Meta-Frameworks, Integrative Models & Worldviews
Integrative Models and Meta-Frameworks
- Scope and ambition control: What the model claims to cover—and what it explicitly excludes.
- Primitive definition discipline: Core concepts defined precisely, non-overlapping, and stable.
- Ontological clarity: What kinds of things exist in the model (agents, incentives, information, institutions, values) and how they relate.
- Causal vs classificatory distinction: Whether it explains mechanisms or merely labels categories.
- Internal coherence: No contradictions across layers; consistent logic and terminology.
- Completeness vs parsimony: Whether compression loses critical factors or creates blind spots.
- Boundary conditions: Contexts where the model fails or should not be used.
- Falsifiability and testability: What would disconfirm the model; what evidence it predicts.
- Comparative advantage: What it improves over existing frameworks (not “it’s holistic”).
- Operationalization: Can it be executed as a process (steps, gates, outputs) or is it only descriptive?
- Measurement and observability: Which variables are measurable vs inferred; risk of proxy failure.
- Level-of-analysis discipline: Micro/meso/macro kept distinct; no scale-jumping without bridge logic.
- Integration integrity: Whether components truly integrate or are just stacked.
- Incentive and power realism: Whether it accounts for manipulation, capture, and adversarial behavior.
- Misuse risk: How it can be used as a rhetorical weapon or “universal justification engine.”
- Governance of interpretation: Rules preventing arbitrary interpretation and post-hoc rationalization.