TDR Indicator Architecture
The universal logic through which indicators are grouped, classified, and translated into resilience diagnostics across sectors. Methodological consistency with sector-specific flexibility.
Purpose
The TDR Indicator Architecture page defines the general structure used to organize observable variables within Threshold Dynamics Research.
Unlike sector-specific pages such as ESCIS, this page does not define a particular indicator set for one domain. Instead, it explains the universal logic through which indicators are grouped, classified, and translated into resilience diagnostics across sectors.
Its purpose is to ensure methodological consistency across implementations while preserving sector-specific flexibility.
General Principle
Indicators are not isolated metrics. They are organized components of a threshold detection system.
Within the TDR framework, indicators must be capable of performing one or more of the following functions:
Pressures from outside the operational system
Structural or operational condition
Ability to absorb and reorganize
Economic or behavioral feedback loops
Data fragility and confidence limits
This functional view is what makes the architecture portable across sectors.
Four Indicator Families
These indicators measure pressures originating outside the immediate operational system. They capture conditions that push the system toward instability.
These indicators measure the structural or operational condition of the monitored system itself. They capture where the system currently stands relative to its normal operating regime.
These indicators measure the system's ability to absorb disturbance and reorganize. They are especially important for the construction of Lr.
These indicators capture endogenous feedback loops capable of accelerating deterioration. They are especially important for the construction of ΔV and for trajectory-sensitive diagnostics.
Hierarchical Organization
Indicators may be organized into a three-level hierarchy:
Observed or measured variables directly collected from data sources
Normalized or aggregated indicators derived from raw variables
Statistical or resilience signals extracted from processed indicators
This hierarchy allows the system to preserve a clear path from observation to governance variable.
Metadata Structure
Each indicator should include a minimum metadata schema:
This metadata layer is what ensures reproducibility and cross-sector consistency.
Sector Portability
The indicator architecture is designed to be sector-neutral at the structural level.
What changes between sectors is:
What remains constant is the organizational logic.
This allows the same architecture to support:
Relationship to Sector Pages
This page provides the general architecture. Sector pages provide concrete implementations.
Example: TDR Indicator Architecture explains what counts as external forcing, internal state, adaptive capacity, and amplification. ESCIS defines which specific energy indicators belong to those families.
In this sense, sector pages instantiate the general architecture rather than replace it.
Relationship to TDR Signal Processing
Indicators are the direct inputs to the TDR analytical engine.
Once organized into coherent families and metadata structures, they can be processed through:
Indicator architecture therefore sits between:
data sources → indicator architecture → signal processing
Relationship to TFP Variables
Indicators do not map one-to-one to governance outcomes. They first contribute to the generation of TFP variables:
From positional and boundary-sensitive indicators
From trend and acceleration-sensitive indicators
From data quality, uncertainty, and model confidence
From adaptive capacity and reversibility indicators
This is why architecture matters: it structures the path from empirical observation to prudential governance.
Objective
The objective of the TDR Indicator Architecture is to provide a stable, auditable, and cross-sector framework for organizing measurable variables into threshold-relevant diagnostics.
It is the universal design layer that makes sector-specific implementations scientifically coherent and institutionally interoperable.