🌻 Causal mapping teams globally – since 2020

20 Feb 2026

Causal mapping teams globally (last 15 years: 2011-2026)#

Inclusion rule used here: records from 2011 onward that are clearly causal-mapping work (or close adjacent approaches used to build causal maps), starting from zotero-bib and then filtering out obvious noise.

Date of most recent publication	Team members	Location / institution	Papers (title, year, citekey)	What they call the approach	Key methods / fit to categorisation / AI use	Primary evidence source mode	Multi-source handling style	Maturity / status	Tooling stack
2026	Vanessa Hammond; Joseph Lea (plus collaborators)	City of Casey, Melbourne (Australia) context; institution not explicit in record	Where to Start? Participatory Systems Mapping for Place-Based Service Integration in the City of Casey (2026) `Hammond et al. (2026)`	Participatory Systems Mapping (PSM)	Group co-production of causal loop maps; strong fit with group map-building and complexity-aware analysis; uses network metrics + Action Scales; no direct AI in method	Group workshops	Aggregated group map with facilitated consensus	Preprint	Workshop facilitation + network analysis
2025	Steve Powell; Gabriele Caldas Cabral; Fiona Remnant; James Copestake; Heather Britt; Rebekah Avard; co-authors	Causal Map / Causal Pathways ecosystem; some records do not specify formal affiliations	AI-assisted Causal Mapping: A Validation Study (2025) `Powell & Caldas Cabral (2025)`; Qualitative Causal Mapping in Evaluations (2025) `Remnant et al. (2025)`; Strengthening Outcome Harvesting with AI-assisted Causal Mapping (2025) `Britt et al. (2025)`; Causal Mapping for Evaluators (2024) `Powell et al. (2024)`; An M&E Time Machine (2024) `Powell et al. (2024)`; Does Our Theory Match Your Theory? (2023) `Powell et al. (2023)`; Measuring the Women’s Economic Empowerment... testing QuIP (2022) `Avard et al. (2022)`; Chapter 1 Overview \| Guide to Causal Mapping (2022) `Powell et al. (2022)`; Guide to Causal Mapping (2021) `Powell & Ltd. (2021)`; From Narrative Text to Causal Maps (2021) `Remnant (2021)`	Causal mapping; AI-assisted causal mapping; causal QDA; QuIP evidence synthesis	Strong fit with document/interview coding, open elicitation, provenance-explicit multi-source synthesis; explicit separation of evidence assembly vs evaluative judgement; substantial AI support for low-level coding/extraction	Narrative interviews, documents, mixed	Explicit provenance and source-thread logic; map-as-evidence-repository approach	Peer-reviewed + chapter + guidance + report + preprint	Causal Map software + LLM-assisted coding/extraction
2025	Jordan White; Pete Barbrook-Johnson	Institute for New Economic Thinking (University of Oxford); CECAN / University of Surrey	Guidance on Using Large Language Models to Extract Cause-and-Effect Pairs from Texts for Systems Mapping (2025) `White & Barbrook-Johnson (n.d.)`	Systems mapping with LLM extraction	Fit with document coding + semi-automation; uses LLM prompts to extract cause-effect pairs then build preliminary maps for later human refinement	Documents/text corpora	Aggregated extraction over multiple texts; human validation step	Report/guidance	GPT-based extraction + external mapping tools (e.g., PRSM)
2024	Fran Ackermann; Colin Eden; James Alexander; Eunice Maytorena-Sanchez	Project studies / management lineage; institutions not explicit in these records	Overlooked and Underused? (2024) `Ackermann & Maytorena-Sanchez (2024)`; Researching Complex Projects (2016) `Ackermann & Alexander (2016)`; Using Causal Mapping to Support Information Systems Development (2011) `Ackermann & Eden (2011)`	Causal mapping for projects and IS development	Fit with individual/group elicitation, document-supported mapping, and idiographic systemic analysis; strong continuity from 2011 to 2024; AI not central	Interviews, workshops, documents	Comparative and synthetic use across sources	Peer-reviewed articles	Decision Explorer / Group Explorer + manual coding
2023	Rory Hooper; Nihit Goyal; Kornelis Blok; Lisa Scholten	Institution not explicit in record (policy evidence synthesis context)	A Semi-Automated Approach to Policy-Relevant Evidence Synthesis (2023) `Hooper (2023)`	Semi-automated causal mapping for policy evidence synthesis	Hybrid NLP + causal mapping + graph analytics; fit with document coding and multi-source synthesis; AI used directly for extraction pipeline	Policy/research documents	Aggregated multi-document synthesis	Preprint	NLP pipeline + graph analytics + causal-map post-processing
2025	Philippe Giabbanelli; Tyler Gandee; Ameeta Agrawal; Niyousha Hosseinichimeh	Applied ontology / systems mapping	Benchmarking and Assessing Transformations Between Text and Causal Maps via Large Language Models (2025) `Giabbanelli et al. (2025)`	Text-to-map and map-to-text for causal maps	Benchmarking and evaluation datasets for LLM transformation between prose and causal maps; AI core method	Documents and causal-map corpora	Multi-dataset benchmark aggregation	Peer-reviewed article	LLMs + benchmark notebooks/metrics
2025	Melissa Valdivia Cabrera; Michael Johnstone; Joshua Hayward; Kristy Bolton; Douglas Creighton	Community health systems modelling	Integration of Large-Scale Community-Developed Causal Loop Diagrams... NLP Approach (2025) `Valdivia Cabrera et al. (2025)`; foundational merge workflow in `Hayward et al. (2020)`	NLP-assisted CLD factor merging	Semantic similarity / NLP used to merge community-generated CLD factors at scale; strong fit with multi-source map integration	Participatory CLDs + associated text labels	Aggregated map integration across communities	Peer-reviewed articles	NLP semantic matching + network analysis/DEMATEL
2024	Raquel Buzogany; Birgit Kopainsky; Paulo Goncalves	System Dynamics Review / policy narrative analysis	Developing Theoretically Grounded Causal Maps to Examine and Improve Policy Narratives (2024) `Buzogany et al. (2024)`	Theoretically grounded causal maps / CLDs	Grounded-theory coding from qualitative corpora into CLDs; fit with document coding and policy narrative synthesis	Policy and academic texts	Aggregated cross-domain causal synthesis	Peer-reviewed article	Qualitative coding + CLD modelling
2024	Mohammad S. Jalali; Ali Akhavan	System Dynamics Review	Integrating AI Language Models in Qualitative Research (2024) `Jalali & Akhavan (2024)`	AI-assisted replication of interview analysis	ChatGPT-assisted replication of interview-to-CLD analysis; AI used as augmentative analyst	Interview transcripts	Replication against prior coded analyses	Peer-reviewed article	ChatGPT-assisted qualitative coding
2023	Charlotte Matthews; Will Airey; Fiona Remnant; Aurelie Charles	University of Bath / local SDG evaluation context	The Dynamics of the UN Voluntary Local Review Using Causal Mapping... (2023) `Matthews et al. (2023)`	Causal mapping for SDG VLR analysis	Cross-SDG causal mapping to identify leverage points and stakeholders in local policy; fit with document + stakeholder synthesis	VLR documents + stakeholder evidence	Within-goal and across-goal map synthesis	Applied report	Causal Map workflow + policy analysis
2022	Pete Barbrook-Johnson; Alexandra Penn; Helen Wilkinson; Dione Hills (overlapping collaborators)	UK policy/evaluation systems-mapping community (institutions not always explicit in these records)	Participatory Systems Mapping for Complex Energy Policy Evaluation (2021) `Barbrook-Johnson & Penn (2021)`; Building a System-Based Theory of Change Using Participatory Systems Mapping (2021) `Wilkinson et al. (2021)`; Participatory Systems Mapping (2022) `Barbrook-Johnson & Penn (2022)`; Running Systems Mapping Workshops (2022) `Barbrook-Johnson & Penn (2022)`; Participatory Systems Mapping in Action (2020) `Mapping & Incentive (2020)`	Participatory systems mapping; system-based ToC	Strong fit with group map-building, open elicitation, and translation from cyclic systems maps to evaluable ToC submaps; AI generally not central in core 2021-2022 method papers	Group workshops (plus some supporting docs)	Consensus-built maps with subgroup/submap analysis	Peer-reviewed + handbook chapters + practice case	Workshop facilitation + network/submap analysis
2022	Jie Yang; Soyeon Caren Han; Josiah Poon	AI-NLP causality extraction community	A Survey on Extraction of Causal Relations from Natural Language Text (2022) `Yang et al. (2022)`	Causal relation extraction from text	Survey of knowledge-based, ML, and deep-learning pipelines for extracting cause-effect links; strong document coding / text-to-causal-link relevance	Text corpora	Cross-dataset method synthesis	Peer-reviewed article	NLP extraction pipelines
2020	Luke Craven (method lineage)	Systems/evaluation research	System Effects: A Hybrid Methodology for Exploring the Determinants of Food In/Security (2017) `Craven (2017)`; Improving the Health, Wellbeing... (2020) `Craven (2020)`	System Effects (hybrid SSM + FCM + graph analysis)	Fit with participant-derived maps + aggregate structural analysis across cases; no direct AI core component	Interviews/workshops + synthesis	Aggregated comparative map structures	Peer-reviewed + applied report	FCM + graph-theoretic analysis
2020	Steven E. Wallis (plus prior collaborators in IPA lineage)	Institution not explicit in record	Integrative Propositional Analysis for Developing Capacity... (2020) `Wallis (2020)`	Integrative Propositional Analysis (IPA)	Causal propositions mapped and scored structurally (breadth/systemicity); fits analysis-heavy map evaluation rather than pure elicitation; AI not central	Strategic documents/propositions	Integrated conceptual synthesis	Peer-reviewed article	Manual proposition extraction + structural metrics
2020	Sasha Strelnikoff; Aruna Jammalamadaka; Dana Warmsley	Institution not explicit in record	Causal Maps for Multi-Document Summarization (2020) `Strelnikoff et al. (2020)`	Causal maps for multi-document summarization	Fully unsupervised NLP pipeline for cause-effect extraction and clustering; fits document coding at scale with explicit AI/NLP core	Multi-document corpora	Aggregated large-scale document synthesis	Peer-reviewed conference paper	DeepCx + embeddings + mixture model + graph pruning
2018	Igor Pyrko; Viktor Dorfler	Management/organization research context	Using Causal Mapping in the Analysis of Semi-structured Interviews (2018) `Pyrko & Dorfler (2018)`	Eden/Ackermann-style causal mapping for interview analysis	Strong fit with interview coding, map merging across respondents, and feedback-chain analysis; AI not central	Semi-structured interviews	Merged intersubjective maps from individual interview maps	Conference proceedings paper	Manual coding + map-merging analysis
2018	Ricardo Wilson-Grau; Heather Britt	Outcome Harvesting practice community	Outcome Harvesting Principles in Practice (2018) `Wilson-Grau (2018)`; Outcome Harvesting (2012) `Wilson-Grau & Britt (2012)`	Outcome Harvesting (adjacent causal-claim approach)	Adjacent method for harvesting causal contribution claims from narrative evidence; fits multi-source evidence assembly; typically no AI core	Narrative outcomes/interviews/documents	Multi-source claim harvesting	Guidance/practice documents	Manual harvesting/coding
2017	Gerard Hodgkinson; Kristian Sund; Robert Galavan	Managerial and organizational cognition community	Chapter 1: Exploring Methods in Managerial and Organizational Cognition (2017) `Hodgkinson et al. (2017)`	Causal/cognitive mapping methods in MOC	Methodological synthesis of causal mapping in management cognition; mainly interview/document elicitation + map analysis tradition; AI not central	Interviews/documents (methodological review)	Comparative methodological synthesis	Book chapter	Method framework synthesis
2016	Mauri Laukkanen; Mingde Wang; Päivi Eriksson	Comparative causal mapping lineage (management/organization)	Comparative Causal Mapping: The CMAP3 Method (2016) `Laukkanen & Wang (2016)`; New Designs and Software for Cognitive Causal Mapping (2013) `Laukkanen & Eriksson (2013)`; Comparative Causal Mapping and CMAP3 Software in Qualitative Studies (2012) `Laukkanen (2012)`	Comparative Causal Mapping (CCM), CMAP3	Core comparative/aggregative map methodology, including standardized concept pools and software-supported cross-case comparison; AI not central	Interviews/documents (structured to low-structured variants)	Comparative aggregation across multiple respondents/cases	Book + peer-reviewed articles	CMAP3 + manual standardization
2014	Michal Sedlacko; Andre Martinuzzi; Inge Ropke; Nuno Videira; Paula Antunes	Sustainability / ecological economics context	Participatory Systems Mapping for Sustainable Consumption (2014) `Sedlacko et al. (2014)`	Participatory systems mapping	Early strong participatory systems-mapping method paper; fits group map-building and systemic insight generation; AI not central	Participatory workshops	Group-built causal map synthesis	Peer-reviewed article	Workshop methods + map analysis

Notes on team boundaries#

Teams are grouped by overlapping authors and clear method lineage; single-paper rows are kept where overlap is weak or absent.
Duplicates were collapsed where records represent the same output (for example Powell & Caldas Cabral (2025) vs Powell & Cabral (2025)).
Obvious noisy keyword matches (items tagged causal mapping but not materially about causal-mapping methods) were excluded.

From your supplied list: explicitly not in this table (and why)#

Pre-2011 foundational classics (kept out only due to 15-year scope): e.g., Axelrod 1976, Eden 1988/1992, Eden/Ackermann/Cropper 1992, Narayanan/Armstrong 2004, Clarkson/Hodgkinson 2005.
Outside causal-mapping core despite causal relevance: e.g., Pearl 2000, Forrester 1971, Tolman 1948, Wright 1921 (important background, but not causal-mapping method teams).
General AI/qualitative-method papers with weak direct mapping focus: retained only when explicitly tied to causal-map/CLD production or transformation.

References

Ackermann, & Eden (2011). Using Causal Mapping to Support Information Systems Development.

Ackermann, & Alexander (2016). Researching Complex Projects: Using Causal Mapping to Take a Systems Perspective. https://linkinghub.elsevier.com/retrieve/pii/S0263786316300072.

Ackermann, & Maytorena-Sanchez (2024). Overlooked and Underused? The Benefits and Challenges of Using Causal Mapping for Project Studies. https://doi.org/10.1016/j.plas.2024.100161.

Avard, Mukuru, & Liesner (2022). Measuring the Women’s Economic Empowerment Generated by Impact Investing; Testing the QuIP Method on an Investment in Uganda’s Cotton Sector. Taylor \& Francis.

Barbrook-Johnson, & Penn (2021). Participatory Systems Mapping for Complex Energy Policy Evaluation. http://dx.doi.org/10.1177/1356389020976153.

Barbrook-Johnson, & Penn (2022). Participatory Systems Mapping. In Systems Mapping: How to Build and Use Causal Models of Systems. https://doi.org/10.1007/978-3-031-01919-7_5.

Barbrook-Johnson, & Penn (2022). Running Systems Mapping Workshops. In Systems Mapping: How to Build and Use Causal Models of Systems. https://doi.org/10.1007/978-3-031-01919-7_10.

Britt, Powell, & Cabral (2025). Strengthening Outcome Harvesting with AI-assisted Causal Mapping. https://5a867cea-2d96-4383-acf1-7bc3d406cdeb.usrfiles.com/ugd/5a867c_ad000813c80747baa85c7bd5ffaf0442.pdf.

Buzogany, Kopainsky, & Gonçalves (2024). Developing Theoretically Grounded Causal Maps to Examine and Improve Policy Narratives about Global Challenges. https://doi.org/10.1002/sdr.1788.

Craven (2017). System Effects: A Hybrid Methodology for Exploring the Determinants of Food In/Security. https://www.tandfonline.com/doi/full/10.1080/24694452.2017.1309965.

Craven (2020). Improving the Health, Wellbeing , and Chronic Disease Management of the Arabic Speaking Community Data - Through the Culture Well Project , Asthma Australia.

Giabbanelli, Gandee, Agrawal, & Hosseinichimeh (2025). Benchmarking and Assessing Transformations Between Text and Causal Maps via Large Language Models. SAGE Publications. https://doi.org/10.1177/15705838241304102.

Hammond, Lea, & Hammond (2026). Where to Start? Participatory Systems Mapping for Place-Based Service Integration in the City of Casey. https://doi.org/10.20944/preprints202601.2371.v1.

Hayward, Morton, Johnstone, Creighton, & Allender (2020). Tools and Analytic Techniques to Synthesise Community Knowledge in CBPR Using Computer-Mediated Participatory System Modelling. https://www.nature.com/articles/s41746-020-0230-x.

Hodgkinson, Sund, & Galavan (2017). Chapter 1: Exploring Methods in Managerial and Organizational Cognition: Advances, Controversies, and Contributions. In New Horizons in Managerial and Organizational Cognition. https://doi.org/10.1108/S2397-52102017002.

Hooper (2023). A Semi-Automated Approach to Policy-Relevant Evidence Synthesis: Combining Natural Language Processing, Causal Mapping, and Graph Analytics for Public Policy. https://doi.org/10.21203/rs.3.rs-3285731/v1.

Jalali, & Akhavan (2024). Integrating AI Language Models in Qualitative Research: Replicating Interview Data Analysis with ChatGPT. https://doi.org/10.1002/sdr.1772.

Laukkanen (2012). Comparative Causal Mapping and CMAP3 Software in Qualitative Studies. https://doi.org/10.17169/fqs-13.2.1846.

Laukkanen, & Eriksson (2013). New Designs and Software for Cognitive Causal Mapping. https://www.emerald.com/insight/content/doi/10.1108/QROM-08-2011-1003/full/html.

Laukkanen, & Wang (2016). Comparative Causal Mapping: The CMAP3 Method. Routledge.

Mapping, & Incentive (2020). Participatory Systems Mapping in Action —Supporting the Evaluation of the Renewable Heat Incentive.

Matthews, Airey, Remnant, & Charles (2023). The Dynamics of the UN Voluntary Local Review Using Causal Mapping within and across the Sustainable Development Goals: A Case Study of Bath and North East Somerset.

Powell, & Ltd. (2021). Guide to Causal Mapping. https://info.causalmap.app/.

Powell, Remnant, Copestake, Mishan, Arvard, & Goddard (2022). Chapter 1 Overview | Guide to Causal Mapping. https://causalmap.app.

Powell, Larquemin, Copestake, Remnant, & Avard (2023). Does Our Theory Match Your Theory? Theories of Change and Causal Maps in Ghana. In Strategic Thinking, Design and the Theory of Change. A Framework for Designing Impactful and Transformational Social Interventions.

Powell, Copestake, & Remnant (2024). Causal Mapping for Evaluators. https://doi.org/10.1177/13563890231196601.

Powell, Cabral, & Mishan (2024). An M\&E Time Machine: Using AI to Measure Changes in a System across a Time Period on Features Which Only Emerge during It.. https://doi.org/10.31124/advance.171535113.38566027/v1.

Powell, & Caldas Cabral (2025). AI-assisted Causal Mapping: A Validation Study. Routledge. https://doi.org/10.1080/13645579.2025.2591157.

Powell, & Cabral (2025). AI-assisted Causal Mapping: A Validation Study. Routledge. https://www.tandfonline.com/doi/abs/10.1080/13645579.2025.2591157.

Pyrko, & Dorfler (2018). Using Causal Mapping in the Analysis of Semi-structured Interviews. https://doi.org/10.5465/AMBPP.2018.14348abstract.

Remnant (2021). From Narrative Text to Causal Maps- QuIP Analysis and Visualisation 24 Oct 2021.

Remnant, Copestake, Powell, & Channon (2025). Qualitative Causal Mapping in Evaluations. In Handbook of Health Services Evaluation: Theories, Methods and Innovative Practices. https://doi.org/10.1007/978-3-031-87869-5_12.

Sedlacko, Martinuzzi, Røpke, Videira, & Antunes (2014). Participatory Systems Mapping for Sustainable Consumption: Discussion of a Method Promoting Systemic Insights. Elsevier.

Strelnikoff, Jammalamadaka, & Warmsley (2020). Causal Maps for Multi-Document Summarization. https://doi.org/10.1109/BigData50022.2020.9377731.

Valdivia Cabrera, Johnstone, Hayward, Bolton, & Creighton (2025). Integration of Large-Scale Community-Developed Causal Loop Diagrams: A Natural Language Processing Approach to Merging Factors Based on Semantic Similarity. https://doi.org/10.1186/s12889-025-22142-3.

Wallis (2020). Integrative Propositional Analysis for Developing Capacity in an Academic Research Institution by Improving Strategic Planning. https://doi.org/10.1002/sres.2599.

White, & Barbrook-Johnson (n.d.). Guidance on Using Large Language Models to Extract Cause-and-Effect Pairs from Texts for Systems Mapping Jordan White1 and Pete Barbrook-Johnson1,2 1 Institute for New Economic Thinking, University of Oxford 2 Centre for the Evaluation of Complexity Across the Nexus, University of Surrey.

Wilkinson, Hills, Penn, & Barbrook-Johnson (2021). Building a System-Based Theory of Change Using Participatory Systems Mapping. SAGE Publications Ltd. https://doi.org/10.1177/1356389020980493.

Wilson-Grau, & Britt (2012). Outcome Harvesting.

Wilson-Grau (2018). Outcome Harvesting: Principles, Steps, and Evaluation Applications. IAP.

Yang, Han, & Poon (2022). A Survey on Extraction of Causal Relations from Natural Language Text. https://doi.org/10.1007/s10115-022-01665-w.