Please Read Our Three-Guide Introduction First!

Before starting this Advanced Guide, it is critical to have read our introduction to the three guides, titled Reality-Aligned Thinking and Metacognition: Introduction to the Basic, Intermediate, or Advanced Guides. Skipping it is allowed, just as ignoring the instructions before assembling furniture. The furniture may still stand, but it will probably stare at you with one crooked leg and missing critical parts.

We have also provided pre- and post-completion self-scoring tests for the Intermediate Guide so you can see how you did after completing this guide. These tests will include essential information from the introduction to the three guides.

 Click here for the pretest and click here for the post-test.

Prologue:

This advanced guide, along with all three of our guides, is dedicated to the following simple idea. What the world's future needs most right now is not so much another technological breakthrough. It is a widespread and major upgrade in rational thinking, analysis, and decision-making skills that better enable individuals to problem-solve and act on the challenges in their lives, ranging from the simple to the complex. In case you were in a hurry and didn't read the introduction. The following are critical reminders from the introduction to all three guides:

1. Choose a real current problem.
2. Understand the powerful difference between declarative vs. experiential knowledge.
3. Use AI as an assistant, not an authority.
4. Use the simplest adequate thinking tool.
5. Apply one method at a time.
6. Write results, act carefully, review, repeat.
7. Treat intuition as a signal to test, not a verdict to worship.

Introduction: What the Advanced Guide Covers and What Each Method Is Best Used For

Best for: very high-stakes analysis, complex adaptive systems, civilizational risks, intelligence agency analysts, climate and ecological risk, major institutional redesign, long-range strategy, AI governance, intelligence agency analysis, major public claims, personal transformation, leadership, and problems where the thinker’s own overt or hidden assumptions are part of the problem.

What the Advanced Guide Covers and What Each Method Is Best Used For

• • Advanced tool selector: Best for choosing the right advanced method without turning every problem into a graduate seminar with snacks missing.
  • Claim-strength guide: Best for matching the strength of a claim to the strength of the evidence.
  • Full Robert Kegan subject-object theory: Best for seeing how identity, worldview, loyalty, fear, role, and hidden meaning-making shape judgment.
  • Disembedding practices: Best for turning what you are unconsciously subject to into something you can observe, examine, and revise.
  • Classical metacognition: Best for planning, monitoring, evaluating, and adjusting your thinking process while you are using it.
  • Self-regulation and inner reference point practices: Best for staying grounded under uncertainty, pressure, conflict, or emotional activation.
  • DMAP overview: Best for understanding Dialectical Metasystemic Analysis and Problem-Solving as a method for complex, changing, nested, relational systems.
  • Critical realist open-systems humility: Best for remembering that real-world systems are open, incomplete, changing, and not fully captured by any single model.
  • DMAP readiness checks: Best for determining whether the learner has sufficient cognitive bandwidth, emotional stability, subject-object capacity, and disciplined practice to use advanced tools effectively.
  • Jan De Visch creative attunement, advanced version: Best for sensing emerging meaning, symbolic patterns, creative hunches, and not-yet-clear insights before translating them into disciplined inquiry.
  • Otto Laske’s Dialectical Thought Forms: Best for examining process, context, relationship, and transformation across complex systems.
  • The 28 DTF mind-opening questions: Best for expanding how a problem can be viewed before prematurely locking onto one explanation.
  • DMAP model-building loop: Best for building, testing, revising, and improving mental models of complex problems.
  • Balcony and dance-floor movement: Best for moving between direct experience and reflective overview.
  • Social scaffolding to self-scaffolding: Best for learning advanced thinking first with support, then internalizing it as an independent skill.
  • John Stewart's recursive self-improvement: Best for improving not only your decisions, but the strategies and meta-strategies that produced them.
  • Escalator framework: Best for developing, using, and equipping higher levels of human agency and intelligence.
  • Incubation and whole-system synthesis: Best for letting disciplined research and reflection integrate into deeper insight without pretending a sudden insight is automatically true.
  • Reality testing: Best for forcing beautiful theories to survive contact with evidence, constraints, critics, and consequences.
  • Red Team validation: Best for stress-testing conclusions before publication, major decisions, or high-stakes action.
  • Evidence-tier review: Best for separating direct evidence, strong inference, weak inference, speculation, and unsupported claims.
  • Claim hygiene: Best for separating facts, interpretations, assumptions, conclusions, recommendations, and confidence levels.
  • False either-or and both-and screening: Best for detecting fake choices and finding integrative solutions when they are viable.
  • Commons failure audit: Best for testing whether a solution can survive free-riding, capture, weak enforcement, unfair burden-sharing, bad monitoring, or ecological overshoot.
  • Stewardship review: Best for checking humility, ownership, power, control, authority, distortion risk, and responsible release.
  • Data integrity, model failure, and AI-amplified error audit: Best for checking whether datasets, algorithms, forecasts, or AI-assisted outputs are biased, incomplete, mismeasured, overfit, outdated, or being treated as more certain than they are.
  • Ecological overshoot and planetary-boundary screen: Best for testing whether a solution depends on unavailable energy, materials, ecological capacity, fiscal capacity, social trust, or governance bandwidth.
  • Dyslexia and final-copy accuracy check: Best for verifying names, terms, dates, numbers, links, headings, abbreviations, and readability before release. The main person creating these guides has dyslexia and added this extra red team procedure. If you have any type of handicap that could affect the final accuracy of your work, add this to your final red team criteria.

AI support prompts for the Advanced Guide

(Please note that these AI prompts and many other prompts will be repeated in the Intermediate Guide where needed.)

• • “Help me examine how my identity, role, loyalty, fear, worldview, or emotional investment may be shaping how I see this problem.”
  • “Use a metacognitive review: What thinking process am I using, what might it miss, and what should I monitor as I continue?”
  • “Help me examine this issue through process, relationship, context, and transformation perspectives. What changes when I view the problem through each lens?”
  • “Help me build a provisional whole-system model of this issue. Include actors, incentives, feedback loops, constraints, resources, information flows, power dynamics, and possible transformation points.”
  • “Red team this conclusion. Separate facts, interpretations, assumptions, inferences, speculations, and recommendations. Then identify the weakest links.”
  • “Screen this solution for false either-or framing. What both-and solutions might preserve what is valid on each side while avoiding the worst trade-offs?”
  • “Run a commons failure audit on this solution. How could it fail through free-riding, weak enforcement, capture, unfair burden-sharing, bad monitoring, low legitimacy, or ecological/resource overshoot?”
  • “Audit this AI-assisted analysis for possible data problems, hallucinations, outdated information, weak sources, missing counterevidence, overconfidence, and model failure.”
  • “Before publication or action, create a final stewardship review: What could be distorted, misused, overstated, misunderstood, or released without enough humility?”

Prologue: 

To be successful using our advanced rational thinking guide, it is essential that you have your rational thinking basics functioning well, especially your understanding of complex adaptive systems and systems thinking. The basic and intermediate rational-thinking guides were created to address a common educational gap we discovered while trying to teach people DMAP.

We learned that their effectiveness in applying DMAP methodology and achieving highly accurate results also depended on their grasp of earlier essential or foundational rational-thinking methods, particularly complex adaptive systems and systems theory. If you have grasped the information and skills in our basic and intermediate rational thinking guides, you should do very well in the advanced guide by applying DMAP and achieving highly accurate results.

Introduction: Why this work matters now

Maybe what the world needs now, alongside better technology, is a serious upgrade in how people think before they decide and act. That sounds obvious, which is why it is so impressive that civilization keeps forgetting it.

The advanced thinking tools you are about to learn will take serious effort and work to learn and successfully apply. This guide is designed for high-level organizational leaders, think tank analysts, forecasters, researchers, high-level corporate executives, high-level government policy and planning executives, educators, coaches, self-directed adults, and early college-level learners who want something more than clever opinions moving at keyboard speed. It introduces four major domains of higher-order thinking:

1. 1. Domain 1: Self-regulation of thinking. This is metacognition in the standard research sense: planning, monitoring, evaluating, and adjusting your own thinking and learning.
   2. Domain 2: Subject-object growth and meaning-making. This is Robert Kegan’s territory: what you are still embedded in, and what you can step back from and examine.
   3. Domain 3: Dialectical and metasystemic cognition. This is where Otto Laske’s Dialectical Thought Form Framework and DMAP (Dialectical Metasystemic Analysis and Problem-solving) become central. It helps you think in terms of process, context, relationship, hidden absences, contradiction, and transformation. (Please note that DMAP is a unique and new application of the dialectical thought form work (DTF) of Otto Laske and others related to his work.)
   4. Domain 4: Recursive self-improvement. This is where John Stewart’s work becomes useful: improving not just your strategies but the strategies that generate them.

The larger purpose is simple: better self-regulation, better perspective-taking, better handling of complexity, better models, and better action. In everyday life, these capacities support learning, relationships, leadership, career decisions, strategic planning, and emotional steadiness. In public life, they are the kinds of capacities needed by people working on climate change, ecological overshoot, political polarization, AI risk, institutional breakdown, financial instability, and other delightful menu items from the modern buffet of consequences.

The big clarification: four domains, not one ladder

It is misleading to treat ordinary metacognition, Kegan’s subject-object development, Laske’s dialectical cognition, and Stewart’s recursive self-improvement as if they were four rungs of one identical ladder. They are not.

The cleaner picture is a four-domain integration model. Each domain has its own focus, strengths, limits, and training path. They can support one another, but growth in one domain does not automatically produce growth in the others. You can be highly self-reflective and still think statically. You can be analytically brilliant and still be emotionally fused with approval, ideology, fear, or identity. You can know better strategies and still fail to use them when stress knocks over the furniture.

Why not call all of this “metacognition”?

Because that stretches the word until it becomes an academic sock puppet. In the research literature, metacognition usually refers to awareness and regulation of cognition, especially planning, monitoring, evaluating, and adjusting learning or problem-solving. That fits Domain 1 very well.

Kegan is about meaning-making structure. Laske is about cognitive complexity and dialectical sense-making. Stewart is about recursive self-scaffolding. You can use “metacognition” as a friendly doorway into the whole topic, but using it as a giant umbrella risks flattening the very distinctions that make the other domains powerful.

Who are the major thinkers and contributors in this guide?

This guide draws on several major thinkers whose work helps explain how adults learn to regulate thinking, step back from what controls them, understand complex open systems, think dialectically, and improve the strategies that guide their action. No single thinker owns the whole territory. That would be too simple, and therefore suspicious. The strength of this guide comes from integrating several complementary bodies of work into a practical learning sequence.

• Robert Kegan is a developmental psychologist best known for adult meaning-making development and the subject-object movement. His work helps explain how people gradually become able to step back from assumptions, identities, emotional patterns, social expectations, and mental structures that previously shaped them from the background. In this guide, Kegan’s work supports the section on subject-object growth: learning to notice what you are embedded in so you can examine it rather than be silently run by it.
• Michael Basseches is a foundational thinker in adult dialectical development. His work helps explain how mature thinking becomes more dynamic, relational, developmental, and able to work with contradiction and change. In this guide, Basseches provides part of the developmental foundation for understanding why higher-order thinking must move beyond static logic into process, relationship, context, and transformation.
• Roy Bhaskar was the Oxford-trained philosopher who founded critical realism, one of the most important philosophical foundations behind open-systems thinking, dialectical analysis, and serious social science. Bhaskar argued that reality is not limited to what we directly observe. Beneath visible events are deeper structures, causal powers, tendencies, mechanisms, constraints, and conditions that may or may not become visible in any given situation. This is essential for DMAP because complex human, ecological, economic, psychological, and institutional systems rarely behave like closed laboratory systems. They are open systems, where many causal forces interact, interfere, amplify, suppress, delay, or distort one another.
• Otto Laske developed the Dialectical Thought Form Framework and the broader Constructive Developmental Framework. Laske’s work distinguishes cognitive sense-making from social-emotional meaning-making and gives learners a practical way to strengthen dialectical cognition. His 28 Dialectical Thought Forms help people think in terms of process, context, relationship, contradiction, and transformation. Laske also drew from Bhaskar’s dialectical critical realism, especially Bhaskar’s layered, open-system, causal view of reality. This makes Laske’s work especially important for DMAP because DMAP is not merely asking people to think harder. It asks them to think more structurally, developmentally, relationally, and causally.
• Elliott Jaques contributed major work on levels of work complexity, time-span of discretion, human capability, and requisite organization. His work helps connect thinking development to real-world task complexity. In this guide, Jaques is useful because some problems require longer time horizons, more complex judgment, and greater capacity to hold multiple interacting variables without reducing everything to a slogan, which is apparently a popular human hobby.
• Jan De Visch helps learners notice imaginal, embodied, symbolic, and pre-conceptual cues before formal dialectical analysis begins. This matters because people often sense complexity before they can clearly explain it. De Visch’s work supports the pre-DMAP warm-up process: noticing the half-formed images, metaphors, body signals, emotional tones, and intuitive cues that may reveal something important before formal analysis organizes it.
• John Stewart contributes a practical account of recursive self-improvement, mental models, self-scaffolding, and the disciplined upgrading of cognition and action. His work helps explain how people can improve not only their decisions but also the strategies, learning loops, and self-correcting practices that shape future decisions. In this guide, Stewart’s work supports Domain 4: learning how to improve the way you improve.
• Lawrence Wollersheim contributed the overall practical architecture, the questioning sequence, the learning-layer design, and the integrative organization of these guides. His contribution has been to bring together and apply the work of Kegan, Basseches, Bhaskar, Laske, Jaques, De Visch, and Stewart within the emerging DMAP methodology, especially by organizing these ideas into a usable sequence for advanced thinking, analysis, judgment, and problem-solving. 

Why Roy Bhaskar matters for DMAP

Roy Bhaskar's work is essential to this guide because his critical realism provides DMAP with a rigorous philosophical foundation for working with complex reality rather than merely organizing surface observations. Critical realism distinguishes between what happens, what we observe, and the deeper structures or causal mechanisms that generate events. That matters because most real-world problems do not unfold inside tidy closed systems. They unfold in open systems where many causes operate at once, where effects may be delayed or hidden, and where the same cause may produce different outcomes depending on context.

For DMAP, this is not an abstract philosophical luxury item, like a velvet hat for an academic parade. It is practical. If you are analyzing climate change, institutional dysfunction, political polarization, health behavior, organizational failure, AI risk, or personal development, you cannot rely only on obvious symptoms. You have to ask: What mechanisms are operating beneath the surface? What structures make this pattern keep reproducing? What conditions activate or suppress those mechanisms? What is absent, blocked, distorted, or hidden? Bhaskar’s open-systems realism helps explain why good analysis must look beneath events into the deeper causal architecture of a situation.

This is one reason Bhaskar’s work is so important for understanding Laske and DMAP. Laske’s dialectical thought-form work does not merely ask people to think harder. It asks them to think more structurally, developmentally, relationally, and causally. Bhaskar helps supply the philosophical backbone for that move: reality is layered, open, dynamic, and only partly visible. DMAP builds on that insight by training people to look for process, context, relationships, hidden absences, contradictions, transformations, and hidden causal mechanisms before they rush into conclusions, plans, or the usual ceremonial faceplant humans call “decision-making.”

How to read the rest of this guide

Read one page at a time. Apply the page to a real problem. Use the AI prompt modules to widen your questioning, but do not outsource your final judgment. AI can help gather options, compare frames, generate counterarguments, and expose gaps. It can also hallucinate, miss context, over-flatten complexity, and sound confident while being wrong, which is not exactly a rare human talent either.

The strongest use of AI in this guide is not “tell me what to think.” The strongest use is “help me ask better questions, compare better options, expose missing variables, and test my reasoning more honestly.”