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GeezerVison is showing truecauses.org — Structured Democratic Dialogue – The research behind True Causes

True Causes
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Structured Democratic Dialogue – The research behind True Causes

True Causes is built on Structured Democratic Dialogue, the method that grew out of John Warfield’s Interactive Management and was developed by Alexander Christakis and Yiannis Laouris. It is not new: fifty years of peer-reviewed work, hundreds of documented dialogues. Laouris and Christakis called it harnessing collective wisdom, and named scale as its hardest limit; lifting that limit is what True Causes is for. A few deliberate departures. One of them: the method keeps every idea attached to its author's name throughout, and its practitioners argue anonymity weakens accountability. Here nobody is named inside a dialogue, because in a workplace or a divided community the name is what stops people writing the true card. We think the trade is right; it is untested. See the research. The mechanism science around it, the rules tested against bloc voting, and the implementation are what we add.

  • John N. Warfield & A. Roxana Cárdenas — Interactive Management and Interpretive Structural Modelling; spreadthink; the laws of requisite variety, parsimony and saliency. A Handbook of Interactive Management, 2nd ed., Iowa State University Press, 1994 — out of print; the manuscript is free from the Warfield archive.
  • Alexander N. Christakis & Kenneth C. Bausch — Structured Democratic Dialogue as a democratic practice. How People Harness Their Collective Wisdom and Power, Information Age Publishing, 2006.
  • Yiannis Laouris & Alexander N. Christakis — running the method in a virtual setting, and scale named as its hardest limit: what True Causes sets out to lift. Harnessing collective wisdom at a fraction of the time using Structured Dialogic Design Process in a virtual communication context, International Journal of Applied Systemic Studies 1(2), 131–153, 2007.
  • Kevin M. Dye — the erroneous priorities effect: importance votes cast before the relations among ideas are examined prove wrong once they are. First observed by Kapelouzos in 1989. Dye & Conaway, Lessons Learned from Five Years of Application of the CogniScope Approach to the FDA, 1999; defined and measured in Laouris & Michaelides, European Journal of Operational Research, 2018.
  • W. Ross Ashby — the law of requisite variety: only variety absorbs variety. An Introduction to Cybernetics, Chapman & Hall, 1956 — full text, Principia Cybernetica.
  • George A. Miller — the limits of a group's working attention, the reason questions are asked one at a time. The magical number seven, plus or minus two. Psychological Review 63(2), 1956.
  • Yiannis Laouris and colleagues, Future Worlds Center — more than 120 documented co-laboratories, including the practice thresholds True Causes implements. Laouris & Dye, Five generations of evolution of dialogic design, Systems Research and Behavioral Science 41(2), 2024 · Laouris & Metcalf, Assessing the viability of virtual structured democratic dialogue, Systems Research and Behavioral Science 42(3), 2025 · Laouris, integrating asynchronous influence maps, 2023.
  • Benjamin Broome, Michael Hogan and colleagues — Interactive Management studied and applied independently of the line above, as a method of collective intelligence, and the facilitation it depends on. Razzante, Hogan, Broome, Tracy, Chawla & Skurzak, Interactive Management research in organizational communication, Management Communication Quarterly 37(4), 971–989, 2023 · Hogan, Harney, Broome et al., A group dynamics framework for 21st century collective intelligence facilitators, Systems Research and Behavioral Science 38(4), 2021.
  • Cynthia R. Farina and colleagues, Cornell eRulemaking Initiative — online participation in complex public policy: more participants is not better participation. People need the facts a question turns on, their input has to reach someone who answers it, and voting on ideas rewards what is popular rather than what is useful. The briefing a room can carry, the recipient named with a date, and the hint on cards too vague to judge follow from it. Farina, Epstein, Heidt & Newhart, Designing an online civic engagement platform: balancing “more” vs. “better” participation in complex public policymaking, International Journal of E-Politics 5(1), 16–40, 2014.

The wider literature: Structured Democratic Dialogue · Interpretive Structural Modelling · Interactive Management. Our own simulations and their results ship with the software and are described in the notes bundled with it.

What else is out there. Polis finds where a crowd already agrees and shows you the clusters. Remesh and tools like it scale that agreement-finding to thousands of people. The Habermas Machine writes a statement most of a group can sign. All three are good at one question: what do we agree on? This asks a different one — what causes what? — settles it pair by pair, and keeps the disagreements it cannot settle instead of smoothing them over. The nearest tool is the method's own: IdeaPrism, from Laouris's team, runs clustering and mapping asynchronously and sends disagreements back for justification.

Not the wisdom of crowds. Galton's ox and every prediction market since work by averaging independent guesses: the errors cancel because nobody talked. That is the right tool for a number — a weight, a date, a price. It has no answer for does A cause B, where a hundred uninformed guesses average to an uninformed guess. This works the other way round: people are made to talk first, so that what they judge is informed; and their judgements are not averaged but counted against a bar they must clear together. Independence is what a crowd needs; shared meaning is what a group needs.

In other fields' words. To a computer scientist this is human-based computation: people answer each pair, and an algorithm, interpretive structural modelling, assembles the map. To an economist it works on dispersed knowledge, in Hayek's sense: what a problem needs is spread across many people, and no one holds it all. On a public question it is civic intelligence. And it is collective problem solving, not collective decision-making: it informs a decision and leaves the decision to the people who must answer for it.

Start a structured dialogue on your own question.

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