DCG concepts are not isolated definitions. They form a connected operating language for structure, power, accessible futures, intervention and institutional learning.
A research and governance architecture for making evolving causal structures inspectable, constructing the futures they generate, locating structural leverage and governing intervention through accountable cycles of authorization, execution, observation and learning.
The capability to transform dispersed evidence into an inspectable understanding of the structures, constraints, regimes and propagation paths shaping consequential outcomes.
The analysis and design of dependencies, constraints, resources and coordination through which actors can produce effects.
The deliberate design of present structural changes that can open, protect or close future possibilities.
The design of bounded interventions in the relationships, constraints or feedback mechanisms producing an outcome.
A traceable record of models, evidence, assumptions, decisions and observed consequences that supports later revision and reuse.
A governed process for testing decision-relevant signals across independent sources, domains, scales and temporal frames before allowing them to update the causal model.
The smallest decision-relevant difference that changes the model, the diagnosis of state or regime, or the accessibility of a future.
Decision-relevant uncertainty in the causal field: ambiguity about structure, active regime, propagation, adaptation or the consequences of intervention.
The form through which state, force, direction, coupling, resistance, delay, incentives and constraints condition propagation and future accessibility.
Conditional futures whose generating pathways can be identified, influenced and monitored within real structural and institutional boundaries.
Disproportionate systemic change produced by modifying a limited structural condition at the right state, scale and temporal window.
A model for reading and governing three power vectors across causal terrain: Red coercion, Yellow metabolism and Blue validation. Luminosity modifies how each vector operates.
A condition in which the broader causal architecture—feedback, incentives, constraints, leverage, timing, risk and learning—makes particular behaviors or futures likely, persistent or governable.
The persistent lineage connecting evidence, assumptions, authority, intervention, direct effects, delayed consequences and learning.
Decision-relevant structural equivalence between systems that share dominant loops, constraints and intervention logic despite different surface labels.
The technological and operational environment designed to materialize Structural Intelligence and selected DCG capabilities as inspectable decision artifacts.
