to be one of the keynote speakers. Also, thanks to the audience for the great dialogue and engagement. The conference is one of the key activities of the European Social Simulation Association (ESSA) to promote social simulation and computational social science in Europe and elsewhere.

 

Here is the title and abstract of my talk:

 

How to escape the dilemmas of complex systems modelling in public health:

A users guide and map

 

The current literature is clear: there is an urgent need to apply a complex systems modelling approach to public health. What is less clear is how to do this effectively. Research and practice have shown mixed results, due to a series of dilemmas. A short list includes: a strong tendency to model public health issues instead of interrogating the development, implementation and evaluation of systems-level interventions; public health practitioners and funding organisations being biased toward simple, individual-level, short-term solutions based on clinical trials; modellers being tone deaf about the roadblocks to applying simulations to public health; the need to focus on stakeholder engagement; and an overemphasis on computational models over qualitative methods. Fortunately, a small but growing global network of scholars are charting new territory. They are part of a fresh turn in complexity and modelling, the social science turn, which fosters a transdisciplinary, social complexity imagination that, in one way or another, addresses the field’s current dilemmas to create new areas of disruptive and highly innovative social inquiry. The Atlas of social complexity – written with Lasse Gerrits, forthcoming 2024 Edward Elgar – charts this new territory, seeking to map its present future; which we do by outlining a set of ‘best practices’ (with examples of scholars doing this work) for applying social complexity to public health modelling. These include: (1) challenging social physics and reductionism, (2) rethinking complex causality and system dynamics, (3) emphasising co-creation and context, (4) understanding real-world policy making, (5) modelling at multiple levels and with multiple models, (6) developing interdisciplinary methods and using qualitative data, (7) grounding models in rigorous social science, and (8) accepting the limits of what modelling can do. 

 

CLICK HERE for a link to the PDF of my presentation

 

CLICK HERE for a link to COMPLEX-IT

 

CLICK HERE for a link to the Map of the Complexity Sciences

 

 

The Atlas of Social Complexity and the latest research in complexity and psychology. Society for Chaos Theory in Psychology & Life Sciences 33rd Annual International Conference

Much thanks to Stephen Guastello and colleagues for the chance to present at the Society for Chaos Theory in Psychology & Life Sciences 33rd Annual International Conference 2-4 August, 2023 at the Fields Institute at University of Toronto.

For my talk, I presented on our (mine and Lasse Gerrits) forthcoming Atlas of Social Complexity. My focus was on the complexity of psychology and the psychology of complexity research taking place at the forefront of the social science turn in the complexity sciences and the study of social complexity 

The book, which will be published in 2024, is as follows. Keep an eye out for it! CITATION: Castellani, Brian and Gerrits, Lasse. Forthcoming 2024. The Atlas of Social Complexity. Edward Elgar. 

MATERIALS:

•  CLICK HERE for the PDF of my presentation
• (note: slides are copyrighted, so please acknowledge if referenced or used)
  

• ·      CLICK HERE for the Complexity Sciences Map

  ·      CLICK HERE to explore COMPLEX-IT and its software, tutorials, etc.

  ·      CLICK HERE for a published article on COMPLEX-IT 

  ·      CLICK HERE for Big Data Mining and Complexity

  ·      CLICK HERE for the Sage Handbook of Case-Based Methods
  

   

Smart and approachable methods for stakeholders in policy and diplomacy -- ICCS CONFERENCE CoDip

Corey Schimpf and I presented our work as part of the Computational Diplomacy and Policy Workshop July 3rd, Prague, 2023, for the International Conference on Computational Science. The workshop was run by Michael Lees, Bastien Chopard, and me.

TITLE

The complexities of policy, data and computational methods: Charting a new, case-based, social science grounded, AM-Smart methods approach

 

Co-authors, in addition to Corey and me, include Peter Barbrook-Johnson, Lasse Gerrits, and Christopher Caden

 

 

ABSTRACT

In the globalized worlds in which we live, governments cannot escape the uncertainty, interdependence, and complexity of current public policy. Nor can they escape the urgent need for sweeping policy reform – infrastructural, political, environmental, social – to address this complexity, including the coordinating local, national, and international policies and stakeholders. Governments are also confronted presently with a big-data flood of information and the promised ‘sales pitch’ of computational science – from modelling and simulation to data science and artificial intelligence – to correctly guide decision-making. While such complexities of policy, data and methods is not an entirely new problem, what is of critical importance is how rather ineffective it has all been. The promise of complexity and computation has struggled to live up to expectation. A shift has emerged in the policy landscape, albeit minor, involving a ‘social science turn’ in complexity and computational modelling. This ‘turn’ involves using the theories, concepts, methods and empirical insights of social science to inform the complexity and computational sciences. In terms of specifics, leading areas of research includes co-production for simulation; participatory design; rigorous stakeholder engagement; a resurgence in systems mapping; mixed-methods development, such as qualitative comparative analysis and agent-based modelling; addressing issues of power and inequalities in the policy landscape, including grounding policy in a complexities of place approach; adopting a case-based perspective; and co-designing more easily accessible computational modelling platforms, called AM-Smart methods.

 

Our presentation will seek to outline this ‘social science’ turn in complexity and computational modelling and its implications for improving public policy. This outline will include (1) a brief overview of the above advances; (2) a quick introduction to a methods platform we developed, COMPLEX-IT, which has incorporated many of the social science turn advances into its design; and (3) critically reflect on the strengths and weakness of the social science turn, including barriers to and levers for advancing the utility of this approach across team members with distinct roles, perspectives, and intersections with public policy work. All with the goal of helping to advance the field of computational policy/diplomacy.

 

 

CLICK HERE TO ACCESS COMPLEX-IT

 

CLICK HERE TO ACCESS CECAN

 

CLICK HERE TO ACCESS PRSM – PARTICIPATORY SYSTEMS MAPPER

 

CLICK HERE FOR OPEN ACCESS BOOK, SYSTEMS MAPPING

 

CLICK HERE FOR POLDER CENTER AT UNIVERSITY OF AMSTERDAM

 

CLICK HERE FOR DURHAM RESEARCH METHODS CENTRE

 

CLICK HERE for the PDF of our Workshop Introduction

 

HERE ARE THE OTHER PRESENTATIONS FROM OUR TWO-PART SESSION

 

 

 

Mitigating the impact of air pollution on dementia and brain health: Setting the policy agenda (University of Suffolk, Together for Transformation Conference)

Much thanks to Valerie Gladwell and Colin Martin and the University of Suffolk for the opportunity to present at their Together for Transformation Conference, which focused on exploring transformational research to support collaboration, innovation and policy change.

 

I was there on behalf of INPSIRE and CECAN. InSPIRE is a UK policy and research consortium, housed at Durham University, devoted to mitigating the impact that air pollution and the exposome have on brain health (including cognitive function, mental health and dementia). CECAN is the Centre for the Evaluation of Complexity Across the Nexus.

 

I presented on the latest policy brief we have released on transforming policy on air quality and brain health. CLICK HERE FOR POLICY BRIEF. The brief is based on a 2022 article we published, Mitigating the impact of air pollution on dementia and brain health: Setting the policy agenda.

 

CLICK HERE for PDF of PowerPoint

 

ABSTRACT

Background: Emerging research suggests exposure to high levels of air pollution at critical points in the life-course is detrimental to brain health, including cognitive decline and dementia. Social determinants play a significant role, including socio-economic deprivation, environmental factors and heightened health and social inequalities. Policies have been proposed more generally, but their benefits for brain health have yet to be fully explored.

 

Objective and methods: Over the course of two years, we worked as a consortium of 20+ academics in a participatory and consensus method to develop the first policy agenda for mitigating air pollution's impact on brain health and dementia, including an umbrella review and engaging 11 stakeholder organisations.

 

Results: We identified three policy domains and 14 priority areas. Research and Funding included: (1) embracing a complexities of place approach that (2) highlights vulnerable populations; (3) details the impact of ambient PM2.5 on brain health, including current and historical high-resolution exposure models; (4) emphasises the importance of indoor air pollution; (5) catalogues the multiple pathways to disease for brain health and dementia, including those most at risk; (6) embraces a life course perspective; and (7) radically rethinks funding. Education and Awareness included: (8) making this unrecognised public health issue known; (9) developing educational products; (10) attaching air pollution and brain health to existing strategies and campaigns; and (11) providing publicly available monitoring, assessment and screening tools. Policy Evaluation included: (12) conducting complex systems evaluation; (13) engaging in co-production; and (14) evaluating air quality policies for their brain health benefits.

 

Conclusion: Given the pressing issues of brain health, dementia and air pollution, setting a policy agenda is crucial. Policy needs to be matched by scientific evidence and appropriate guidelines, including bespoke strategies to optimise impact and mitigate unintended consequences. The agenda provided here is the first step toward such a plan.

 

World-Leading Global Scholars Visiting and Working with the DRMC Team and Fellows

The DRMC has had a busy academic year and we are only two-thirds of the way through! Since autumn, through the Research Methods Café and other avenues, we have had research conversations on research interview methods, discussed R software, worked with our new DRMC Student Fellows, set up the new research themes, and developed a Power Automate guide to process separate reviewing of anonymous and identifiable information for grant/job applications.
 
We also had three visiting scholars to Durham. DRMC has tremendous capacity to become a world-leading hub for intellectual engagement around methods. Toward this effort, the following three international scholars visited the DRMC.

Prof Christophe Gernigon, Université de Montpellier, France Christophe is Professeur des Universités in Psychology of Sport and Exercise at the Université de Montpellier. Christophe specialises in the application of complexity modelling, in particular, dynamical systems theory, to topics in social psychology and sports psychology. For more on his work, click here.   While at Durham, Christophe gave two lectures. The first – The dynamics of approach and avoidance motivation: A key to understanding (non-) sporting lives? – was for the Department of Sport and Exercise at Durham. The second – On the reproducibility issue: Will psychological science ever exorcise Laplace’s Demon? – was for the DRMC.

Dr Corey Schimpf, State University of New York, USA Corey is in the Department of Engineering Education, University of Buffalo, State University of New York, USA. His expertise is in agent architecture and AI, design research and design thinking, data visualization, critical studies, data mining, educational technology, case-based methods, research methods, and computational social science.   Corey is part of the international DRMC team developing the AM-Smart methods platform, COMPLEX-IT – which non-experts can use to run some of the latest developments in computational modelling. We are presently developing a systems mapping tab and a fast-ABM tab. Corey visited Durham in October to present on a paper he and I recently wrote, Approachable modeling and smart methods: a new methods field of study.

Dr Philippe Giabbanelli, Miami University, USA Philippe is truly a global scholar. Born in France, studied in Canada, did his post-doctoral studies at Cambridge, and is presently working in the States. Philippe’s research group primarily work on simulation models and machine learning for public health. More specifically, they are focused on discrete simulation models (e.g., agent-based modeling, cellular automata), network analysis, and machine learning (e.g., classification, performance analysis). Currently, his main projects are (i) using machine learning to accelerate large-scale simulations and (ii) shifting from ‘big’ to ‘useful’ data by identifying the minimum parts of a dataset needed to quickly make accurate predictions.    Philippe is part of the international DRMC team developing new approaches to agent-based modelling. He was also a great colleague and support during the COVID pandemic, as the world community of modellers, of which our DRMC was a team, came together to quickly develop various models of the pandemic. As a result, we wrote the following paper together, Opportunities and challenges in developing covid-19 simulation models: Lessons from six funded projects.   In March, Philippe brought his global experience and methods expertise to Durham to work on a research paper with our team and to do two presentations. The first was Agent-based modelling for public health: New methods and applications to obesity and suicide. This is highly innovative work, engaging in co-creation for developing simulation models. It was an exciting talk! Click here and also click here for two papers on which this presentation was based. The second presentation, which you can click here to watch on YouTube, and which builds on the first, was Participatory modelling and mixed-methods for public health simulations.

Looking forward to 2023-2024. Building on our initial success, we will invite several more international scholars. So far, we are hoping we will be able to invite the following colleagues, perhaps for a conference on the philosophy of complexity. Stay tuned!

Dr Federica Russo, University of Amsterdam, Netherlands Federica is a philosopher of science, technology, and information based at the University of Amsterdam. Her current research concerns epistemological, methodological, and normative aspects as they arise in the biomedical and social sciences, and in highly technologized scientific contexts. She is currently working on an edited volume on complexity in causality. For more on her work, Click here.

Prof. dr dr, Lasse Gerrits, Erasmus University, Netherlands Lasse is Academic Director of the Institute for Housing and Urban Development Studies of Erasmus University Rotterdam. His current research focuses on social scientific research methods, complexity sciences, systems theories, urban planning and development, governance, railway systems, infrastructure development, qualitative research methods, qualitative comparative analysis, network analysis, system modelling, socio-technological evolution.

Prof. Andrea Hurst, Nelson Mandela University, South Africa
Andrea is Chair in Identities and Social Cohesion in Africa, at Nelson Mandela University. Another global scholar, Andrea was awarded PhD in Philosophy from Villanova University, Philadelphia, 2006. Her research focused on bringing complexity-thinking in continental philosophy into contact with psychoanalytic theory, leading to the publication of a book entitled Derrida vis-á-vis Lacan: Interweaving Deconstruction and Psychoanalysis (New York: Fordham University Press, 2008). Presently, her work remains engaged, broadly speaking, in examining the interfaces between philosophy as a way of life in its many dimensions, psychoanalytic thinking, and the development of notions of ethical responsibility within the contemporary paradigmatic shift from “simplicity” to “complexity.”