PGA™ Complete Standards & Modules Index
Prediction Governance Architecture — Prediction Governance Layer
Official Prediction Governance Architecture Map for Human Forecasting, AI
Systems, Predictive Models, Prediction Markets, Autonomous Agents,
Organizations, Decision Systems, Collective Intelligence, and Future Predictive
Environments
This document serves as the official OOF® Prediction Governance architecture map and structural index used for Prediction Governance design, Prediction Lifecycle navigation, predictive-system diagnostics, architecture development, Prediction Governance assessment, lifecycle governance, Predictive Performance analysis, historical reconstruction, and interoperability across human forecasting, AI systems, predictive models, prediction markets, autonomous agents, organizations, decision systems, collective intelligence environments, and future predictive systems.
PGA™ consists of 12 Parent Standards and 60 Core Modules.
Additional standards and modules may be added when new governable Prediction spaces are identified. However, the standards and modules listed below form the core structural backbone of PGA™.
1. Prediction Object & Purpose Standard (POPS)
Governed Space: Prediction Object & Predictive Purpose
Core Question: What exactly is being predicted, for what purpose, over what horizon, and within what predictive boundary?
Modules:
POIM — Prediction Object Identification Module
PPDM — Prediction Purpose Definition Module
PTSM — Prediction Target Specification Module
PHDM — Prediction Horizon Definition Module
PBEM — Prediction Boundary Establishment Module
2. Prediction Methodology Standard (PMES)
Governed Space: Prediction Methodology
Core Question: By what documented and reproducible methodology is the prediction legitimately constructed?
Modules:
PMSM — Prediction Methodology Specification Module
MSDM — Methodological Structure Definition Module
PLDM — Prediction Logic Documentation Module
MAPM — Methodology Application Module
MVGM — Methodology Version Governance Module
3. Prediction Basis Standard (PBAS)
Governed Space: Prediction Basis
Core Question: What information, data, observations, evidence references, and signals legitimately form the basis of the prediction?
Modules:
PIIM — Prediction Information Identification Module
PSMM — Prediction Signal Mapping Module
SRVM — Source Relevance & Validity Module
ISUM — Information Sufficiency Module
PBTRM — Prediction Basis Traceability Module
4. Prediction Assumption Standard (PAS)
Governed Space: Prediction Assumptions
Core Question: What assumptions must hold for the prediction and its stated probability, confidence, feasibility, or expected outcome to remain meaningful?
Modules:
PAIM — Prediction Assumption Identification Module
ADMM — Assumption Dependency Mapping Module
ASNM — Assumption Sensitivity Module
AMAM — Assumption Materiality Assessment Module
ACGM — Assumption Change Governance Module
5. Prediction Formation Standard (PFOS)
Governed Space: Prediction Formation
Core Question: How are methodology, Prediction Basis, assumptions, and applicable conditions transformed into a specific governed prediction?
Modules:
PCOM — Prediction Component Organization Module
PCIM — Prediction Condition Integration Module
POFM — Prediction Output Formation Module
PSEM — Prediction State Establishment Module
PFTM — Prediction Formation Traceability Module
6. Prediction Probability & Uncertainty Standard (PPUS)
Governed Space: Predictive Probability & Uncertainty
Core Question: How should probability, uncertainty, confidence, ranges, and conditionality be represented without overstating what the prediction actually establishes?
Modules:
PRPM — Prediction Probability Representation Module
PUNM — Prediction Uncertainty Module
CFRM — Confidence Representation Module
PRGM — Prediction Range Governance Module
CPM — Conditional Probability Module
7. Prediction Feasibility Standard (PFES)
Governed Space: Prediction Feasibility
Core Question: Is the predicted outcome realistically achievable under the stated assumptions, constraints, time horizon, Prediction Basis, and relevant conditions?
Modules:
FCIM — Feasibility Condition Identification Module
PCMM — Prediction Constraint Mapping Module
OPAM — Operational Plausibility Assessment Module
EOFM — Execution & Outcome Feasibility Module
FSDM — Feasibility State Determination Module
8. Collective Prediction Governance Standard (CPGS)
Governed Space: Collective Prediction
Core Question: Under what conditions may predictions originating from multiple participants, models, agents, markets, or forecasting mechanisms be combined and represented as a legitimate collective prediction?
Modules:
PSDM — Prediction Source Diversity Module
PDVM — Prediction Diversity Validation Module
PAGM — Prediction Aggregation Governance Module
PICM — Prediction Independence & Concentration Module
CPRM — Collective Prediction Representation Module
9. Prediction Communication & Reliance Standard (PCRS)
Governed Space: Prediction Communication & Reliance
Core Question: How may a prediction be communicated, interpreted, and relied upon without exceeding what its methodology, uncertainty, feasibility, intended purpose, and governed conditions legitimately support?
Modules:
PRSM — Prediction Representation & Signaling Module
PLDIM — Prediction-Led Decision Interpretation Module
PIBM — Prediction Interpretation Boundary Module
RLCM — Reliance Legitimacy & Context Module
PUBM — Prediction Use Boundary Module
10. Prediction Monitoring & Revision Standard (PMRS)
Governed Space: Prediction Monitoring & Revision
Core Question: When changing information or conditions materially affect a prediction, when must it be preserved, reviewed, revised, superseded, or withdrawn?
Modules:
PCHM — Prediction Change Monitoring Module
PRVM — Prediction Revision Module
PSSM — Prediction Supersession Module
PWM — Prediction Withdrawal Module
11. Prediction Outcome & Performance Standard (POFPS)
Governed Space: Prediction Outcome & Predictive Performance
Core Question: Once a sufficiently governed outcome becomes available, how should the prediction be associated with that outcome and its predictive performance legitimately determined over time?
Modules:
POAM — Prediction Outcome Association Module
POCM — Prediction Outcome Comparison Module
PEMM — Prediction Error Measurement Module
PCALM — Prediction Calibration Module
PPCM — Predictive Performance Comparison Module
12. Prediction Record & Continuity Standard (PRCS)
Governed Space: Prediction Record & Historical Continuity
Core Question: How must a prediction and its complete history remain identifiable, reconstructable, versioned, and historically continuous across formation, revision, supersession, outcome, performance assessment, retirement, and lifecycle re-entry?
Modules:
PRFM — Prediction Record Formation Module
PVCM — Prediction Version Continuity Module
PHPM — Prediction History Preservation Module
PRSTM — Prediction Record State Transition Module
PRRM — Prediction Record Re-Entry Module
PGA™ Architecture Summary
Parent Standards: 12 Core Modules: 60
Core Governed Prediction Spaces
Prediction Object & Predictive Purpose Prediction Methodology Prediction Basis Prediction Assumptions Prediction Formation Predictive Probability & Uncertainty Prediction Feasibility Collective Prediction Prediction Communication & Reliance Prediction Monitoring & Revision Prediction Outcome & Predictive Performance Prediction Record & Historical Continuity
PGA™ Navigation Layer
Core Questions Map
POPS → What exactly is being predicted, for what purpose, over what horizon, and within what predictive boundary?
PMES → By what documented and reproducible methodology is the prediction legitimately constructed?
PBAS → What information, data, observations, evidence references, and signals legitimately form the basis of the prediction?
PAS → What assumptions must hold for the prediction and its stated probability, confidence, feasibility, or expected outcome to remain meaningful?
PFOS → How are methodology, Prediction Basis, assumptions, and applicable conditions transformed into a specific governed prediction?
PPUS → How should probability, uncertainty, confidence, ranges, and conditionality be represented without overstating what the prediction actually establishes?
PFES → Is the predicted outcome realistically achievable under the stated assumptions, constraints, time horizon, Prediction Basis, and relevant conditions?
CPGS → Under what conditions may predictions originating from multiple participants, models, agents, markets, or forecasting mechanisms be combined and represented as a legitimate collective prediction?
PCRS → How may a prediction be communicated, interpreted, and relied upon without exceeding what its methodology, uncertainty, feasibility, intended purpose, and governed conditions legitimately support?
PMRS → When changing information or conditions materially affect a prediction, when must it be preserved, reviewed, revised, superseded, or withdrawn?
POFPS → Once a sufficiently governed outcome becomes available, how should the prediction be associated with that outcome and its predictive performance legitimately determined over time?
PRCS → How must a prediction and its complete history remain identifiable, reconstructable, versioned, and historically continuous across formation, revision, supersession, outcome, performance assessment, retirement, and lifecycle re- entry?
Architectural Position
PGA™ governs the complete Prediction Governance lifecycle from definition of the Prediction Object and predictive purpose through Predictive Performance and historical continuity.
The architecture progresses:
Prediction Object & Purpose → Prediction Methodology → Prediction Basis → Prediction Assumptions → Prediction Formation → Probability & Uncertainty → Prediction Feasibility → Collective Prediction where applicable → Communication & Reliance → Monitoring & Revision → Outcome & Performance → Prediction Record & Continuity
Together these standards govern what is being predicted and why, how the prediction is methodologically constructed, what information and assumptions support it, how a specific prediction is formed, how probability and uncertainty are represented, whether the predicted outcome is feasible, how multiple predictions may legitimately become a collective prediction, how predictions are communicated and relied upon, how they respond to changing conditions, how they are associated with governed outcomes and assessed for Predictive Performance, and how their complete history remains identifiable and reconstructable.
Collective Prediction is conditional rather than mandatory.
The single-predictor path may proceed:
Prediction Feasibility → Communication & Reliance
The collective path may proceed:
Prediction Feasibility → Collective Prediction → Communication & Reliance
Architecture Position ≠ Mandatory Processing Through Every Optional Governance Space.
Its lifecycle becomes recursive when material predictive conditions change:
Governed Prediction → Monitoring → Review → Revision / Supersession / Withdrawal → Preserved Historical Prediction State
Where a sufficiently governed outcome becomes available:
Historical Prediction → Outcome Association → Outcome Comparison → Error Measurement → Calibration where applicable → Predictive Performance Comparison
Where a historical Prediction Record later becomes relevant:
Historical / Inactive Prediction Record → Re-Entry Evaluation → Re-Entry Classification → Re-Entered Prediction Record State or New Prediction Formation
This recursive structure allows Prediction Governance to remain responsive to changes in Prediction Basis, assumptions, probability, uncertainty, feasibility, communication, reliance, operational conditions, outcomes, Predictive Performance, and historical lifecycle state.
Cross-Architecture Boundary
PGA™ ↔ ORA™ ORA™ governs what is actually happening in Operational Reality . PGA™ governs the prediction and its relationship to sufficiently governed outcomes without establishing Operational Reality itself .
PGA™ ↔ VALIDOS™ PGA™ governs the Prediction Lifecycle and its methodological conditions . VALIDOS™ governs whether the total validation basis sufficiently supports a Validation Determination and intended reliance .
PGA™ ↔ INTEGROS® PGA™ governs prediction-specific methodology, basis, assumptions, formation, uncertainty, feasibility, lifecycle, performance, and continuity . INTEGROS® governs integrity across objects, states, evidence, and processes .
PGA™ ↔ ADIT® PGA™ governs which information, observations, evidence references, and signals form the Prediction Basis . ADIT® governs evidential observation, preservation, verification, examination, and auditability .
PGA™ ↔ AGA™ PGA™ governs Prediction Governance methodology and governed predictive conditions . AGA™ governs authority, responsibility, accountability, attribution, and decision relationships surrounding prediction-related activity .
PGA™ ↔ AIG® PGA™ governs the prediction as a governed object . AIG® governs AI behavioral governance and behavioral integrity .
PGA™ ↔ ASGA™ PGA™ governs predictions produced or used within predictive environments . ASGA™ governs autonomous- system authority, operation, action, constraints, escalation, and governability .
PGA™ ↔ SIMULOS® PGA™ governs predictions . SIMULOS® governs simulation purpose, structure, execution, outputs, and lifecycle .
PGA™ ↔ Prediction Models / Forecasting Mechanisms PGA™ governs the Prediction Lifecycle . Prediction models, human forecasters, agents, markets, and forecasting mechanisms govern or perform prediction generation, calculation, estimation, inference, judgment, or signal production .
Foundational Architecture Distinctions
Prediction Governance ≠ Prediction Generation
Prediction ≠ Operational Reality
Prediction Outcome Association ≠ Outcome Determination
Prediction Basis ≠ Evidence Governance
Prediction Governance ≠ Validation Determination
Probability ≠ Confidence
Probability ≠ Certainty
Confidence ≠ Certainty
High Probability ≠ High Confidence
Same Probability Value ≠ Same Predictive Meaning
Possible ≠ Plausible ≠ Feasible ≠ Probable
Feasible ≠ Probable
Multiple Predictors ≠ Independent Predictions
Number of Participants ≠ Information Diversity
Collective Signal ≠ Governed Collective Prediction
Market-Implied Probability ≠ Governed Probability Estimate
Market-Implied Probability ≠ Population Belief
Communicable ≠ Reliance-Eligible
Valid Initial Probability ≠ Valid Continuing Probability
Revision ≠ Historical Replacement
Supersession ≠ Deletion
Observed Accuracy ≠ Demonstrated Predictive Skill
Predictive Success ≠ Predictive Capability
Information Advantage ≠ Predictive Capability
Outcome Knowledge ≠ Predictive Capability
Outcome Knowledge ≠ Outcome Control
Decision Proximity ≠ Decision Authority
Predictive Accuracy ≠ Trading Profitability
Trading Profitability ≠ Predictive Reliability
Current Prediction State ≠ Complete Prediction History
Re-Entry ≠ New Origin by Default
Canonical Principle
PGA™ does not generate predictions, govern the future itself, establish Operational Reality, determine evidence validity, perform general Validation Governance, allocate accountability, govern general AI behavior, control autonomous action, or treat model outputs, simulation outputs, market prices, collective signals, or probability values as Governed Predictions by default. PGA™ governs the methodological conditions under which a Prediction Object and predictive purpose are defined, Prediction Methodology is documented, Prediction Basis and assumptions are governed, a specific prediction is formed, probability and uncertainty are represented, feasibility is assessed, collective prediction is governed where applicable, communication and reliance remain bounded, changing conditions trigger monitoring and revision, predictions are associated with sufficiently governed outcomes, Predictive Performance is assessed, and the complete Prediction Record remains identifiable, versioned, historically continuous, reconstructable, and capable of governed lifecycle re-entry.
PGA™ governs the prediction — not the future.
PGA™ Parent Standards
Prediction Object & Purpose Standard (POPS)
Prediction Methodology Standard (PMES)
Prediction Basis Standard (PBAS)
Prediction Assumption Standard (PAS)
Prediction Formation Standard (PFOS)
Prediction Probability & Uncertainty Standard (PPUS)
Prediction Feasibility Standard (PFES)
Collective Prediction Governance Standard (CPGS)
Prediction Communication & Reliance Standard (PCRS)
Prediction Monitoring & Revision Standard (PMRS)
Prediction Outcome & Performance Standard (POFPS)
Prediction Record & Continuity Standard (PRCS)