| Timetable | Parallel Sessions - November 1st |
|---|---|
| 11:00 - 12:30 | Registration & Coffee (if not attending the conference) |
| 12:30 - 13:30 | Opening / lunch with conference participants |
| 13:30-14:15 | MethodsNET Roundtable discussion on AI |
| Session 1a: 14:30 - 16:00 | Integration of Artificial Intelligence in Qualitative Data Analysis: Introduction to an Innovative Practice |
| Session 1a: 14:30 - 16:00 | How Are You Coding? Abductive Coding: from Epistemology to a Set of Tactics for Qualitative Coding Convenors: Virginie Van Ingelgom (UCLouvain) Claire Dupuy (UCLouvain) Maria Theiss (University of Warsaw) Luis Vila-Henninger (Aarhus University) |
| Session 1a: 14:30 - 16:00 | Network Analyses Across Sociology, Political Sciences & Psychology: Methodological Applications & Challenges Convenors: M. Annelise Blanchard (UCLouvain) Vincent Lorant Stephane Bael |
| Session 1a: 14:30 - 16:00 | Mastering Web Scraping for Data Collection Convenors: Aurélien Goutsmedt (UCLouvain) Marine Bardou (UCLouvain) Thomas Laloux (UCLouvain) |
| Session 1a: 14:30 - 16:00 | Participatory Research Methods: Principles, Practices and Challenges Convenors:
Elisabeth Ilboudo Nebie, Arizona State University
Christine Gibb, University of Ottawa
Cai Wilkinson, Deakin University
|
| 16:00 - 16:30 | Coffee Break |
| Session 1b: 16:30 - 18:00 | Mastering Web Scraping for Data Collection Convenors: Aurélien Goutsmedt (UCLouvain) Marine Bardou (UCLouvain) Thomas Laloux (UCLouvain) |
| Session 1b: 16:30 - 18:00 | Participatory Research Methods: Principles, Practices and Challenges Convenors:
Elisabeth Ilboudo Nebie, Arizona State University
Christine Gibb, University of Ottawa
Cai Wilkinson, Deakin University
|
| Session 1b: 16:30 - 18:00 | Network Analyses Across Sociology, Political Sciences & Psychology: Methodological Applications & Challenges Convenors: M. Annelise Blanchard (UCLouvain) Vincent Lorant Stephane Bael |
| Session 1b: 16:30 - 18:00 | How Are You Coding? Abductive Coding: from Epistemology to a Set of Tactics for Qualitative Coding Convenors: Virginie Van Ingelgom (UCLouvain) Claire Dupuy (UCLouvain) Maria Theiss (University of Warsaw) Luis Vila-Henninger (Aarhus University) |
| Timetable | Parallel Sessions - November 2nd |
|---|---|
| Session 2a: 09:00 - 10:30 | Accounting for Heterogeneity in Meta-Analysis Convenors: Caspar van Lissa (Tilburg University) |
| Session 2a: 09:00 - 10:30 | COMPLEX-IT: A Computational, Multi-Methods Platform for Non-Experts to Explore Complex Social Science and Health Data |
| Session 2a: 09:00 - 10:30 | Qualitative Case Study Research and Designs Convenors: Zinette Bergman (University of Basel) Manfred Max Bergman (University of Basel) |
| Session 2a: 09:00 - 10:30 | Social Network Analysis for Change Convenors: Silvia Fierascu (West University of Timisoara) Viorel Proteasa (West University of Timisoara) |
| Session 2a: 09:00 - 10:30 | How Are You Coding? Abductive Coding: from Epistemology to a Set of Tactics for Qualitative Coding Convenors: Virginie Van Ingelgom (UCLouvain) Claire Dupuy (UCLouvain) Maria Theiss (University of Warsaw) Luis Vila-Henninger (Aarhus University) |
| Session 2a: 09:00 - 10:30 | Introduction to Configurational Comparative Analysis using EvalC3 Convenor: Simon Armour (Sheffield Hallam University) Ryan Storey (Sheffield Hallam University) |
| 10:30-11:00 | Coffee Break |
| Session 2b: 11:00 - 12:30 | COMPLEX-IT: A Computational, Multi-Methods Platform for Non-Experts to Explore Complex Social Science and Health Data |
| Session 2b: 11:00 - 12:30 | How Are You Coding? Abductive Coding: from Epistemology to a Set of Tactics for Qualitative Coding Convenors: Virginie Van Ingelgom (UCLouvain) Claire Dupuy (UCLouvain) Maria Theiss (University of Warsaw) Luis Vila-Henninger (Aarhus University) |
| Session 2b: 11:00 - 12:30 | Social Network Analysis for Change Convenors: Silvia Fierascu (West University of Timisoara) Viorel Proteasa (West University of Timisoara) |
| Session 2b: 11:00 - 12:30 | Accounting for Heterogeneity in Meta-Analysis Convenors: Caspar van Lissa (Tilburg University) |
| Session 2b: 11:00 - 12:30 | Introduction to Configurational Comparative Analysis using EvalC3 Convenor: Simon Armour (Sheffield Hallam University) Ryan Storey (Sheffield Hallam University) |
| Session 2b: 11:00 - 12:30 | Qualitative Case Study Research and Designs Convenors: Zinette Bergman (University of Basel) Manfred Max Bergman (University of Basel) |
| 12:30-13:30 | Lunch |
| Session 3a: 13:30 - 15:00 | What are We Actually Tracing in Process Tracing Methods? Exploring Competing Concepts of Process and Mechanisms Convenors: Derek Beach (Aarhus University) Ludvig Norman (Stockholm University) Hilde van Meegdenburg (Leiden University) |
| Session 3a: 13:30 - 15:00 | Expanding Mixed Methods Research and Designs Convenors: Manfred Max Bergman (University of Basel) |
| Session 3a: 13:30 - 15:00 | Common Method Variance: From Myth to Procedural and Statistical Remedies. Exploring Different Methods to Assess the Risk of Common Method Variance in Survey-Based Research Designs Convenors: Corentin Hericher (UCLouvain) Leander De Schutter (VU Amsterdam) |
| 15:00-15:30 | Coffee Break |
| Session 3b: 15:30 - 17:00 | What are We Actually Tracing in Process Tracing Methods? Exploring Competing Concepts of Process and Mechanisms Convenors: Derek Beach (Aarhus University) Ludvig Norman (Stockholm University) Hilde van Meegdenburg (Leiden University) |
| Session 3b: 15:30 - 17:00 | Common Method Variance: From Myth to Procedural and Statistical Remedies. Exploring Different Methods to Assess the Risk of Common Method Variance in Survey-Based Research Designs Convenors: Corentin Hericher (UCLouvain) Leander De Schutter (VU Amsterdam)
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| Session 3b: 15:30 - 17:00 | Expanding Mixed Methods Research and Designs Convenors: Manfred Max Bergman (University of Basel) |
Please note that the content of the above program is subject to change.
| MethodsNET Roundtable discussion on AI Roundtable speakers: Maryline Vivion Levi Littvay | Friday November 1st, Roundtable 13:30 – 14:15 |
| Artificial Intelligence (AI) is increasingly becoming a transformative tool in human sciences research, offering unprecedented capabilities to upgrade existing methodologies. From improving data analysis to enabling more complex behavioral modeling, AI-driven techniques have vast potential. Hybrid research methods can benefit from AI’s computational power, enabling large-scale data analysis while maintaining human judgment for contextual interpretation. The integration of AI will encourage more collaboration across disciplines, such as fostering interdisciplinary research between substantive specialists and data scientists to explore hypothetical future social dynamics. However, the integration of AI into scientific practice also brings challenges and ethical concerns that need to be carefully addressed. Algorithmic bias is a major concern, as well as the complexity and interpretability of AI models, which often remain ‘black boxes.’ Without understanding the underlying mechanisms, it is difficult to ensure transparency and fairness in these models. As a result, the actionable insights provided by AI-driven research face critical ethical scrutiny. In this roundtable discussion, participants will explore the transformative impact of AI on both existing and emerging research methodologies. The conversation will focus on how AI tools and techniques are reshaping data collection, analysis, and interpretation across various fields in social sciences. Key topics will include the role of machine learning in predictive analytics, the integration of AI in research, and the ethical considerations surrounding AI-driven methodologies. | |
| Integration of Artificial Intelligence in Qualitative Data Analysis: Introduction to an Innovative Practice Convenors: Maryline Vivion, Université Laval Alban Da Silva, Université Laval | Friday November 1st, Workshop session 1A 14:30 – 16:00 |
| Artificial intelligence (AI) offers numerous opportunities, particularly for the analysis of qualitative data, and more specifically for thematic content analysis. Thematic content analysis involves systematically transforming a corpus of qualitative data into a number of themes representative of the analyzed content, thus enabling data reduction. This process is long and laborious, requiring significant investments in time and resources as it involves multiple readings of the data corpus. In this regard, AI has the potential to significantly accelerate this process due to its ability to handle large volumes of data and establish connections between disparate elements, thereby improving the quality of the analysis. AI can be trained to recognize and categorize themes within qualitative data corpora, greatly reducing the need for manual coding. This is why the use of AI as an analytical tool is on the rise. Nonetheless, its use for data analysis raises many questions. Several limitations have already been identified. First, concerns related to data confidentiality are raised because the data provided feed the AI, potentially leading to breaches of confidentiality. Moreover, potential biases in the algorithms used to analyze data can generate results that perpetuate or amplify existing biases and inequalities in society. AI hallucination biases, which refer to incorrect or fictitious content generated by AI, are also issues. Another major limitation is the inability to understand how the algorithms arrived at the results, reflecting a lack of transparency. Despite these issues, several tools designed to support qualitative data analysis have been developed, such as ATLAS.ti, which reached an agreement with OpenAI and launched a beta version of its “open coding” feature powered by OpenAI in 2023, which automatically suggests codes from excerpts of a dataset. The integration of AI into QDAS will undoubtedly change approaches to qualitative data analysis. However, these transformations must be accompanied by thoughtful consideration of the advantages and limitations of AI, as well as a critical perspective on the results generated by it. Objective The objective of the workshop is to introduce participants to integrating AI for qualitative data analysis using the software ATLAS.ti. · Understand the advantages and disadvantages of AI-assisted coding · Develop strategies to adjust computer coding to avoid hallucinations, inductive biases, and judgment errors · Identify appropriate uses of artificial intelligence in the processing of qualitative data Target Audience Researchers, academics, professionals, or students involved in qualitative research methods, particularly those involved in thematic content analysis. Software/hardware or other requirements for participants · Workshop participants will be asked to get ATLAS.ti software prior to the workshop. A free trial is available on the ATLAS.ti website. · A fictitious project will be provided as well as sample queries by the workshop organizer. The workshop will be carried out in three phases. First, an overview of the features offered by the software will be presented, followed by training on developing queries for coding interviews. Next, participants will experiment with the AI features by using several queries offered by the software on fictitious interview about climate change. Finally, participants will compare the results generated by the different analyses. Part 1: ATLAS.ti software and the art of developing queries for thematic analysis. Facilitated by Alban Da Silva. In this session, participants will receive an in-depth introduction to the ATLAS.ti software and its functionalities for thematic analysis. The facilitator will guide them through the process of developing queries to effectively code qualitative data. Through practical demonstrations and examples, participants will learn how to navigate the software interface, create codes, and organize data for thematic analysis. Part 2: Exploring AI Capabilities: Analyzing Fictitious Interviews on Climate Change. Facilitated by Maryline Vivion and Alban Da Silva. In this segment, participants will engage in hands-on exploration of AI capabilities using fictitious interview data related to perceptions and attitudes towards climate change. They will be guided through a fictional project scenario where they will utilize the software to apply various AI-assisted coding functions. Sample queries will be provided to participants to facilitate their understanding and application of the software’s features. Part 3: Exchange between participants on the results obtained. Facilitated by Maryline Vivion and Alban Da Silva During the final 20 minutes of the workshop, participants will have the opportunity to share and discuss the results of their coding exercises. Facilitated by the workshop leader, participants will engage in an exchange of insights, observations, and challenges encountered during the coding process. Comparisons will be made between different coding approaches and interpretations, fostering collaborative learning and critical reflection among participants. | |
| Mastering Web Scraping for Data Collection Convenors: Aurélien Goutsmedt, UCLouvain Marine Bardou, UCLouvain Thomas Laloux, UCLouvain | Friday November 1st Workshop session 1A and 1B 14:30 – 16:00 16:30 – 18:00 |
| In this workshop, participants will delve into the world of data scraping. Scraping is the process of extracting different types of data from various sources on the internet. Web scraping is an essential tool for researchers, allowing them to efficiently collect large volumes of data from the internet. This workshop will equip participants with the skills needed to perform web scraping ethically and effectively, significantly enhancing their data collection capabilities. The workshop will be led by three convenors with extensive experience in scraping various types of internet data. The sessions will be interactive, combining presentations, hands-on exercises, and group discussions. Participants will receive ongoing support and feedback throughout the workshop. This workshop is divided into two 90-minute sessions. Session 1: Introduction to Web Scraping The first 90-minute session will introduce the basics of web scraping. No prior knowledge of scraping or programming languages is required. Participants will learn: · What is web scraping? An overview of web scraping and its distinction from public repositories and APIs. · The ethics of web scraping: Important ethical aspects to consider when scraping data, such as how to know if you can scrape a website, how to take into account GDPR, how to avoid overloading a website, etc. · “Languages of the internet”: Basic notions of HTML and CSS, and how to access web page code in browsers. · Web scraping tools in R: Introduction to R packages like rvest, polite, and RSelenium, along with concrete examples. By the end of this session, participants will have a foundational understanding of web scraping and will know how to start learning web scraping and use it in their projects. This session includes complete written tutorials, which enable participants to run scripts independently post-workshop. Session 2: Hands-on Web Scraping The second 90-minute session is designed for participants with at least a basic understanding of R. This hands-on session will involve practical activities using R and web scraping on personal computers. The session will be divided into two parts: 1. Practical examples: Demonstrations of various tasks, including checking scraping restrictions, understanding website and URL structures, and dealing with dynamic websites. 2. Hands-on exercise: Participants will work on specific exercises or their own projects. Two types of exercises with different levels of difficulty will be proposed. The three convenors will assist the participants in these exercises and provide concrete help and advice addressing the different problems encountered by the participants. Technical Requirements For the second 90-minute session, participants should have: · Pre-installed software (R and RStudio) and necessary packages (tidyverse, rvest, polite, and RSelenium) · An internet connection for accessing online resources | |
| Network Analyses Across Sociology, Political Sciences & Psychology: Methodological Applications & Challenges Convenors: M. Annelise Blanchard, UCLouvain Vincent Lorant Stephane Baelee | Friday November 1st Workshop session 1A 14:30 – 16:00 |
| The workshop will be composed of multiple presentations, including space for discussion and questions, about how network analysis is used in specific domains such as sociology, political science, and psychology. In the second session, we will showcase valuable packages for conducting analyses, such as R-igraph and R-ERGM. Interested participants can download these R packages beforehand if they wish to follow along, although this is not required. Workshop content An overview and discussion of why network analysis is interesting (or limited) for psychology, sociology and political sciences. The target audience includes researchers interested in learning about network analyses across fields, and the specific challenges and opportunities of applying them across domains. SNR is the study of the network, an object composed of two ingredients, nodes and ties. These nodes can be scientists (nodes) publishing together (ties), or adolescents (nodes) befriending (tie) each other at school, or web-blogs (nodes)and their cross-references (ties). Nodes can also be institutions having common activities or maintaining social exchanges such as when hospitals (node) refer a patient (tie) to another health service. Social network research is a perspective about social life: actors are interdependent, their ties are channels for exchanging resources, actors’ relationships are structured and not random, and the network provides constraints and resources to the actors. The workshop introduces the landscape of social network research and its building blocks, as well as two case-studies in the domains of political sciences and medical sociology. The workshop then covers how psychology has adapted the same logic of interdependent relationships to understand how symptoms of mental disorders interrelate, but this time by estimating the relationships (ties) between symptoms (instead of graphing known ties, as in SNR) leading to ongoing methodological challenges. Throughout, the workshop will raise thinking points and challenges (both methodological and theoretical) tied to specific examples of network analysis. Specific content covered will include: · Social networks: definitions, methods & applications · The landscape of socio-network research: nodes, groups and dyads. · Social network method: modeling the network vs modeling the consequences of the network · Application/example: Work on online extremist ecosystems · Measuring separation in networks · Networks in psychology research: estimated (not known) edges, and the complications · Centrality & theoretical issues; community detection in psychology networks | |
| How Are You Coding? Abductive Coding: From Epistemology to a Set of Tactics for Qualitative Coding Convenors: Virginie Van Ingelgom, UCLouvain Claire Dupuy, UCLouvain Maria Theiss, University of Warsaw Luis Vila-Henninger, Aarhus University | Friday November 1st Workshop session 1A and 1B 14:30 – 16:00 16:30 – 18:00 Saturday November 2nd Workshop session 2A and 2B 09:00 – 10:30 11:00 – 12:30 |
| Coding qualitative data is a crucial process that involves categorizing and organizing textual information to identify patterns, themes, and concepts. In qualitative data analysis, many researchers anchor their methodological approach to coding – explicitly or not – in grounded theory as developed by Glaser and Strauss (1967). Grounded theory offers a useful set of steps for coding and analyzing qualitative data inductively and has generated rich and insightful bodies of work. This approach was developed based on projects with a relatively small number of interviews, generally conducted and analyzed by a single researcher. Increasingly, however, qualitative studies involve larger amounts of qualitative data (see the literature on Big Qual, for instance, Davidson et al., 2019) and frequently involve teams of people who code based on a shared pool of material. Recent methodological research thereby argues that grounded theory’s crucial principles – theoretical sampling toward saturation, strongly inductive analysis, and full immersion in the research field—bear little resemblance to many researchers’ actual practices (Deterding & Waters, 2018; Vila-Henninger, L., Dupuy, C., Van Ingelgom, V. et al., 2022). From this discrepancy between research principles and new practices arises the issue this workshop focuses on: what avenues are to be taken to analyze and code qualitative data? Logistically, the development of Qualitative Data Analysis (QDA) software – e.g., Atlas.ti, Delve, MaxQDA, NVivo – has been very helpful. However, coding procedures for theory building still mostly draw from grounded theory, inductive principles, while deduction is also part of other researchers’ coding practices. In this context of intense debate over the use of induction versus deduction in qualitative analysis, a third way has been explored: abduction (Timmermans & Tavory, 2012; Tavory & Timmermans, 2014, 2019; Tavory, 2016). This workshop offers a space for innovations in research methods by inviting researchers to reflect on how qualitative coding and abduction in general, and methods of abductive coding in particular, provide a fruitful avenue for qualitative researchers oriented toward theory-building. Abduction is considered from the joint perspective of an epistemology and methods of data analysis. Specifically, the workshop aims to outline a set of tactics for abductive coding based on existing research (e.g., Vila-Henninger, L., Dupuy, C., Van Ingelgom, V. et al., 2022; Dupuy & Van Ingelgom, 2024). The workshop will be structured around two sessions. Session 1: The first session will discuss abduction by focusing on its defining features in relation to induction and deduction and will engage with the main methods for abductive coding by mapping their crucial principles, distinctive characteristics, and existing techniques. Session 2: In the second session, workshop participants will collectively explore the potential and limits of different methods for abductive coding based on their respective research. The workshop welcomes participants interested in abductive coding across different disciplines in the social sciences and beyond, with different experiences in abductive coding (whether in research, in teaching, or based on a general interest), working alone or in teams. Target Audience: Interested participants can submit an abstract (250 words) highlighting how they implement abductive coding in their own research and the methodological foundations for their coding practices. To prepare for the collective dynamic at the heart of this workshop, participants will be invited to send a sample of their coding practices with their thoughts on abductive coding one month prior to the workshop. | |
| Participatory Research Methods: Principles, Practices and Challenges Convenors: Elisabeth Ilboudo Nebie, Arizona State University Christine Gibb, University of Ottawa Cai Wilkinson, Deakin University | Friday November 1st Workshop session 1A and 1B 14:30 – 16:00 16:30 – 18:00 |
| Participatory research methods are founded on an understanding of research as a process of knowledge co-creation that requires the inclusion of the people and communities who have lived experience at all stages of the research process. They have gained increasing traction as researchers have sought to find ways to navigate power inequalities and promote positive social change, becoming well established in fields such as applied anthropology and community development, as well as attracting wider attention from scholars in disciplines including political science, geography, education and health sciences. However, questions remain about the essential principles of participatory research, how to operationalise it effectively, and, crucially, the extent to which it can live up to its aim of making research meaningfully participatory. In this workshop, participants will explore these questions and consider the possibilities and challenges that participatory research methods present. An initial overview of the key principles of participatory research will provide context, along with presentation of examples of research conducted using participatory methods from anthropology and global studies to illustrate the range of techniques that may be used. Discussion will then focus on identifying good practices for participatory research and also addressing the challenges that these methods poses practically, politically and pedagogically. This workshop will consist of two 90-minute sessions. Session 1: In the first session, the principles and examples of participatory research will be discussed, focusing on inclusion, integration of interdisciplinary approaches, and use of technologies and media. Session 2: In the second session, workshop participants will collectively identify good practices for participatory research and explore the challenges of making research meaningfully participatory. Target Audience Researchers at any level from the social and related sciences interested in participatory research methods. Some qualitative methods experience is recommended, but experience of using participatory research methods, while welcome, is not required. To help provide a common starting point for discussion, participants will be provided with suggested preparatory readings. | |
| Accounting for Heterogeneity in Meta-Analysis Convenor: Caspar van Lissa, Tilburg University | Saturday November 2nd Workshop session 2A and 2B 09:00 – 10:30 11:00 – 12:30 |
| Conventional meta-analysis methods require studies to be close or exact replications. In real-life applications, this rarely happens. Instead, different studies investigate the same research questions in different populations using various study designs and measurement instruments. You need a method to account for these between-study differences. This workshop teaches participants how to perform meta-analysis according to contemporary best practices using free open-source software (R). It introduces the basic statistical models for meta-analysis, with particular attention devoted to quantifying and explaining heterogeneity in effect sizes. We discuss several cases: 1. Accounting for heterogeneity using a random-effects model 2. Coding between-study differences as moderators and controlling for their influence using meta-regression 3. Using machine learning methods (LASSO regression and random forests) to select relevant moderators 4. Aggregating conceptual replication studies using the Product Bayes Factor Objective To equip participants with all the tools they need to conduct a meta-analysis of heterogeneous studies (e.g., diverse papers about a similar topic). Technical Content Participants learn to conduct meta-analysis using the metafor (random effects meta-analysis), MetaForest (random forests moderator selection), pema (Bayesian LASSO-penalized meta-regression), and bain (Product Bayes Factor) packages. Software Requirements Participants will receive a tutorial on how to install the necessary software (R and RStudio) before the workshop. Target Audience All scholars intending to conduct a meta-analysis (e.g., in social sciences, biomedical sciences, environmental sciences). Workshop Process Participants are encouraged to bring real data for the worked examples so they can start on their applied analyses. Demo data are available for those who do not yet have their own data. Each 90-minute session begins with a 20-minute introductory lecture, followed by 10 minutes of Q&A. Then there are two 30-minute exercise blocks, guided by an online coursebook with instructions, code, and formative self-assessment questions. The workshop chair will walk around to support students. The last 10 minutes of each exercise block consist of discussion and peer feedback to resolve any sticking points. Presentations The first 30-minute presentation covers the basic models for meta-analysis (fixed-effect and random-effects analysis), meta-regression, and Bayesian penalized meta-regression. The second 30-minute presentation covers random forest meta-analysis and the Product Bayes Factor. Moderation Approach After the exercise blocks, the workshop chair facilitates knowledge exchange among participants so they can resolve each other’s sticking points. Only as a last resort does the chair step in to provide answers. Note to participants: Please prepare your laptops and data for the workshop via this link https://cjvanlissa.github.io/meta_workshop/tutorial.html | |
| COMPLEX-IT: A Computational, Multi-Methods Platform for Non-Experts to Explore Complex Social Science and Health Data Convenor: Brian Castellani, Durham University | Saturday November 2nd Workshop session 2A and 2B 09:00 – 10:30 11:00 – 12:30 |
| While the complexity sciences offer a new approach to thinking about social and health data, using their computational methods can be considerably challenging for non-experts—particularly postgraduate students, applied researchers, policy evaluators, and civil servants. There is a solution! This workshop will introduce COMPLEX-IT, a free online R-platform designed for non-experts to employ the latest developments in machine learning, data visualization, participatory systems mapping, network analysis, simulation, data forecasting, and cluster analysis. A major strength of COMPLEX-IT is that it can work with a variety of data types, including qualitative QCA data. In our workshop, we will explore a real-world data set to walk through the steps of using COMPLEX-IT to show how these tools can help attendees gain new insights into social and health data. The goal is for participants to leave with a new methods platform they can use in their own work. Introduction to Computational Modeling and the challenges of using these methods in the social and health sciences Overview of Case-Based Modeling and Case-Comparative methods Introduction to COMPLEX-IT Review of case study for workshop Step-by-step run-through on using COMPLEX-IT Participants are encouraged to bring their computers to this workshop and, if they want, some test data from their own work. Participants are also encouraged, prior to the workshop, to take a look at the COMPLEX-IT website and tutorials at https://www.complex-it-data.org/. | |
| Qualitative Case Study Research and Designs Convenors: Zinette Bergman, University of Basel Manfred Max Bergman, University of Basel | Saturday November 2nd Workshop session 2A and 2B 09:00 – 10:30 11:00 – 12:30 |
| Case study research has been a cornerstone of social science research methods for over a century. Despite its widespread use across various disciplines, this method is often misunderstood, challenging to implement, and often perceived as lacking rigor. To avoid these pitfalls, researchers tend to narrow their case study design and application, adhering to strict approaches including that of Robert Yin or process tracing. While these approaches serve researchers well within their constraints, alternative forms of case study research exist, specifically, if research contexts are complex, unstable, and rapidly evolving. Such alternative approaches to case study research require a broad and diverse skill set, along with the ability to adapt research design, data collection, and analysis methods. In this workshop, we will present a typology of different case study methodologies, exploring their possibilities and consequences. Participants will be introduced to case study as a standalone research design and a component of more complex designs. Drawing on the Chicago School of Sociology and methodological approaches Robert Stake and Sharon Merriam, we will illustrate how a case study encompasses (a) a distinct type of research approach, (b) a process for conducting research, and (c) the product of an empirical inquiry – the case itself. Through this exploration, participants will not only become acquainted with the diverse tools and strategies this method offers but also understand how different case study approaches can be utilized to conduct systematic, culture-specific, and context-relevant research. Additionally, we will introduce the concept of positive case studies, demonstrating how they can form a break with current practices in social science research and applications. This workshop will consist of two 90-minute sessions. Session 1 Part A: Introduction to the basics of case study, followed by Q&A Part B: Case study research design, including simple and complex design strategies Session 2 Part A: Different types of designs and their associated advantages and disadvantages Part B: Integration of case study research in more complex designs; positive case studies Target Audience Researchers from the social and related sciences interested in case study research beyond causal case studies/process tracing. Some qualitative methods experience is recommended. Technical content, software/hardware, or other requirements for participants None Role of Contributors Session 1, Part 1: Zinette Bergman Session 1, Part 2: Manfred Max Bergman Session 2, Part 1: Zinette Bergman Session 2, Part 2: Manfred Max Bergman and Zinette Bergman | |
| Social Network Analysis for Change Convenors: Silvia Fierascu, West University of Timisoara Viorel Proteasa, West University of Timisoara | Saturday November 2nd Workshop session 2A and 2B 09:00 – 10:30 11:00 – 12:30 |
| More than 80% of change initiatives in organizations, whether public or private, fail. In social communities, the rate of change is even slower and less successful. Social Network Analysis (SNA) is a very promising approach to change management in organizations and community-building. It is a comprehensive, democratic, people-focused methodology that often represents the missing link between an organization or community’s vision and mission, a link that is value-driven first. Understanding and applying Social Network Analysis for change can help organizations and communities manage change initiatives with much more efficiency, closer to their values and with the right people at the decision-making table, whether those changes are related to organizational development, community-building, or public policy. Social Network Analysis is a method used to map and measure relationships and flows between people, groups, and organizations. When applied to change management, SNA can provide critical insights into how information, influence, and trust are distributed within an organization or a community, thereby identifying key actors, bottlenecks, and opportunities for effective change implementation. In this workshop, we propose an interactive learning experience on applying SNA for change management. We will examine specific real cases of change initiatives in organizations, distributed networks, and urban communities where SNA was effectively applied to harness these initiatives. Participants will learn how to develop ethical data collection instruments, work with sensitive network data, analyze and process data to provide relevant insights for informed decision-making, and design effective change management processes for organizations and/or social communities. No hardware or software is required for this workshop. Target Audience Researchers at any level of seniority who are working with public or private practitioners, communities, or organizations. Session 1: ONA Theory and Practice Introductions (20 mins) (Silvia and Viorel) About Applied Network Science (10 mins) (Viorel) Organizational Network Analysis – Key Concepts (20 mins) (Silvia) Organizational Network Analysis – Applications (20 mins) (Silvia) Q&A (20 mins) (All) Session 2: ONA Exercises Group Formation and Setup (10 mins) (Viorel) Parallel Groups Case Work – Analysis (20 mins) (Silvia and Viorel) Parallel Groups Case Work – Solutions (20 mins) (Silvia and Viorel) Plenary Group Debrief (20 mins) (Silvia) Discussions & Conclusions (20 mins) (Silvia and Viorel) | |
| Introduction to Configurational Comparative Analysis using EvalC3 Convenors: Simon Armour, Sheffield University Ryan Storey, Sheffield University | Saturday November 2nd Workshop session 2A and 2B 09:00 – 10:30 11:00 – 12:30 |
| Configurational comparative analysis provides a means to explore how multiple attributes of complex human systems, categorised qualitatively or qualitatively, may interact to predict identified outcomes, through systematic comparison of cases. While qualitative comparative analysis (QCA) is the best-known method of configurational analysis, there are alternatives. One of these is EvalC3 (developed by Rick Davies), now available as a web app. EvalC3 is free for researchers to utilise in their work. It provides a selection of search algorithms, as well as the ability to manually design and test hypotheses, plus user friendly visualisations of findings in the form of Decision Trees and multiple model performance measures. This workshop will introduce participants to EvalC3 and its outputs, drawing on our early experiences of using it in our evaluation of Sport England funded place-based systemic approaches to reducing inequalities in physical activity. We will demonstrate use of the software, including opportunities for hands-on practice, using sample datasets. Target Audience The workshop will be of interest to any researchers who are interested in exploring configurational understandings of causal mechanisms in complex adaptive systems. Workshop structure The first part of the workshop will include an introduction to our evaluation of place-based systemic approaches to inequalities in physical activity and an explanation of how and why we are using EvalC3 in this work. This will include presentations to introduce our work including how and why CCA is useful in responding to the challenges of evaluating such approaches in the contexts of complex systems. We will share examples of outputs produced and explore with workshop participants how these are being interpreted, working in interactive groups. The second session will provide an overview of EvalC3online and demonstration of the steps and options for designing, evaluating and searching the data for models, and the interpretation of decision-tree models. Participants will be invited to work in groups to practice using the software, using sample data provided. We will review decision-tree models produced and discuss the interpretation of these, before closing with reflections on the uses of this software, and the opportunity for further questions. | |
| What are We Actually Tracing in Process Tracing Methods? Exploring Competing Concepts of Process and Mechanisms Convenors: Derek Beach, Aarhus University Ludvig Norman, Stockholm University Hilde van Meegdenburg, Leiden University | Saturday November 2nd Workshop session 3A and 3B 13:30 – 15:00 15:30 – 17:00 |
| This workshop brings together methodological experts to discuss different interpretations of what ‘process’ or ‘mechanisms’ being traced in process tracing methods are. There have been considerable advances regarding the ‘tracing’ side of process tracing methods, especially regarding the use of Bayesian logic and more interpretive methods. However, there has been considerably less work done on how to theorize the processes being traced. While process tracers agree that drawing an arrow between a cause and outcome is not enough to provide a causal explanation of the linkage, there is less agreement about the type of conceptual language that can be used to theorize causal processes and mechanisms. Some scholars suggest that process or mechanistic theories can be conceptualized as a series of one or more mechanisms (e.g., ‘societal mobilization’), whereas others disaggregate processes into a series of actors engaging in activities. The intention of the workshop is to engage in practical discussions about what the minimum requirements are for a ‘good’ process/mechanistic theory, drawing on different understandings of processes and mechanisms, and using practical examples from published research. Note that the workshop is not intended to be a philosophical debate about ontological issues about the nature of causation. Instead, the aim is to address questions such as: · What are the limits and benefits of different conceptual frameworks related to process and mechanism? · How, through which designs and techniques, can we capture the causal linkages of a process? · How can we generate and communicate theoretical understandings of how process/mechanism(s) link cause and outcome, also across different methodological traditions? · How and to what ends can processes and mechanisms be studied empirically and compared across cases? Target audience The audience is anyone interested in case study methods, and more broadly in theoretical advances. | |
| Expanding Mixed Methods Research and Design Convenor: Manfred Max Bergman, University of Basel | Saturday November 2nd Workshop session 3A and 3B 13:30 – 15:00 15:30 – 17:00 |
| The first part of this half-day workshop will cover the basics of mixed methods research designs, including core designs, sampling strategies, advantages and disadvantages, and justifications for mixed methods research. In the second part, the workshop will delve into details of integration, the glue that keeps different method components together, which include mixed methods research questions, sampling strategies, and joint displays. The final part will cover complex mixed methods designs, expanding mixed methods theory and applications, as well as presentation and publication strategies for complex mixed methods projects. | |
| Common Method Variance: From Myth to Procedural and Statistical Remedies. Exploring Different Methods to Assess the Risk of Common Method Variance in Survey-Based Research Designs Convenors: Corentin Hericher, UCLouvain Leander De Schutter, VU Amsterdam | Saturday November 2nd Workshop session 3A and 3B 13:30 – 15:00 15:30 – 17:00 |
| The workshop will focus on the risks of common method variance (CMV) in survey-based behavioral research. The first part of the workshop (15 minutes) will be dedicated to understanding what CMV is and discussing debates around its mere existence (e.g., Richardson et al., 2009; Spector, 2006). In the second part of the workshop (15 minutes), regardless of the existing debates, we will discuss procedural remedies aimed at preventing the risks of CMV in survey-based research, such as the division of data collection by time, persons, and locations (e.g., Podsakoff et al., 2003). Procedural remedies have inherent strengths, weaknesses, and practical limitations. Third, we will address statistical remedies (60 minutes) for CMV, all post hoc analyses based on confirmatory factor analyses (CFA) to detect risks of CMV: the CFA marker technique and the unmeasured latent factor construct (ULMC) technique. For the ULMC technique, we will introduce the ConMET package for R (De Schutter, 2021), a package designed to conduct nested CFAs and contains the ULMC CMV test. Then, using an existing database, we will conduct tests using R scripts containing codes for both the ULMC and CFA marker techniques, to understand the pros and cons of each method. Because the ULMC tests will yield a positive result, we will explore additional tests to understand whether the threat is serious or not. The first and second parts of the workshop will be more theoretical, with slides presenting debates and procedural remedies, featuring practical examples in research. The second part of the workshop will also use some slides but will require participants to bring their laptops so that they can conduct the tests with us. The tests will require R and three packages: haven, lavaan, and ConMET. The database and scripts will be provided to participants before the workshop. Leander De Schutter will handle the technical and statistical discussions, while Corentin Hericher will lead the workshop and provide explanations about debates and remedies. | |