Building Complexity Literacy
A Toolkit for Evaluating Frameworks
I wanted to call this piece “Predatory Theater: A Toolkit for Inoculating Yourself Against the Charlatans” but I opted for something more general and, ultimately, I hope more helpful. This isn’t just about the sprawling metamodern community or the linguistic convergence of overlapping circles—I’ve been grappling with naming these patterns my entire life.
I’m offering this in the spirit of building antidotes to bullshit, because we all get to choose our own adventure and there’s a role for every soul. Different strokes for different folks and all that. Last week I got started talking about ‘enshittification’ and this is an extension as well as a prologue- it’s by no means a manifesto, just what I’m working through.
This piece is for me as much as anyone else curious about how to think concretely about ecosystem collapse-ability. For those searching for more than AI-soteric abstraction (or along with it). For those with pragmatic souls and imaginative hands (or vice versa). It’s for anyone thinking it’s beginning to look a lot like “fuck this” [insert grumpy cat meme here]
We can do this living better thing. But it’s more than hot takes and prayer emoji—we need people willing to stick their necks out and show the work of everyday cohesion.
So here we are, as part of my series on recipes for connection and complexity without complicity, to help illuminate the bullshit and build the kind of self-responsibility that enables shared power. We have more power than we know, and together we can do anything. ✊🏻✨
What This Toolkit Actually Does
This isn’t about calling out specific people. It’s about building your pattern recognition skills to evaluate any complexity-based work you encounter—including this one and my own frameworks. (and it doesn’t have to be limited to “chaos theory” or complexity science, it just happens to be my flavor; if we are living in chaos, which is too often conflated with ‘anarchy’ work with it, not against it 😉)
Here goes!
Questions to Ask About Any Complexity-Based Work
Why Pattern Recognition Matters
Complexity science offers genuinely powerful tools for understanding human systems, organizational dynamics, and social change. As these frameworks gain wider use, it becomes increasingly important to develop discernment about how they’re being applied.
This toolkit provides structural questions you can ask about any complexity-based framework you encounter—including this one. The goal isn’t to judge specific people or approaches, but to build your capacity to evaluate how frameworks function and whether they serve your needs
Core Complexity Concepts: What They Actually Mean
Understanding these foundational concepts from complexity science helps you recognize when they’re being used accurately versus when terminology is being borrowed without the underlying principles.
1. Emergence
Definition from complexity science: A process by which a system of interacting subunits acquires qualitatively new properties that cannot be understood as the simple addition of their individual contributions.
What this means in practice: When you observe group dynamics that arise naturally from individual interactions without anyone orchestrating them. Like how traffic patterns emerge from individual driving decisions, or how conversation norms develop in communities.
Questions to ask about frameworks claiming to use emergence: - Are they describing patterns that emerged naturally, or patterns they designed and imposed? - Can you observe similar patterns emerging independently in other contexts? - Do they explain how the emergent properties arose from local interactions?
Watch for: Frameworks that claim to have “discovered” patterns that seem to be built into their assessment tools. True emergence happens whether or not anyone is watching or measuring.
2. Complex Adaptive Systems
Definition from complexity science: A system composed of many interacting components, without central control, whose emergent global behavior is more complex than can be explained from understanding individual components. These systems are capable of adapting to changing inputs.
What this means in practice: Human systems have functional differentiation without requiring hierarchy or central control. Different ways of thinking and processing information serve different ecosystem functions naturally.
Questions to ask about frameworks working with complex systems: - Do they acknowledge that systems adapt and change on their own? - Are they teaching you to work WITH natural patterns or trying to control them? - Do they position themselves as necessary central coordinators, or as people sharing observations?
Watch for: Approaches that suggest simple cause-effect relationships where none exist, or position the practitioner as the expert who must control or manage the complexity. Complex systems resist central control by definition.
3. Attractors (Including Strange Attractors)
Definition from complexity science: Values or sets of values that a system tends toward over time. Strange attractors have fractal structure and appear in chaotic systems—they’re patterns the system gravitates toward without settling into fixed points.
What this means in practice: Systems have natural tendencies—patterns they move toward under certain conditions. In conversations, you might notice gravitational pull toward either curiosity or defensiveness, understanding or correction-seeking. These are attractors.
Questions to ask about frameworks using attractor concepts: - Are they helping you recognize patterns in YOUR systems? - Do they acknowledge that different systems have different attractors? - Are they treating development as dynamic patterns or as fixed destinations?
Watch for: Linear development paths with “levels” to ascend, or frameworks suggesting everyone should reach the same endpoint. Attractors are about pattern recognition, not prescriptive destinations. Levels can exist as progression, as developmental stages but not “jumping through hoops” to “attain” anything
4. Sensitive Dependence on Initial Conditions
Definition from complexity science: When small changes in starting conditions lead to significantly different outcomes. This sensitivity makes long-term prediction impossible in chaotic systems—it’s why we can’t forecast weather accurately beyond a few days.
What this means in practice: Context matters enormously. The same principles applied in different starting conditions will produce different outcomes. This is to be expected, and listening to people with experience in their environments is crucial (especially if you think you have The Answer ™️)
Questions to ask about frameworks claiming complexity awareness: - Do they acknowledge that context shapes outcomes? - Do they expect local adaptation, or sell “THE formula” that works everywhere? - Are they honest about what can and cannot be predicted?
Watch for: Universal applicability claims, promises of predictable outcomes, or suggestions that ignoring initial conditions is acceptable. Context-blind frameworks aren’t actually working with complexity.
5. Self-Organization
Definition from complexity science: A process where global patterns emerge solely from numerous local interactions. The rules specifying interactions are executed using local information, without reference to the global pattern—no central controller needed.
What this means in practice: You can provide local interaction rules that enable system-level change without centralized management. When many people apply principles in their own contexts, patterns emerge naturally from those distributed actions.
Questions to ask about frameworks claiming to support self-organization: - Are they providing principles that people can apply independently? - Do they require ongoing expert management and interpretation? - Does the system become more capable of self-direction over time, or more dependent?
Watch for: Certification requirements, gatekeeping, or suggestions that the system can’t function without continued expert guidance. True self-organization distributes intelligence rather than concentrating it.
The Assessment Toolkit: Questions to Ask
When encountering any complexity-based framework, these questions help you evaluate its structure and likely impact:
About Observation vs. Construction
Ask: Is this pattern something that was observed emerging naturally, or something that was designed and then presented as discovery?
Why it matters: Authentic complexity work describes what’s already happening. Constructed frameworks can be useful tools, but they’re different from observed patterns—and it matters which you’re working with.
What to look for: - Can they point to multiple independent instances of this pattern? - Do others using different terminology describe similar observations? - Is there a clear methodology for how the pattern was identified? (For me this looks like: “can I turn it into a cooking metaphor?”)
About Methodology Transparency
Ask: Can they explain their research process? What did they observe, for how long, under what conditions?
Why it matters: Understanding how insights were derived helps you assess their applicability to your context and their validity in general.
What to look for: - Clear documentation of observation methods - Transparent about data sources and limitations - Acknowledgment of what they don’t know or can’t claim. Abstract ideas are great for juicing us up, but applied wisdom looks like confident embodiment and ease, not a checklist or throwing our nemeses under the bus…
About Agency and Dependency
Ask: Does engaging with this framework increase your capacity for independent navigation, or create ongoing need for expert interpretation?
Why it matters: Some frameworks are designed to transfer capability to you. Others are designed to keep you dependent on the framework provider. Both serve functions, but you should know which you’re getting.
What to look for: - Do you understand more about your own system after engaging? - Can you apply principles without continued guidance? - Does the framework graduate you toward independence or deepen dependency? This is where experts matter and specialized knowledge is crucial- and where this toolkit becomes proof in the pudding. Your own system could be corrupted, and so could the experts’ but engaging in honest conversation about it should bring more clarity if both parties are engaging openly and honestly.
About Context Sensitivity
Ask: Does this approach acknowledge that different contexts require different applications, or claim to work universally?
Why it matters: Complexity science is fundamentally about context dependency. Frameworks that ignore context aren’t actually working with complexity principles, regardless of terminology used.
What to look for: - Explicit acknowledgment that local adaptation is necessary - Examples showing how application varies by context - Humility about limitations and boundary conditions
About Power and Intelligence Distribution
Ask: Does this approach honor distributed wisdom and diverse ways of knowing, or concentrate expertise in credential-holders?
Why it matters: Complex systems thrive on requisite variety—they need multiple types of intelligence and processing architecture. Frameworks that concentrate power in experts’ hands are working against complexity principles.
What to look for: - Recognition that different people bring different valuable perspectives - Respect for lived experience alongside formal study - Distribution of interpretation capability, not just information
About Knowledge Accessibility
Ask: Is knowledge shared accessibly, or locked behind paywalls and gatekeeping structures?
Why it matters: Complexity literacy works best as a distributed skill. When knowledge is artificially scarce, it benefits the framework provider more than the communities trying to use it.
What to look for: - Sliding scale pricing or commons-based sharing - Open documentation that you can verify and build on - Willingness to have work scrutinized and tested
We all deserve to have our time fairly compensated- support work you want to see more of!
Common Patterns Worth Recognizing
These aren’t accusations—they’re structural patterns that show up across domains. Recognizing them helps you make informed decisions about where to invest your time and resources.
Dense Terminology Without Clear Application
What it looks like: Heavy use of technical language that sounds impressive but doesn’t connect to concrete examples or observable phenomena.
Why it shows up: Complex language can make simple concepts seem more valuable than they are, or obscure when someone doesn’t fully understand what they’re talking about.
How to respond: Ask for concrete examples. “Can you show me how this applies in a real situation?” Watch whether examples are clear and specific or stay abstract.
Proprietary Language for Standard Concepts
What it looks like: New terms for things that already have widely-used names in complexity science or related fields.
Why it shows up: Sometimes genuine synthesis creates new useful terminology. Sometimes it’s about making work seem unique when it’s not.
How to respond: Ask if existing terms describe similar concepts. Research whether the pattern they’re describing has been documented elsewhere using standard terminology.
Diagnostic Tools That Create Need for Services
What it looks like: Assessments that consistently reveal you need the specific services that the framework provider offers.
Why it shows up: When frameworks are designed primarily as marketing tools rather than genuine aids to understanding.
How to respond: Notice whether the framework makes you MORE capable of navigation over time, or keeps you returning for interpretation. Authentic tools increase your agency.
Making Simple Concepts Unnecessarily Complex
What it looks like: Straightforward ideas wrapped in elaborate frameworks or terminology that makes them harder to understand rather than easier.
Why it shows up: If something is too easily understood, people may not see why they need expert guidance with it.
How to respond: Ask yourself—is the complexity in the concept itself, or in how it’s being presented? Good complexity work makes difficult concepts MORE accessible, not less.
Inner Circle Dynamics
What it looks like: Framework use that creates in-groups and out-groups, with progression through levels or special access for committed practitioners.
Why it shows up: Human psychology around belonging is powerful. Frameworks can leverage this intentionally or accidentally.
How to respond: Notice whether skeptical questions are welcomed or treated as resistance. Authentic work invites investigation; extraction patterns punish it.
What Authentic Complexity Work Looks Like
In contrast to concerning patterns, here are markers that suggest a framework is probably serving its stated purpose:
✓ Observable Pattern Recognition
Describes how systems naturally function based on documented observation. Others can verify the patterns independently.
✓ Functional Differentiation Without Hierarchy
Recognizes that different processing styles serve different ecosystem functions. No ladders to climb, just different valuable contributions.
✓ Explicit Context Dependency
Clear about local adaptation being necessary. Provides principles rather than prescriptions, expects variation in application.
✓ Supports Emergence
Teaches interaction rules that allow patterns to emerge naturally. Trusts self-organization rather than imposing orchestration.
✓ Transparent Methodology
Clear about data sources, observational methods, and how insights were derived. Cites influences and acknowledges standing on others’ shoulders.
✓ Accessible Knowledge Sharing
Commons-based approach to information. Sustainability doesn’t require artificial scarcity or extraction.
✓ Lived Experience Grounding
Substantial applied research in contexts where failure had real consequences, not just theoretical study.
✓ Increasing Independence Over Time
Frameworks make you MORE capable of independent navigation, not more dependent on expert interpretation.
✓ Welcomes Reality-Checking
Open to critique, updates based on new information, treats questioning as collaboration rather than threat.
Practice Exercise: Evaluate Any Framework
Use this checklist when encountering complexity-based work (including this toolkit):
□ Can you find similar patterns documented by multiple independent sources using standard terminology?
□ Is the methodology transparent—can you understand how they arrived at these insights?
□ Does engaging increase your agency and understanding, or create dependency on continued interpretation?
□ Do they acknowledge that context matters and outcomes vary, or claim universal applicability?
□ Is knowledge shared accessibly, or behind paywalls and gatekeeping?
□ Do they welcome scrutiny and critique, or treat questions as attacks?
□ Can you apply principles independently after engaging, or need ongoing expert guidance?
□ Is there substantial lived experience behind claims, or primarily theoretical credentials?
□ Does the approach distribute intelligence and capability, or concentrate it in expert hands?
□ Are they observing natural patterns or constructing frameworks and calling them discoveries?
If you’re raising concerns on multiple items, investigate further before investing significant resources.
Building Collective Discernment
The goal of this toolkit isn’t to make you suspicious of everything—it’s to help you ask good questions and make informed decisions about where to invest your time, trust, and resources.
Share these questions in your networks. Discuss what you’re noticing. Reality-check frameworks together—multiple perspectives catch what any individual might miss.
Apply these criteria to everything, including this toolkit and its sources. Pattern recognition should cut in all directions. If questioning something makes it collapse, it wasn’t solid to begin with. Good work holds up under examination.
Support frameworks that pass these tests. When you find complexity work that’s transparent, increases agency, distributes power, and welcomes scrutiny—amplify it. The best response to extraction patterns is thriving alternatives.
Complexity science offers powerful tools. Making those tools accessible and useful requires collective literacy about how frameworks function and whether they’re serving their stated purposes.
Learn to ask good questions. Build distributed discernment. Help good work thrive.
Coming later this week: the companion guide going into deeper dives of each header, the questions I’ve already had pushback on (and maybe more to come!)
About This Toolkit
Methodology transparency: This toolkit emerged from three decades of applied complexity research in restaurant management, collaborative co-parenting, and community organizing. The complexity science definitions are drawn from the Santa Fe Institute’s Complexity Explorer glossary (complexityexplorer.org)—the academic standard for these terms.
AI collaboration disclosure: This document was developed collaboratively with Claude (Anthropic’s AI). The synthesis is human, the formatting and articulation received AI assistance, the complexity science is cited from legitimate sources.
Application to this work: Everything in this toolkit should apply to evaluating the frameworks it references—Strange Attractor Academy, Cascading Conversations, and Inscendent Community Hub infrastructure. If you find gaps between stated principles and actual practice, that’s important information.
Living document: This toolkit should evolve based on collective use and feedback. Contribute improvements, point out limitations, help it get better through reality-checking.
Complexity science definitions adapted from: Santa Fe Institute’s Complexity Explorer glossary
Created as a commons resource—share freely, adapt as needed, credit the sources, keep it accessible. Please contact bee@pragmagination.us or dm here, I’d love to connect!
Wow! This is deep and rich. And complex. 😉
And I can see you’ve been thinking about it for a long time… the clarity amidst the complexity shows.
Do you have plans to illustrate this framework in action via some kind of storytelling? It’s one aspect to grok an extensive framework via a descriptive process as you done here. Some might also be supported by seeing examples of the process in the field.
Appreciate the deep effort that’s gone into putting this together!
I mean the visual and verbal is so alive in my imagination but yes, I'm not sure how yet without just opening a hub and showing it in real time like I did via restaurant coordination... I'm not sure how to translate that yet because ya girl is *not* about to open a proof of concept restaurant (my kids might though, but that a decade out 😄)